R/model_setup_functions.R
In benenns/OUD-Model: Semi-Markov Decision Model
Defines functions
check_sum_of_transition_array
check_transition_probability
markov_model
#' Markov model
#'
#' \code{markov_model} implements the main model functions to calculate Markov trace.
#'
#' @param l_params_all List with all parameters
#' @param err_stop Logical variable to stop model run if transition array is invalid, if TRUE. Default = FALSE.
#' @param verbose Logical variable to indicate print out of messages. Default = FALSE
#' @param checks Logical variable to indicate output of visual checks (e.g. slices of transition array)
#' @param cali Logical variable to adjust model cutoff to only calibration period
#' @return
#' a_TDP: Transition probability array
#' m_M_trace: Fully stratified markov cohort trace
#' m_M_agg_trace: Aggregated markov trace over base health states
#' m_M_agg_trace_death: State-specific mortality from each health state
#' m_M_agg_trace_sero: HIV seroconversions from each health state
#' @export
markov_model <- function(l_params_all, err_stop = FALSE, verbose = FALSE, checks = FALSE, cali = FALSE){
### Definition:
## Markov model implementation function
### Prefixes:
## l_* denotes list
## n_* denotes number
## a_* denotes 3-D array
## m_* denotes 2-D matrix
## v_* denotes vector
## df_* denotes data frame
## p_* denotes transition parameters
## c_* denotes costs
## u_* denotes utilities
### Arguments:
## l_params_all: List with all parameters
## verbose: Logical variable to indicate print out of messages
### Returns:
## a_TDP: Transition probability array.
## m_M_trace: Fully disaggregated matrix cohort trace.
## m_M_agg_trace: Aggregated trace over selected base health states.
## m_M_agg_trace_death: State-specific mortality from each health state.
## m_M_agg_trace_sero: HIV seroconversions from each health state.
##
with(as.list(l_params_all), {
#### Set up model states ####
l_dim_s <- list() # list of health states
# Base health states
BASE <- l_dim_s[[1]] <- c("MET", "METC", "BUP", "BUPC", "ABS", "REL", "ODN", "ODF")
# Injection/non-injection stratification
INJECT <- l_dim_s[[2]] <- c("NI", "INJ")
# Episodes (1-3)
EP <- l_dim_s[[3]] <- c("1", "2", "3")
# HIV/HCV status
SERO <- l_dim_s[[4]] <- c("NEG", "HIV", "HCV", "COI")
# Set model periods
if(cali == TRUE){
# Calibration periods
n_t <- (n_cali_max_per + 1) # if calibrating, cut model off at max calibration output (e.g. 36 months for three-years)
} else{
# Maximum model periods(regular)
n_t <- (n_age_max - n_age_init) * n_per # convert years
}
df_flat <- expand.grid(l_dim_s) #combine all elements together into vector of health states
df_flat <- dplyr::rename(df_flat, BASE = Var1,
INJECT = Var2,
EP = Var3,
SERO = Var4)
# Create index of states to populate transition matrices
# All treatment
TX <- df_flat$BASE == "BUP" | df_flat$BASE == "MET"
TXC <- df_flat$BASE == "BUPC" | df_flat$BASE == "METC"
all_TX <- df_flat$BASE == "BUP" | df_flat$BASE == "BUPC" | df_flat$BASE == "MET" | df_flat$BASE == "METC"
# All out-of-treatment (incl ABS)
OOT <- df_flat$BASE == "REL" | df_flat$BASE == "ABS" | df_flat$BASE == "ODN" | df_flat$BASE == "ODF"
# Buprenorphine
BUP <- df_flat$BASE == "BUP" # treatment only
BUPC <- df_flat$BASE == "BUPC" # concurrent opioid use
all_BUP <- df_flat$BASE == "BUP" | df_flat$BASE == "BUPC"
# Methadone
MET <- df_flat$BASE == "MET" # treatment only
METC <- df_flat$BASE == "METC" # concurrent opioid use
all_MET <- df_flat$BASE == "MET" | df_flat$BASE == "METC"
# Relapse
REL <- df_flat$BASE == "REL"
# Overdose
all_OD <- df_flat$BASE == "ODN" | df_flat$BASE == "ODF"
non_OD <- df_flat$BASE != "ODN" & df_flat$BASE != "ODF"
ODN <- df_flat$BASE == "ODN" # non-fatal overdose
ODF <- df_flat$BASE == "ODF" # fatal overdose
# Abstinence
ABS <- df_flat$BASE == "ABS"
# Serostatus
NEG <- df_flat$SERO == "NEG"
HIV <- df_flat$SERO == "HIV"
HCV <- df_flat$SERO == "HCV"
COI <- df_flat$SERO == "COI"
all_HIV <- df_flat$SERO == "HIV" | df_flat$SERO == "COI"
all_HCV <- df_flat$SERO == "HCV" | df_flat$SERO == "COI"
# Injection
INJ <- df_flat$INJECT == "INJ"
NI <- df_flat$INJECT == "NI"
# Episodes
EP1 <- df_flat$EP == "1"
EP2 <- df_flat$EP == "2"
EP3 <- df_flat$EP == "3"
df_n <- unite(df_flat, newCol) # combine columns into one data frame of all health states
v_n_states <- df_n[,1] # convert df into vector
n_states <- length(v_n_states) # total number of health states
l_index_s <- list(TX = TX, OOT = OOT,
BUP = BUP, BUPC = BUPC,
MET = MET, METC = METC,
REL = REL,
all_OD = all_OD, ODN = ODN, ODF = ODF,
ABS = ABS,
NEG = NEG, HIV = HIV, HCV = HCV, COI = COI,
INJ = INJ, NI = NI,
EP1 = EP1, EP2 = EP2, EP3 = EP3)
#### Overdose probability ####
#' Probability of non-fatal and fatal overdose
#'
#' \code{p_OD} is used to calculate overdose probabilities from health states. This function also requires additional overdose/fentanyl/naloxone parameters included in `l_params_all`
#'
#' @param rate Baseline overdose rate for health states
#' @param rate_fatal Fatal overdose rate
#' @param rate_fent Fentanyl overdose rate
#' @param multiplier Multiplier for elevated overdose in first month of health state
#' @param fent_mult Multiplier for overdose rate in health states when exposed to fentanyl
#' @param first_month Logical parameter to switch between month 1 and month 2+ for parameter estimation
#' @param fatal Logical parameter to switch between fatal/non-fatal overdose
#' @param injection Logical parameter to adjust rate calculation for injection/non-injection use
#' @param time Time period for time-varying parameters
#'
#' @return
#' `p_OD` monthly probability of fatal or non-fatal overdose from a given health state
#' @export
p_OD <- function(rate,# = rate,
rate_fatal,# = rate_fatal,
#rate_fent = n_fent_OD,
multiplier,# = multiplier,
fent_mult,# = fent_mult,
#fent_reduction_state = fent_reduction_state,
time,# = time,
first_month = FALSE,
fatal = FALSE,
injection = FALSE){
# Probability of successful naloxone use
p_NX_rev <- (p_witness * p_NX_used * p_NX_success)
# Probability of mortality from overdose accounting for baseline overdose fatality and effectiveness of naloxone
# Subsets overdose into fatal and non-fatal, conditional on different parameters
# Convert fatal overdose rate into probability of death following overdose
p_fatal_OD <- 1 - exp(-(rate_fatal))
# Convert fentanyl overdose rate into probability
#p_fent_OD <- 1 - exp(-(rate_fent))
# Probability of fentanyl exposure
# Generate time-varying probability of fentanyl exposure
# Currently modeling logarithmic growth based on 2018-2020 period (consider cutting off at some point, e.g., 5-years, 10-years)
#v_fent_exp_rate <- rep(0, n_t)
#for(i in 2:n_t){
# v_fent_exp_rate[1] <- -log(1- p_fent_exp_base)
# v_fent_exp_rate[i] <- v_fent_exp_rate[i-1] + n_fent_growth_rate
#}
#v_fent_exp_prob <- 1 - exp(-v_fent_exp_rate) # create vector of monthly fentanyl exposure probabilities (generated by growth rates from 2018-2020)
v_fent_exp_prob <- c(p_fent_exp_2018, p_fent_exp_2019, p_fent_exp_2020)
# Adjustment for injection/non-injection
#if (injection){
# v_fent_exp_prob <- v_fent_exp_prob
#} else{
# v_fent_exp_prob <- v_fent_exp_prob * p_ni_fent_reduction
#}
# Convert input monthly rates to monthly probabilities - multiply rates by first month multiplier before converting
if (injection == TRUE && first_month == TRUE){
p_base_OD <- 1 - exp(-(rate * n_INJ_OD_mult * multiplier * (v_fent_exp_prob[time] * fent_mult)))
#p_fent_OD <- 1 - exp(-(rate_fent * multiplier))
}
else if (injection == TRUE && first_month == FALSE){
p_base_OD <- 1 - exp(-(rate * n_INJ_OD_mult * (v_fent_exp_prob[time] * fent_mult)))
#p_fent_OD <- 1 - exp(-(rate_fent))
}
else if (injection == FALSE && first_month == TRUE){
p_base_OD <- 1 - exp(-(rate * multiplier * (v_fent_exp_prob[time] * p_ni_fent_reduction * fent_mult)))
#p_fent_OD <- 1 - exp(-(rate_fent * multiplier))
}
else if (injection == FALSE && first_month == FALSE){
p_base_OD <- 1 - exp(-(rate * (v_fent_exp_prob[time] * p_ni_fent_reduction * fent_mult)))
#p_fent_OD <- 1 - exp(-(rate_fent))
}
# Naloxone effect on fatal overdose
p_fatal_OD_NX <- p_fatal_OD * (1 - p_NX_rev)
# Probability of fentanyl exposure (adjusted for injection/non-injection)
#if (injection){
#p_fent_exp <- p_fent_exp
#} else{
# p_fent_exp <- p_fent_exp * p_ni_fent_reduction
#}
# Calculate fatal and non-fatal overdose probabilities
if (fatal == TRUE){
p_OD <- p_base_OD * p_fatal_OD_NX #((p_base_OD * (1 - p_fent_exp)) + (p_fent_OD * (p_fent_exp))) * p_fatal_OD_NX
} else{
p_OD <- p_base_OD * (1 - p_fatal_OD_NX) #((p_base_OD * (1 - p_fent_exp)) + (p_fent_OD * (p_fent_exp))) * (1 - p_fatal_OD_NX)
}
return(p_OD)
}
# Module to calculate probability of overdose from states
# Four separate matrices to account for state-time (first month vs. second+), and model-time (changing fentanyl prevalence, etc.)
#### Time-dependent overdose probabilities ####
# Time periods
time_periods <- n_cali_per
# Empty 2-D matrix
m_ODN <- m_ODN_first <- m_ODF <- m_ODF_first <- array(0, dim = c(n_states, time_periods),
dimnames = list(v_n_states, 1:time_periods))
#test<- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_TX_OD_mult, fent_mult = n_fent_OD_mult, time = 1, first_month = TRUE, fatal = FALSE, injection = FALSE)
for(i in 1:time_periods){
# Probability of overdose
# Non-fatal (first month)
m_ODN_first[BUP & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[MET & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[TXC & NI, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[REL & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[ODN & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[ABS & NI, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[BUP & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[MET & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[TXC & INJ, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[REL & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[ODN & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[ABS & INJ, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
# Fatal (first month)
m_ODF_first[BUP & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[MET & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[TXC & NI, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[REL & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[ODN & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[ABS & NI, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[BUP & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[MET & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[TXC & INJ, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[REL & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[ODN & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[ABS & INJ, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
# Non-fatal (month 2+)
m_ODN[BUP & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[MET & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[TXC & NI, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[REL & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[ODN & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[ABS & NI, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[BUP & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[MET & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[TXC & INJ, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[REL & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[ODN & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[ABS & INJ, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
# Fatal (month 2+)
m_ODF[BUP & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[MET & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[TXC & NI, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[REL & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[ODN & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[ABS & NI, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[BUP & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[MET & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[TXC & INJ, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[REL & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[ODN & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[ABS & INJ, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
}
if (checks){
# Overdose
write.csv(m_ODN_first,"checks/overdose/m_ODN_first.csv", row.names = TRUE)
write.csv(m_ODF_first,"checks/overdose/m_ODF_first.csv", row.names = TRUE)
write.csv(m_ODN,"checks/overdose/m_ODN.csv", row.names = TRUE)
write.csv(m_ODF,"checks/overdose/m_ODF.csv", row.names = TRUE)
} else{}
# Probability of non-overdose
m_non_OD_first <- 1 - (m_ODN_first + m_ODF_first)
m_non_OD <- 1 - (m_ODN + m_ODF)
#### Time-dependent remain probabilities ####
# Empty 2-D matrix
# Three matrices to account for overdose probabilities in 2018, 2019, and 2020+
#m_TDP_1 <- m_TDP_2 <- m_TDP_3 <- m_TDP_1_non_OD <- m_TDP_2_non_OD <- m_TDP_3_non_OD <- array(0, dim = c(n_states, n_t),
# dimnames = list(v_n_states, 1:n_t))
a_remain <- array(0, dim = c(n_states, time_periods, n_t),
dimnames = list(v_n_states, 1:time_periods, 1:n_t))
# Generate state-specific weibull parameters
# Shape
p_weibull_shape_BUP_NI <- p_weibull_shape_BUP_INJ <- p_weibull_shape_BUP
p_weibull_shape_MET_NI <- p_weibull_shape_MET_INJ <- p_weibull_shape_MET
p_weibull_shape_ABS_NI <- p_weibull_shape_ABS_INJ <- p_weibull_shape_ABS
p_weibull_shape_REL_NI <- p_weibull_shape_REL_INJ <- p_weibull_shape_REL
# Scale
p_weibull_scale_BUP_NI <- p_weibull_scale_BUP_INJ <- p_weibull_scale_BUP
p_weibull_scale_MET_NI <- p_weibull_scale_MET_INJ <- p_weibull_scale_MET
p_weibull_scale_ABS_NI <- p_weibull_scale_ABS_INJ <- p_weibull_scale_ABS
p_weibull_scale_REL_NI <- p_weibull_scale_REL_INJ <- p_weibull_scale_REL
# Generate state-specific frailty terms
# Non-injection
p_frailty_BUP_NI_1 <- p_frailty_BUP_1
p_frailty_BUP_NI_2 <- p_frailty_BUP_2
p_frailty_BUP_NI_3 <- p_frailty_BUP_3
p_frailty_BUPC_NI_1 <- p_frailty_BUP_1 * p_frailty_BUPC
p_frailty_BUPC_NI_2 <- p_frailty_BUP_2 * p_frailty_BUPC
p_frailty_BUPC_NI_3 <- p_frailty_BUP_3 * p_frailty_BUPC
p_frailty_MET_NI_1 <- p_frailty_MET_1
p_frailty_MET_NI_2 <- p_frailty_MET_2
p_frailty_MET_NI_3 <- p_frailty_MET_3
p_frailty_METC_NI_1 <- p_frailty_MET_1 * p_frailty_METC
p_frailty_METC_NI_2 <- p_frailty_MET_2 * p_frailty_METC
p_frailty_METC_NI_3 <- p_frailty_MET_3 * p_frailty_METC
p_frailty_ABS_NI_1 <- p_frailty_ABS_1
p_frailty_ABS_NI_2 <- p_frailty_ABS_2
p_frailty_ABS_NI_3 <- p_frailty_ABS_3
p_frailty_REL_NI_1 <- p_frailty_REL_1
p_frailty_REL_NI_2 <- p_frailty_REL_2
p_frailty_REL_NI_3 <- p_frailty_REL_3
# Injection
p_frailty_BUP_INJ_1 <- p_frailty_BUP_1 * p_frailty_BUP_INJ
p_frailty_BUP_INJ_2 <- p_frailty_BUP_2 * p_frailty_BUP_INJ
p_frailty_BUP_INJ_3 <- p_frailty_BUP_3 * p_frailty_BUP_INJ
p_frailty_BUPC_INJ_1 <- p_frailty_BUP_1 * p_frailty_BUP_INJ * p_frailty_BUPC
p_frailty_BUPC_INJ_2 <- p_frailty_BUP_2 * p_frailty_BUP_INJ * p_frailty_BUPC
p_frailty_BUPC_INJ_3 <- p_frailty_BUP_3 * p_frailty_BUP_INJ * p_frailty_BUPC
p_frailty_MET_INJ_1 <- p_frailty_MET_1 * p_frailty_MET_INJ
p_frailty_MET_INJ_2 <- p_frailty_MET_2 * p_frailty_MET_INJ
p_frailty_MET_INJ_3 <- p_frailty_MET_3 * p_frailty_MET_INJ
p_frailty_METC_INJ_1 <- p_frailty_MET_1 * p_frailty_MET_INJ * p_frailty_METC
p_frailty_METC_INJ_2 <- p_frailty_MET_2 * p_frailty_MET_INJ * p_frailty_METC
p_frailty_METC_INJ_3 <- p_frailty_MET_3 * p_frailty_MET_INJ * p_frailty_METC
p_frailty_ABS_INJ_1 <- p_frailty_ABS_1 * p_frailty_ABS_INJ
p_frailty_ABS_INJ_2 <- p_frailty_ABS_2 * p_frailty_ABS_INJ
p_frailty_ABS_INJ_3 <- p_frailty_ABS_3 * p_frailty_ABS_INJ
p_frailty_REL_INJ_1 <- p_frailty_REL_1 * p_frailty_REL_INJ
p_frailty_REL_INJ_2 <- p_frailty_REL_2 * p_frailty_REL_INJ
p_frailty_REL_INJ_3 <- p_frailty_REL_3 * p_frailty_REL_INJ
# Probability of remaining in health state
# All remain in fatal overdose, remain probability = 1
for(j in 1:time_periods){
for(i in 1:n_t){
# Non-injection
# Episode 1
a_remain[EP1 & BUP & NI, j, i] <- as.vector(exp(p_frailty_BUP_NI_1 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP1 & BUPC & NI, j, i] <- as.vector(exp(p_frailty_BUPC_NI_1 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP1 & MET & NI, j, i] <- as.vector(exp(p_frailty_MET_NI_1 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP1 & METC & NI, j, i] <- as.vector(exp(p_frailty_METC_NI_1 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP1 & ABS & NI, j, i] <- as.vector(exp(p_frailty_ABS_NI_1 * p_weibull_scale_ABS_NI * (((i - 1)^p_weibull_shape_ABS_NI) - (i^p_weibull_shape_ABS_NI))))
a_remain[EP1 & REL & NI, j, i] <- as.vector(exp(p_frailty_REL_NI_1 * p_weibull_scale_REL_NI * (((i - 1)^p_weibull_shape_REL_NI) - (i^p_weibull_shape_REL_NI))))
a_remain[EP1 & ODN & NI, j, i] <- 0
a_remain[EP1 & ODF & NI, j, i] <- 1
# Episode 2
a_remain[EP2 & BUP & NI, j, i] <- as.vector(exp(p_frailty_BUP_NI_2 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP2 & BUPC & NI, j, i] <- as.vector(exp(p_frailty_BUPC_NI_2 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP2 & MET & NI, j, i] <- as.vector(exp(p_frailty_MET_NI_2 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP2 & METC & NI, j, i] <- as.vector(exp(p_frailty_METC_NI_2 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP2 & ABS & NI, j, i] <- as.vector(exp(p_frailty_ABS_NI_2 * p_weibull_scale_ABS_NI * (((i - 1)^p_weibull_shape_ABS_NI) - (i^p_weibull_shape_ABS_NI))))
a_remain[EP2 & REL & NI, j, i] <- as.vector(exp(p_frailty_REL_NI_2 * p_weibull_scale_REL_NI * (((i - 1)^p_weibull_shape_REL_NI) - (i^p_weibull_shape_REL_NI))))
a_remain[EP2 & ODN & NI, j, i] <- 0
a_remain[EP2 & ODF & NI, j, i] <- 1
# Episode 3
a_remain[EP3 & BUP & NI, j, i] <- as.vector(exp(p_frailty_BUP_NI_3 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP3 & BUPC & NI, j, i] <- as.vector(exp(p_frailty_BUPC_NI_3 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP3 & MET & NI, j, i] <- as.vector(exp(p_frailty_MET_NI_3 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP3 & METC & NI, j, i] <- as.vector(exp(p_frailty_METC_NI_3 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP3 & ABS & NI, j, i] <- as.vector(exp(p_frailty_ABS_NI_3 * p_weibull_scale_ABS_NI * (((i - 1)^p_weibull_shape_ABS_NI) - (i^p_weibull_shape_ABS_NI))))
a_remain[EP3 & REL & NI, j, i] <- as.vector(exp(p_frailty_REL_NI_3 * p_weibull_scale_REL_NI * (((i - 1)^p_weibull_shape_REL_NI) - (i^p_weibull_shape_REL_NI))))
a_remain[EP3 & ODN & NI, j, i] <- 0
a_remain[EP3 & ODF & NI, j, i] <- 1
# Injection
# Episode 1
a_remain[EP1 & BUP & INJ, j, i] <- as.vector(exp(p_frailty_BUP_INJ_1 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP1 & BUPC & INJ, j, i] <- as.vector(exp(p_frailty_BUPC_INJ_1 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP1 & MET & INJ, j, i] <- as.vector(exp(p_frailty_MET_INJ_1 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP1 & METC & INJ, j, i] <- as.vector(exp(p_frailty_METC_INJ_1 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP1 & ABS & INJ, j, i] <- as.vector(exp(p_frailty_ABS_INJ_1 * p_weibull_scale_ABS_INJ * (((i - 1)^p_weibull_shape_ABS_INJ) - (i^p_weibull_shape_ABS_INJ))))
a_remain[EP1 & REL & INJ, j, i] <- as.vector(exp(p_frailty_REL_INJ_1 * p_weibull_scale_REL_INJ * (((i - 1)^p_weibull_shape_REL_INJ) - (i^p_weibull_shape_REL_INJ))))
a_remain[EP1 & ODN & INJ, j, i] <- 0
a_remain[EP1 & ODF & INJ, j, i] <- 1
# Episode 2
a_remain[EP2 & BUP & INJ, j, i] <- as.vector(exp(p_frailty_BUP_INJ_2 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP2 & BUPC & INJ, j, i] <- as.vector(exp(p_frailty_BUPC_INJ_2 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP2 & MET & INJ, j, i] <- as.vector(exp(p_frailty_MET_INJ_2 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP2 & METC & INJ, j, i] <- as.vector(exp(p_frailty_METC_INJ_2 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP2 & ABS & INJ, j, i] <- as.vector(exp(p_frailty_ABS_INJ_2 * p_weibull_scale_ABS_INJ * (((i - 1)^p_weibull_shape_ABS_INJ) - (i^p_weibull_shape_ABS_INJ))))
a_remain[EP2 & REL & INJ, j, i] <- as.vector(exp(p_frailty_REL_INJ_2 * p_weibull_scale_REL_INJ * (((i - 1)^p_weibull_shape_REL_INJ) - (i^p_weibull_shape_REL_INJ))))
a_remain[EP2 & ODN & INJ, j, i] <- 0
a_remain[EP2 & ODF & INJ, j, i] <- 1
# Episode 3
a_remain[EP3 & BUP & INJ, j, i] <- as.vector(exp(p_frailty_BUP_INJ_3 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP3 & BUPC & INJ, j, i] <- as.vector(exp(p_frailty_BUPC_INJ_3 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP3 & MET & INJ, j, i] <- as.vector(exp(p_frailty_MET_INJ_3 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP3 & METC & INJ, j, i] <- as.vector(exp(p_frailty_METC_INJ_3 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP3 & ABS & INJ, j, i] <- as.vector(exp(p_frailty_ABS_INJ_3 * p_weibull_scale_ABS_INJ * (((i - 1)^p_weibull_shape_ABS_INJ) - (i^p_weibull_shape_ABS_INJ))))
a_remain[EP3 & REL & INJ, j, i] <- as.vector(exp(p_frailty_REL_INJ_3 * p_weibull_scale_REL_INJ * (((i - 1)^p_weibull_shape_REL_INJ) - (i^p_weibull_shape_REL_INJ))))
a_remain[EP3 & ODN & INJ, j, i] <- 0
a_remain[EP3 & ODF & INJ, j, i] <- 1
}
}
# Modify TDP for non-overdose
#for(j in 1:time_periods){
# for(i in 1){
# a_remain_non_OD[, j, i] <- a_remain[, j, i] * m_non_OD_first[, j]
# }
# for(i in 2:n_t){
# a_remain_non_OD[, j, i] <- a_remain_non_OD[, j, i] * m_non_OD[, j]
# }
#}
# Probability of state-exit
m_remain_1 <- a_remain[, 1, ]
m_remain_2 <- a_remain[, 2, ]
m_remain_3 <- a_remain[, 3, ]
m_leave_1 <- 1 - a_remain[, 1, ]
m_leave_2 <- 1 - a_remain[, 2, ]
m_leave_3 <- 1 - a_remain[, 3, ]
#m_leave_1_non_OD <- 1 - m_TDP_1_non_OD
#m_leave_2_non_OD <- 1 - m_TDP_2_non_OD
#m_leave_3_non_OD <- 1 - m_TDP_3_non_OD
if(checks){
# Time dependent state-exit probabilities (from weibull estimates)
write.csv(m_remain_1,"checks/state-time dependent transitions/m_TDP_1.csv", row.names = TRUE)
write.csv(m_remain_2,"checks/state-time dependent transitions/m_TDP_2.csv", row.names = TRUE)
write.csv(m_remain_3,"checks/state-time dependent transitions/m_TDP_3.csv", row.names = TRUE)
#write.csv(m_TDP_1_non_OD,"checks/state-time dependent transitions/m_TDP_1_non_OD.csv", row.names = TRUE)
#write.csv(m_TDP_2_non_OD,"checks/state-time dependent transitions/m_TDP_2_non_OD.csv", row.names = TRUE)
#write.csv(m_TDP_3_non_OD,"checks/state-time dependent transitions/m_TDP_3_non_OD.csv", row.names = TRUE)
write.csv(m_leave_1,"checks/state-time dependent transitions/m_leave_1.csv", row.names = TRUE)
write.csv(m_leave_2,"checks/state-time dependent transitions/m_leave_2.csv", row.names = TRUE)
write.csv(m_leave_3,"checks/state-time dependent transitions/m_leave_3.csv", row.names = TRUE)
#write.csv(m_leave_1_non_OD,"checks/state-time dependent transitions/m_leave_1_non_OD.csv", row.names = TRUE)
#write.csv(m_leave_2_non_OD,"checks/state-time dependent transitions/m_leave_2_non_OD.csv", row.names = TRUE)
#write.csv(m_leave_3_non_OD,"checks/state-time dependent transitions/m_leave_3_non_OD.csv", row.names = TRUE)
} else{}
#### Mortality ####
#' Mortality probability estimates
#'
#' \code{v_mort} is used to populate mortality probability vectors.
#'
#' @param hr
#' @param per
#' @return
#' Mortality vectors for each age applied to model periods (months or weeks), includes state-specific hr.
#' Overdose deaths tracked as "ODF"
#' @export
v_mort <- function(hr = hr, per = per){
v_mort <- rep((1 - exp(-v_r_mort_by_age[n_age_init:(n_age_max - 1), ] * (1/per) * hr)), each = per) #currently working in months
return(v_mort)
}
# Non-injection
v_mort_BUP_NI <- v_mort(hr = hr_BUP_NI, per = n_per)
v_mort_BUPC_NI <- v_mort(hr = hr_BUPC_NI, per = n_per)
v_mort_MET_NI <- v_mort(hr = hr_MET_NI, per = n_per)
v_mort_METC_NI <- v_mort(hr = hr_METC_NI, per = n_per)
v_mort_REL_NI <- v_mort(hr = hr_REL_NI, per = n_per)
v_mort_ODN_NI <- v_mort(hr = hr_ODN_NI, per = n_per) # Mortality equal for REL/ODN (fatal overdoses counted separately)
v_mort_ODF_NI <- rep(0, n_t) # stay in ODF, not tracked in "death"
v_mort_ABS_NEG_NI <- v_mort(hr = hr_ABS_NI, per = n_per)
v_mort_ABS_HIV_NI <- v_mort(hr = hr_HIV_NI, per = n_per)
v_mort_ABS_HCV_NI <- v_mort(hr = hr_HCV_NI, per = n_per)
v_mort_ABS_COI_NI <- v_mort(hr = hr_COI_NI, per = n_per)
# Injection
v_mort_BUP_INJ <- v_mort(hr = hr_BUP_INJ, per = n_per)
v_mort_BUPC_INJ <- v_mort(hr = hr_BUPC_INJ, per = n_per)
v_mort_MET_INJ <- v_mort(hr = hr_MET_INJ, per = n_per)
v_mort_METC_INJ <- v_mort(hr = hr_METC_INJ, per = n_per)
v_mort_REL_INJ <- v_mort(hr = hr_REL_INJ, per = n_per)
v_mort_ODN_INJ <- v_mort(hr = hr_ODN_INJ, per = n_per) # Mortality equal for REL/ODN (fatal overdoses counted separately)
v_mort_ODF_INJ <- rep(0, n_t) # stay in ODF, not tracked in "death"
v_mort_ABS_NEG_INJ <- v_mort(hr = hr_ABS_INJ, per = n_per)
v_mort_ABS_HIV_INJ <- v_mort(hr = hr_HIV_INJ, per = n_per)
v_mort_ABS_HCV_INJ <- v_mort(hr = hr_HCV_INJ, per = n_per)
v_mort_ABS_COI_INJ <- v_mort(hr = hr_COI_INJ, per = n_per)
# Create empty mortality matrix
m_mort <- array(0, dim = c(n_states, n_t),
dimnames = list(v_n_states, 1:n_t))
# Populate mortality matrix (death probability from each state)
for (i in 1:n_t){
# Non-injection
m_mort[BUP & NI, i] <- v_mort_BUP_NI[i]
m_mort[BUPC & NI, i] <- v_mort_BUPC_NI[i]
m_mort[MET & NI, i] <- v_mort_MET_NI[i]
m_mort[METC & NI, i] <- v_mort_METC_NI[i]
m_mort[REL & NI, i] <- v_mort_REL_NI[i]
m_mort[ODN & NI, i] <- v_mort_ODN_NI[i] # using background excess mortality for relapse in non-fatal overdose
m_mort[ODF & NI, i] <- v_mort_ODF_NI[i] # transition to death = 0
m_mort[ABS & NI & NEG, i] <- v_mort_ABS_NEG_NI[i]
m_mort[ABS & NI & HIV, i] <- v_mort_ABS_HIV_NI[i]
m_mort[ABS & NI & HCV, i] <- v_mort_ABS_HCV_NI[i]
m_mort[ABS & NI & COI, i] <- v_mort_ABS_COI_NI[i]
# Injection
m_mort[BUP & INJ, i] <- v_mort_BUP_INJ[i]
m_mort[BUPC & INJ, i] <- v_mort_BUPC_INJ[i]
m_mort[MET & INJ, i] <- v_mort_MET_INJ[i]
m_mort[METC & INJ, i] <- v_mort_METC_INJ[i]
m_mort[REL & INJ, i] <- v_mort_REL_INJ[i]
m_mort[ODN & INJ, i] <- v_mort_ODN_INJ[i] # using background excess mortality for relapse in non-fatal overdose
m_mort[ODF & INJ, i] <- v_mort_ODF_INJ[i] # transition to death = 0
m_mort[ABS & INJ & NEG, i] <- v_mort_ABS_NEG_INJ[i]
m_mort[ABS & INJ & HIV, i] <- v_mort_ABS_HIV_INJ[i]
m_mort[ABS & INJ & HCV, i] <- v_mort_ABS_HCV_INJ[i]
m_mort[ABS & INJ & COI, i] <- v_mort_ABS_COI_INJ[i]
}
if(checks){
# Mortality matrix
write.csv(m_mort,"checks/mortality/m_mort.csv", row.names = TRUE)
} else{}
# Alive probability in each period
m_alive <- 1 - m_mort
#### Unconditional transition probabilities ####
# Empty 2-D unconditional transition matrix (from states, to states)
# Create 2 matrices: 1 - First four weeks (higher OD prob)
#m_UP <- m_UP_4wk <- array(0, dim = c(n_states, n_states),
# dimnames = list(v_n_states, v_n_states))
# Create as array (different probabilities for model-time varying overdose)
a_UP <- a_UP_first <- array(0, dim = c(n_states, n_states, time_periods),
dimnames = list(v_n_states, v_n_states, 1:time_periods))
# Populate unconditional transition matrix
# Remove overdose and non-overdose remain probabilities
#p_BUP_non_OD_remain_NI <- 1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i] - a_remain_non_OD[BUP & NI, ]
#p_BUPC_non_OD_remain_NI <- 1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i] - m_TDP_1_non_OD[BUPC & NI, ]
#p_MET_non_OD_remain_NI <- 1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i] - m_TDP_1_non_OD[MET & NI, ]
#p_METC_non_OD_remain_NI <- 1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i] - m_TDP_1_non_OD[METC & NI, ]
#p_ABS_non_OD_remain_NI <- 1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i] - m_TDP_1_non_OD[ABS & NI, ]
#p_REL_non_OD_remain_NI <- 1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i] - m_TDP_1_non_OD[REL & NI, ]
# Overdose probability populated first, accounting for higher probability of overdose transition in first month
for (i in 1:time_periods){
# Non-Injection
# From BUP
# First month
a_UP_first[BUP & NI, BUPC & NI, i] <- p_BUP_BUPC_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i] - m_TDP_1_non_OD[BUP & NI, ])
a_UP_first[BUP & NI, MET & NI, i] <- p_BUP_MET_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i])
a_UP_first[BUP & NI, METC & NI, i] <- p_BUP_METC_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i])
a_UP_first[BUP & NI, ABS & NI, i] <- p_BUP_ABS_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i])
a_UP_first[BUP & NI, REL & NI, i] <- p_BUP_REL_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i])
#a_UP_first[BUP & NI, ODN & NI, i] <- m_ODN_first[BUP & NI, i]
#a_UP_first[BUP & NI, ODF & NI, i] <- m_ODF_first[BUP & NI, i]
# Month 2+
a_UP[BUP & NI, BUPC & NI, i] <- p_BUP_BUPC_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
a_UP[BUP & NI, MET & NI, i] <- p_BUP_MET_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
a_UP[BUP & NI, METC & NI, i] <- p_BUP_METC_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
a_UP[BUP & NI, ABS & NI, i] <- p_BUP_ABS_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
a_UP[BUP & NI, REL & NI, i] <- p_BUP_REL_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
#a_UP[BUP & NI, ODN & NI, i] <- m_ODN[BUP & NI, i]
#a_UP[BUP & NI, ODF & NI, i] <- m_ODF[BUP & NI, i]
# From BUPC
# First month
a_UP_first[BUPC & NI, BUP & NI, i] <- p_BUPC_BUP_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
a_UP_first[BUPC & NI, MET & NI, i] <- p_BUPC_MET_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
a_UP_first[BUPC & NI, METC & NI, i] <- p_BUPC_METC_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
a_UP_first[BUPC & NI, ABS & NI, i] <- p_BUPC_ABS_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
a_UP_first[BUPC & NI, REL & NI, i] <- p_BUPC_REL_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
#a_UP_first[BUPC & NI, ODN & NI, i] <- m_ODN_first[BUPC & NI, i]
#a_UP_first[BUPC & NI, ODF & NI, i] <- m_ODF_first[BUPC & NI, i]
# Month 2+
a_UP[BUPC & NI, BUP & NI, i] <- p_BUPC_BUP_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
a_UP[BUPC & NI, MET & NI, i] <- p_BUPC_MET_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
a_UP[BUPC & NI, METC & NI, i] <- p_BUPC_METC_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
a_UP[BUPC & NI, ABS & NI, i] <- p_BUPC_ABS_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
a_UP[BUPC & NI, REL & NI, i] <- p_BUPC_REL_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
#a_UP[BUPC & NI, ODN & NI, i] <- m_ODN[BUPC & NI, i]
#a_UP[BUPC & NI, ODF & NI, i] <- m_ODF[BUPC & NI, i]
# From MET
# First month
a_UP_first[MET & NI, METC & NI, i] <- p_MET_METC_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
a_UP_first[MET & NI, BUP & NI, i] <- p_MET_BUP_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
a_UP_first[MET & NI, BUPC & NI, i] <- p_MET_BUPC_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
a_UP_first[MET & NI, ABS & NI, i] <- p_MET_ABS_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
a_UP_first[MET & NI, REL & NI, i] <- p_MET_REL_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
#a_UP_first[MET & NI, ODN & NI, i] <- m_ODN_first[MET & NI, i]
#a_UP_first[MET & NI, ODF & NI, i] <- m_ODF_first[MET & NI, i]
# Month 2+
a_UP[MET & NI, METC & NI, i] <- p_MET_METC_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
a_UP[MET & NI, BUP & NI, i] <- p_MET_BUP_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
a_UP[MET & NI, BUPC & NI, i] <- p_MET_BUPC_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
a_UP[MET & NI, ABS & NI, i] <- p_MET_ABS_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
a_UP[MET & NI, REL & NI, i] <- p_MET_REL_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
#a_UP[MET & NI, ODN & NI, i] <- m_ODN[MET & NI, i]
#a_UP[MET & NI, ODF & NI, i] <- m_ODF[MET & NI, i]
# From METC
# First month
a_UP_first[METC & NI, MET & NI, i] <- p_METC_MET_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
a_UP_first[METC & NI, BUP & NI, i] <- p_METC_BUP_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
a_UP_first[METC & NI, BUPC & NI, i] <- p_METC_BUPC_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
a_UP_first[METC & NI, ABS & NI, i] <- p_METC_ABS_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
a_UP_first[METC & NI, REL & NI, i] <- p_METC_REL_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
#a_UP_first[METC & NI, ODN & NI, i] <- m_ODN_first[METC & NI, i]
#a_UP_first[METC & NI, ODF & NI, i] <- m_ODF_first[METC & NI, i]
# Month 2+
a_UP[METC & NI, MET & NI, i] <- p_METC_MET_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
a_UP[METC & NI, BUP & NI, i] <- p_METC_BUP_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
a_UP[METC & NI, BUPC & NI, i] <- p_METC_BUPC_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
a_UP[METC & NI, ABS & NI, i] <- p_METC_ABS_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
a_UP[METC & NI, REL & NI, i] <- p_METC_REL_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
#a_UP[METC & NI, ODN & NI, i] <- m_ODN[METC & NI, i]
#a_UP[METC & NI, ODF & NI, i] <- m_ODF[METC & NI, i]
# From ABS
# First month
a_UP_first[ABS & NI, REL & NI, i] <- p_ABS_REL_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
a_UP_first[ABS & NI, MET & NI, i] <- p_ABS_MET_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
a_UP_first[ABS & NI, METC & NI, i] <- p_ABS_METC_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
a_UP_first[ABS & NI, BUP & NI, i] <- p_ABS_BUP_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
a_UP_first[ABS & NI, BUPC & NI, i] <- p_ABS_BUPC_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
#a_UP_first[ABS & NI, ODN & NI, i] <- m_ODN_first[ABS & NI, i]
#a_UP_first[ABS & NI, ODF & NI, i] <- m_ODF_first[ABS & NI, i]
# Month 2+
a_UP[ABS & NI, REL & NI, i] <- p_ABS_REL_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
a_UP[ABS & NI, MET & NI, i] <- p_ABS_MET_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
a_UP[ABS & NI, METC & NI, i] <- p_ABS_METC_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
a_UP[ABS & NI, BUP & NI, i] <- p_ABS_BUP_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
a_UP[ABS & NI, BUPC & NI, i] <- p_ABS_BUPC_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
#a_UP[ABS & NI, ODN & NI, i] <- m_ODN[ABS & NI, i]
#a_UP[ABS & NI, ODF & NI, i] <- m_ODF[ABS & NI, i]
# From REL
# First month
a_UP_first[REL & NI, MET & NI, i] <- p_REL_MET_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
a_UP_first[REL & NI, METC & NI, i] <- p_REL_METC_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
a_UP_first[REL & NI, BUP & NI, i] <- p_REL_BUP_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
a_UP_first[REL & NI, BUPC & NI, i] <- p_REL_BUPC_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
a_UP_first[REL & NI, ABS & NI, i] <- p_REL_ABS_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
#a_UP_first[REL & NI, ODN & NI, i] <- m_ODN_first[REL & NI, i]
#a_UP_first[REL & NI, ODF & NI, i] <- m_ODF_first[REL & NI, i]
# Month 2+
a_UP[REL & NI, MET & NI, i] <- p_REL_MET_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
a_UP[REL & NI, METC & NI, i] <- p_REL_METC_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
a_UP[REL & NI, BUP & NI, i] <- p_REL_BUP_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
a_UP[REL & NI, BUPC & NI, i] <- p_REL_BUPC_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
a_UP[REL & NI, ABS & NI, i] <- p_REL_ABS_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
#a_UP[REL & NI, ODN & NI, i] <- m_ODN[REL & NI, i]
#a_UP[REL & NI, ODF & NI, i] <- m_ODF[REL & NI, i]
# From OD (first month same)
a_UP[ODN & NI, MET & NI, i] <- a_UP_first[ODN & NI, MET & NI, i] <- p_ODN_MET_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, METC & NI, i] <- a_UP_first[ODN & NI, METC & NI, i] <- p_ODN_METC_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, BUP & NI, i] <- a_UP_first[ODN & NI, BUP & NI, i] <- p_ODN_BUP_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, BUPC & NI, i] <- a_UP_first[ODN & NI, BUPC & NI, i] <- p_ODN_BUPC_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, ABS & NI, i] <- a_UP_first[ODN & NI, ABS & NI, i] <- p_ODN_ABS_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, REL & NI, i] <- a_UP_first[ODN & NI, REL & NI, i] <- p_ODN_REL_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
#a_UP[ODN & NI, ODF & NI, i] <- m_ODF[ODN & NI, i]
# Injection
# From BUP
# First month
a_UP_first[BUP & INJ, BUPC & INJ, i] <- p_BUP_BUPC_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
a_UP_first[BUP & INJ, MET & INJ, i] <- p_BUP_MET_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
a_UP_first[BUP & INJ, METC & INJ, i] <- p_BUP_METC_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
a_UP_first[BUP & INJ, ABS & INJ, i] <- p_BUP_ABS_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
a_UP_first[BUP & INJ, REL & INJ, i] <- p_BUP_REL_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
#a_UP_first[BUP & INJ, ODN & INJ, i] <- m_ODN_first[BUP & INJ, i]
#a_UP_first[BUP & INJ, ODF & INJ, i] <- m_ODF_first[BUP & INJ, i]
# Month 2+
a_UP[BUP & INJ, BUPC & INJ, i] <- p_BUP_BUPC_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
a_UP[BUP & INJ, MET & INJ, i] <- p_BUP_MET_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
a_UP[BUP & INJ, METC & INJ, i] <- p_BUP_METC_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
a_UP[BUP & INJ, ABS & INJ, i] <- p_BUP_ABS_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
a_UP[BUP & INJ, REL & INJ, i] <- p_BUP_REL_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
#a_UP[BUP & INJ, ODN & INJ, i] <- m_ODN[BUP & INJ, i]
#a_UP[BUP & INJ, ODF & INJ, i] <- m_ODF[BUP & INJ, i]
# From BUPC
# First month
a_UP_first[BUPC & INJ, BUP & INJ, i] <- p_BUPC_BUP_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
a_UP_first[BUPC & INJ, MET & INJ, i] <- p_BUPC_MET_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
a_UP_first[BUPC & INJ, METC & INJ, i] <- p_BUPC_METC_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
a_UP_first[BUPC & INJ, ABS & INJ, i] <- p_BUPC_ABS_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
a_UP_first[BUPC & INJ, REL & INJ, i] <- p_BUPC_REL_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
#a_UP_first[BUPC & INJ, ODN & INJ, i] <- m_ODN_first[BUPC & INJ, i]
#a_UP_first[BUPC & INJ, ODF & INJ, i] <- m_ODF_first[BUPC & INJ, i]
# Month 2+
a_UP[BUPC & INJ, BUP & INJ, i] <- p_BUPC_BUP_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
a_UP[BUPC & INJ, MET & INJ, i] <- p_BUPC_MET_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
a_UP[BUPC & INJ, METC & INJ, i] <- p_BUPC_METC_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
a_UP[BUPC & INJ, ABS & INJ, i] <- p_BUPC_ABS_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
a_UP[BUPC & INJ, REL & INJ, i] <- p_BUPC_REL_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
#a_UP[BUPC & INJ, ODN & INJ, i] <- m_ODN[BUPC & INJ, i]
#a_UP[BUPC & INJ, ODF & INJ, i] <- m_ODF[BUPC & INJ, i]
# From MET
# First month
a_UP_first[MET & INJ, METC & INJ, i] <- p_MET_METC_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
a_UP_first[MET & INJ, BUP & INJ, i] <- p_MET_BUP_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
a_UP_first[MET & INJ, BUPC & INJ, i] <- p_MET_BUPC_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
a_UP_first[MET & INJ, ABS & INJ, i] <- p_MET_ABS_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
a_UP_first[MET & INJ, REL & INJ, i] <- p_MET_REL_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
#a_UP_first[MET & INJ, ODN & INJ, i] <- m_ODN_first[MET & INJ, i]
#a_UP_first[MET & INJ, ODF & INJ, i] <- m_ODF_first[MET & INJ, i]
# Month 2+
a_UP[MET & INJ, METC & INJ, i] <- p_MET_METC_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
a_UP[MET & INJ, BUP & INJ, i] <- p_MET_BUP_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
a_UP[MET & INJ, BUPC & INJ, i] <- p_MET_BUPC_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
a_UP[MET & INJ, ABS & INJ, i] <- p_MET_ABS_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
a_UP[MET & INJ, REL & INJ, i] <- p_MET_REL_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
#a_UP[MET & INJ, ODN & INJ, i] <- m_ODN[MET & INJ, i]
#a_UP[MET & INJ, ODF & INJ, i] <- m_ODF[MET & INJ, i]
# From METC
# First month
a_UP_first[METC & INJ, MET & INJ, i] <- p_METC_MET_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
a_UP_first[METC & INJ, BUP & INJ, i] <- p_METC_BUP_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
a_UP_first[METC & INJ, BUPC & INJ, i] <- p_METC_BUPC_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
a_UP_first[METC & INJ, ABS & INJ, i] <- p_METC_ABS_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
a_UP_first[METC & INJ, REL & INJ, i] <- p_METC_REL_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
#a_UP_first[METC & INJ, ODN & INJ, i] <- m_ODN_first[METC & INJ, i]
#a_UP_first[METC & INJ, ODF & INJ, i] <- m_ODF_first[METC & INJ, i]
# Month 2+
a_UP[METC & INJ, MET & INJ, i] <- p_METC_MET_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
a_UP[METC & INJ, BUP & INJ, i] <- p_METC_BUP_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
a_UP[METC & INJ, BUPC & INJ, i] <- p_METC_BUPC_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
a_UP[METC & INJ, ABS & INJ, i] <- p_METC_ABS_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
a_UP[METC & INJ, REL & INJ, i] <- p_METC_REL_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
#a_UP[METC & INJ, ODN & INJ, i] <- m_ODN[METC & INJ, i]
#a_UP[METC & INJ, ODF & INJ, i] <- m_ODF[METC & INJ, i]
# From ABS
# First month
a_UP_first[ABS & INJ, REL & INJ, i] <- p_ABS_REL_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
a_UP_first[ABS & INJ, MET & INJ, i] <- p_ABS_MET_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
a_UP_first[ABS & INJ, METC & INJ, i] <- p_ABS_METC_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
a_UP_first[ABS & INJ, BUP & INJ, i] <- p_ABS_BUP_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
a_UP_first[ABS & INJ, BUPC & INJ, i] <- p_ABS_BUPC_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
#a_UP_first[ABS & INJ, ODN & INJ, i] <- m_ODN_first[ABS & INJ, i]
#a_UP_first[ABS & INJ, ODF & INJ, i] <- m_ODF_first[ABS & INJ, i]
# Month 2+
a_UP[ABS & INJ, REL & INJ, i] <- p_ABS_REL_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
a_UP[ABS & INJ, MET & INJ, i] <- p_ABS_MET_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
a_UP[ABS & INJ, METC & INJ, i] <- p_ABS_METC_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
a_UP[ABS & INJ, BUP & INJ, i] <- p_ABS_BUP_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
a_UP[ABS & INJ, BUPC & INJ, i] <- p_ABS_BUPC_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
#a_UP[ABS & INJ, ODN & INJ, i] <- m_ODN[ABS & INJ, i]
#a_UP[ABS & INJ, ODF & INJ, i] <- m_ODF[ABS & INJ, i]
# From REL
# First month
a_UP_first[REL & INJ, MET & INJ, i] <- p_REL_MET_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
a_UP_first[REL & INJ, METC & INJ, i] <- p_REL_METC_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
a_UP_first[REL & INJ, BUP & INJ, i] <- p_REL_BUP_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
a_UP_first[REL & INJ, BUPC & INJ, i] <- p_REL_BUPC_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
a_UP_first[REL & INJ, ABS & INJ, i] <- p_REL_ABS_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
#a_UP_first[REL & INJ, ODN & INJ, i] <- m_ODN_first[REL & INJ, i]
#a_UP_first[REL & INJ, ODF & INJ, i] <- m_ODF_first[REL & INJ, i]
# Month 2+
a_UP[REL & INJ, MET & INJ, i] <- p_REL_MET_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
a_UP[REL & INJ, METC & INJ, i] <- p_REL_METC_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
a_UP[REL & INJ, BUP & INJ, i] <- p_REL_BUP_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
a_UP[REL & INJ, BUPC & INJ, i] <- p_REL_BUPC_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
a_UP[REL & INJ, ABS & INJ, i] <- p_REL_ABS_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
#a_UP[REL & INJ, ODN & INJ, i] <- m_ODN[REL & INJ, i]
#a_UP[REL & INJ, ODF & INJ, i] <- m_ODF[REL & INJ, i]
# From OD (first month same)
a_UP[ODN & INJ, MET & INJ, i] <- a_UP_first[ODN & INJ, MET & INJ, i] <- p_ODN_MET_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, METC & INJ, i] <- a_UP_first[ODN & INJ, METC & INJ, i] <- p_ODN_METC_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, BUP & INJ, i] <- a_UP_first[ODN & INJ, BUP & INJ, i] <- p_ODN_BUP_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, BUPC & INJ, i] <- a_UP_first[ODN & INJ, BUPC & INJ, i] <- p_ODN_BUPC_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, ABS & INJ, i] <- a_UP_first[ODN & INJ, ABS & INJ, i] <- p_ODN_ABS_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, REL & INJ, i] <- a_UP_first[ODN & INJ, REL & INJ, i] <- p_ODN_REL_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
#a_UP[ODN & INJ, ODF & INJ, i] <- m_ODF[ODN & INJ, i]
}
if(checks){
# Time dependent state-exit probabilities (from weibull estimates)
write.csv(a_UP_first[, , 1],"checks/UP/a_UP_first_1.csv", row.names = TRUE)
write.csv(a_UP_first[, , 2],"checks/UP/a_UP_first_2.csv", row.names = TRUE)
write.csv(a_UP_first[, , 3],"checks/UP/a_UP_first_3.csv", row.names = TRUE)
write.csv(a_UP[, , 1],"checks/UP/a_UP_1.csv", row.names = TRUE)
write.csv(a_UP[, , 2],"checks/UP/a_UP_2.csv", row.names = TRUE)
write.csv(a_UP[, , 3],"checks/UP/a_UP_3.csv", row.names = TRUE)
} else{}
#### Create full time-dependent transition array ####
# Empty 3-D array
a_TDP_1 <- a_TDP_2 <- a_TDP_3 <- array(0, dim = c(n_states, n_states, n_t),
dimnames = list(v_n_states, v_n_states, 1:n_t))
# Add transitions conditional on state-exit (m_leave = 1 - remain)
# Three transition arrays to account for model-time-varying overdose (2018, 2019, 2020+)
# Modified transitions for first month (state-time)
for (i in 1){
a_TDP_1[, , i] <- a_UP_first[, , 1] * m_leave_1[, i]
a_TDP_2[, , i] <- a_UP_first[, , 2] * m_leave_2[, i]
a_TDP_3[, , i] <- a_UP_first[, , 3] * m_leave_3[, i]
}
## All transitions 2+ months
for (i in 2:n_t){
#a_TDP[, , i] <- m_UP * m_leave[, i]
a_TDP_1[, , i] <- a_UP[, , 1] * m_leave_1[, i]
a_TDP_2[, , i] <- a_UP[, , 2] * m_leave_2[, i]
a_TDP_3[, , i] <- a_UP[, , 3] * m_leave_3[, i]
}
# Add time-dependent remain probabilities
for (i in 1:n_t){
# Non-injection
# Episode 1
# BUP
a_TDP_1[EP1 & BUP & NI, EP1 & BUP & NI, i] <- m_remain_1[EP1 & BUP & NI, i]
a_TDP_2[EP1 & BUP & NI, EP1 & BUP & NI, i] <- m_remain_2[EP1 & BUP & NI, i]
a_TDP_3[EP1 & BUP & NI, EP1 & BUP & NI, i] <- m_remain_3[EP1 & BUP & NI, i]
# BUPC
a_TDP_1[EP1 & BUPC & NI, EP1 & BUPC & NI, i] <- m_remain_1[EP1 & BUPC & NI, i]
a_TDP_2[EP1 & BUPC & NI, EP1 & BUPC & NI, i] <- m_remain_2[EP1 & BUPC & NI, i]
a_TDP_3[EP1 & BUPC & NI, EP1 & BUPC & NI, i] <- m_remain_3[EP1 & BUPC & NI, i]
# MET
a_TDP_1[EP1 & MET & NI, EP1 & MET & NI, i] <- m_remain_1[EP1 & MET & NI, i]
a_TDP_2[EP1 & MET & NI, EP1 & MET & NI, i] <- m_remain_2[EP1 & MET & NI, i]
a_TDP_3[EP1 & MET & NI, EP1 & MET & NI, i] <- m_remain_3[EP1 & MET & NI, i]
# METC
a_TDP_1[EP1 & METC & NI, EP1 & METC & NI, i] <- m_remain_1[EP1 & METC & NI, i]
a_TDP_2[EP1 & METC & NI, EP1 & METC & NI, i] <- m_remain_2[EP1 & METC & NI, i]
a_TDP_3[EP1 & METC & NI, EP1 & METC & NI, i] <- m_remain_3[EP1 & METC & NI, i]
# ABS
a_TDP_1[EP1 & ABS & NI, EP1 & ABS & NI, i] <- m_remain_1[EP1 & ABS & NI, i]
a_TDP_2[EP1 & ABS & NI, EP1 & ABS & NI, i] <- m_remain_2[EP1 & ABS & NI, i]
a_TDP_3[EP1 & ABS & NI, EP1 & ABS & NI, i] <- m_remain_3[EP1 & ABS & NI, i]
# REL
a_TDP_1[EP1 & REL & NI, EP1 & REL & NI, i] <- m_remain_1[EP1 & REL & NI, i]
a_TDP_2[EP1 & REL & NI, EP1 & REL & NI, i] <- m_remain_2[EP1 & REL & NI, i]
a_TDP_3[EP1 & REL & NI, EP1 & REL & NI, i] <- m_remain_3[EP1 & REL & NI, i]
# ODF
a_TDP_1[EP1 & ODF & NI, EP1 & ODF & NI, i] <- m_remain_1[EP1 & ODF & NI, i]
a_TDP_2[EP1 & ODF & NI, EP1 & ODF & NI, i] <- m_remain_2[EP1 & ODF & NI, i]
a_TDP_3[EP1 & ODF & NI, EP1 & ODF & NI, i] <- m_remain_3[EP1 & ODF & NI, i]
# Episode 2
# BUP
a_TDP_1[EP2 & BUP & NI, EP2 & BUP & NI, i] <- m_remain_1[EP2 & BUP & NI, i]
a_TDP_2[EP2 & BUP & NI, EP2 & BUP & NI, i] <- m_remain_2[EP2 & BUP & NI, i]
a_TDP_3[EP2 & BUP & NI, EP2 & BUP & NI, i] <- m_remain_3[EP2 & BUP & NI, i]
# BUPC
a_TDP_1[EP2 & BUPC & NI, EP2 & BUPC & NI, i] <- m_remain_1[EP2 & BUPC & NI, i]
a_TDP_2[EP2 & BUPC & NI, EP2 & BUPC & NI, i] <- m_remain_2[EP2 & BUPC & NI, i]
a_TDP_3[EP2 & BUPC & NI, EP2 & BUPC & NI, i] <- m_remain_3[EP2 & BUPC & NI, i]
# MET
a_TDP_1[EP2 & MET & NI, EP2 & MET & NI, i] <- m_remain_1[EP2 & MET & NI, i]
a_TDP_2[EP2 & MET & NI, EP2 & MET & NI, i] <- m_remain_2[EP2 & MET & NI, i]
a_TDP_3[EP2 & MET & NI, EP2 & MET & NI, i] <- m_remain_3[EP2 & MET & NI, i]
# METC
a_TDP_1[EP2 & METC & NI, EP2 & METC & NI, i] <- m_remain_1[EP2 & METC & NI, i]
a_TDP_2[EP2 & METC & NI, EP2 & METC & NI, i] <- m_remain_2[EP2 & METC & NI, i]
a_TDP_3[EP2 & METC & NI, EP2 & METC & NI, i] <- m_remain_3[EP2 & METC & NI, i]
# ABS
a_TDP_1[EP2 & ABS & NI, EP2 & ABS & NI, i] <- m_remain_1[EP2 & ABS & NI, i]
a_TDP_2[EP2 & ABS & NI, EP2 & ABS & NI, i] <- m_remain_2[EP2 & ABS & NI, i]
a_TDP_3[EP2 & ABS & NI, EP2 & ABS & NI, i] <- m_remain_3[EP2 & ABS & NI, i]
# REL
a_TDP_1[EP2 & REL & NI, EP2 & REL & NI, i] <- m_remain_1[EP2 & REL & NI, i]
a_TDP_2[EP2 & REL & NI, EP2 & REL & NI, i] <- m_remain_2[EP2 & REL & NI, i]
a_TDP_3[EP2 & REL & NI, EP2 & REL & NI, i] <- m_remain_3[EP2 & REL & NI, i]
# ODF
a_TDP_1[EP2 & ODF & NI, EP2 & ODF & NI, i] <- m_remain_1[EP2 & ODF & NI, i]
a_TDP_2[EP2 & ODF & NI, EP2 & ODF & NI, i] <- m_remain_2[EP2 & ODF & NI, i]
a_TDP_3[EP2 & ODF & NI, EP2 & ODF & NI, i] <- m_remain_3[EP2 & ODF & NI, i]
# Episode 3
# BUP
a_TDP_1[EP3 & BUP & NI, EP3 & BUP & NI, i] <- m_remain_1[EP3 & BUP & NI, i]
a_TDP_2[EP3 & BUP & NI, EP3 & BUP & NI, i] <- m_remain_2[EP3 & BUP & NI, i]
a_TDP_3[EP3 & BUP & NI, EP3 & BUP & NI, i] <- m_remain_3[EP3 & BUP & NI, i]
# BUPC
a_TDP_1[EP3 & BUPC & NI, EP3 & BUPC & NI, i] <- m_remain_1[EP3 & BUPC & NI, i]
a_TDP_2[EP3 & BUPC & NI, EP3 & BUPC & NI, i] <- m_remain_2[EP3 & BUPC & NI, i]
a_TDP_3[EP3 & BUPC & NI, EP3 & BUPC & NI, i] <- m_remain_3[EP3 & BUPC & NI, i]
# MET
a_TDP_1[EP3 & MET & NI, EP3 & MET & NI, i] <- m_remain_1[EP3 & MET & NI, i]
a_TDP_2[EP3 & MET & NI, EP3 & MET & NI, i] <- m_remain_2[EP3 & MET & NI, i]
a_TDP_3[EP3 & MET & NI, EP3 & MET & NI, i] <- m_remain_3[EP3 & MET & NI, i]
# METC
a_TDP_1[EP3 & METC & NI, EP3 & METC & NI, i] <- m_remain_1[EP3 & METC & NI, i]
a_TDP_2[EP3 & METC & NI, EP3 & METC & NI, i] <- m_remain_2[EP3 & METC & NI, i]
a_TDP_3[EP3 & METC & NI, EP3 & METC & NI, i] <- m_remain_3[EP3 & METC & NI, i]
# ABS
a_TDP_1[EP3 & ABS & NI, EP3 & ABS & NI, i] <- m_remain_1[EP3 & ABS & NI, i]
a_TDP_2[EP3 & ABS & NI, EP3 & ABS & NI, i] <- m_remain_2[EP3 & ABS & NI, i]
a_TDP_3[EP3 & ABS & NI, EP3 & ABS & NI, i] <- m_remain_3[EP3 & ABS & NI, i]
# REL
a_TDP_1[EP3 & REL & NI, EP3 & REL & NI, i] <- m_remain_1[EP3 & REL & NI, i]
a_TDP_2[EP3 & REL & NI, EP3 & REL & NI, i] <- m_remain_2[EP3 & REL & NI, i]
a_TDP_3[EP3 & REL & NI, EP3 & REL & NI, i] <- m_remain_3[EP3 & REL & NI, i]
# ODF
a_TDP_1[EP3 & ODF & NI, EP3 & ODF & NI, i] <- m_remain_1[EP3 & ODF & NI, i]
a_TDP_2[EP3 & ODF & NI, EP3 & ODF & NI, i] <- m_remain_2[EP3 & ODF & NI, i]
a_TDP_3[EP3 & ODF & NI, EP3 & ODF & NI, i] <- m_remain_3[EP3 & ODF & NI, i]
# Injection
# Episode 1
# BUP
a_TDP_1[EP1 & BUP & INJ, EP1 & BUP & INJ, i] <- m_remain_1[EP1 & BUP & INJ, i]
a_TDP_2[EP1 & BUP & INJ, EP1 & BUP & INJ, i] <- m_remain_2[EP1 & BUP & INJ, i]
a_TDP_3[EP1 & BUP & INJ, EP1 & BUP & INJ, i] <- m_remain_3[EP1 & BUP & INJ, i]
# BUPC
a_TDP_1[EP1 & BUPC & INJ, EP1 & BUPC & INJ, i] <- m_remain_1[EP1 & BUPC & INJ, i]
a_TDP_2[EP1 & BUPC & INJ, EP1 & BUPC & INJ, i] <- m_remain_2[EP1 & BUPC & INJ, i]
a_TDP_3[EP1 & BUPC & INJ, EP1 & BUPC & INJ, i] <- m_remain_3[EP1 & BUPC & INJ, i]
# MET
a_TDP_1[EP1 & MET & INJ, EP1 & MET & INJ, i] <- m_remain_1[EP1 & MET & INJ, i]
a_TDP_2[EP1 & MET & INJ, EP1 & MET & INJ, i] <- m_remain_2[EP1 & MET & INJ, i]
a_TDP_3[EP1 & MET & INJ, EP1 & MET & INJ, i] <- m_remain_3[EP1 & MET & INJ, i]
# METC
a_TDP_1[EP1 & METC & INJ, EP1 & METC & INJ, i] <- m_remain_1[EP1 & METC & INJ, i]
a_TDP_2[EP1 & METC & INJ, EP1 & METC & INJ, i] <- m_remain_2[EP1 & METC & INJ, i]
a_TDP_3[EP1 & METC & INJ, EP1 & METC & INJ, i] <- m_remain_3[EP1 & METC & INJ, i]
# ABS
a_TDP_1[EP1 & ABS & INJ, EP1 & ABS & INJ, i] <- m_remain_1[EP1 & ABS & INJ, i]
a_TDP_2[EP1 & ABS & INJ, EP1 & ABS & INJ, i] <- m_remain_2[EP1 & ABS & INJ, i]
a_TDP_3[EP1 & ABS & INJ, EP1 & ABS & INJ, i] <- m_remain_3[EP1 & ABS & INJ, i]
# REL
a_TDP_1[EP1 & REL & INJ, EP1 & REL & INJ, i] <- m_remain_1[EP1 & REL & INJ, i]
a_TDP_2[EP1 & REL & INJ, EP1 & REL & INJ, i] <- m_remain_2[EP1 & REL & INJ, i]
a_TDP_3[EP1 & REL & INJ, EP1 & REL & INJ, i] <- m_remain_3[EP1 & REL & INJ, i]
# ODF
a_TDP_1[EP1 & ODF & INJ, EP1 & ODF & INJ, i] <- m_remain_1[EP1 & ODF & INJ, i]
a_TDP_2[EP1 & ODF & INJ, EP1 & ODF & INJ, i] <- m_remain_2[EP1 & ODF & INJ, i]
a_TDP_3[EP1 & ODF & INJ, EP1 & ODF & INJ, i] <- m_remain_3[EP1 & ODF & INJ, i]
# Episode 2
# BUP
a_TDP_1[EP2 & BUP & INJ, EP2 & BUP & INJ, i] <- m_remain_1[EP2 & BUP & INJ, i]
a_TDP_2[EP2 & BUP & INJ, EP2 & BUP & INJ, i] <- m_remain_2[EP2 & BUP & INJ, i]
a_TDP_3[EP2 & BUP & INJ, EP2 & BUP & INJ, i] <- m_remain_3[EP2 & BUP & INJ, i]
# BUPC
a_TDP_1[EP2 & BUPC & INJ, EP2 & BUPC & INJ, i] <- m_remain_1[EP2 & BUPC & INJ, i]
a_TDP_2[EP2 & BUPC & INJ, EP2 & BUPC & INJ, i] <- m_remain_2[EP2 & BUPC & INJ, i]
a_TDP_3[EP2 & BUPC & INJ, EP2 & BUPC & INJ, i] <- m_remain_3[EP2 & BUPC & INJ, i]
# MET
a_TDP_1[EP2 & MET & INJ, EP2 & MET & INJ, i] <- m_remain_1[EP2 & MET & INJ, i]
a_TDP_2[EP2 & MET & INJ, EP2 & MET & INJ, i] <- m_remain_2[EP2 & MET & INJ, i]
a_TDP_3[EP2 & MET & INJ, EP2 & MET & INJ, i] <- m_remain_3[EP2 & MET & INJ, i]
# METC
a_TDP_1[EP2 & METC & INJ, EP2 & METC & INJ, i] <- m_remain_1[EP2 & METC & INJ, i]
a_TDP_2[EP2 & METC & INJ, EP2 & METC & INJ, i] <- m_remain_2[EP2 & METC & INJ, i]
a_TDP_3[EP2 & METC & INJ, EP2 & METC & INJ, i] <- m_remain_3[EP2 & METC & INJ, i]
# ABS
a_TDP_1[EP2 & ABS & INJ, EP2 & ABS & INJ, i] <- m_remain_1[EP2 & ABS & INJ, i]
a_TDP_2[EP2 & ABS & INJ, EP2 & ABS & INJ, i] <- m_remain_2[EP2 & ABS & INJ, i]
a_TDP_3[EP2 & ABS & INJ, EP2 & ABS & INJ, i] <- m_remain_3[EP2 & ABS & INJ, i]
# REL
a_TDP_1[EP2 & REL & INJ, EP2 & REL & INJ, i] <- m_remain_1[EP2 & REL & INJ, i]
a_TDP_2[EP2 & REL & INJ, EP2 & REL & INJ, i] <- m_remain_2[EP2 & REL & INJ, i]
a_TDP_3[EP2 & REL & INJ, EP2 & REL & INJ, i] <- m_remain_3[EP2 & REL & INJ, i]
# ODF
a_TDP_1[EP2 & ODF & INJ, EP2 & ODF & INJ, i] <- m_remain_1[EP2 & ODF & INJ, i]
a_TDP_2[EP2 & ODF & INJ, EP2 & ODF & INJ, i] <- m_remain_2[EP2 & ODF & INJ, i]
a_TDP_3[EP2 & ODF & INJ, EP2 & ODF & INJ, i] <- m_remain_3[EP2 & ODF & INJ, i]
# Episode 3
# BUP
a_TDP_1[EP3 & BUP & INJ, EP3 & BUP & INJ, i] <- m_remain_1[EP3 & BUP & INJ, i]
a_TDP_2[EP3 & BUP & INJ, EP3 & BUP & INJ, i] <- m_remain_2[EP3 & BUP & INJ, i]
a_TDP_3[EP3 & BUP & INJ, EP3 & BUP & INJ, i] <- m_remain_3[EP3 & BUP & INJ, i]
# BUPC
a_TDP_1[EP3 & BUPC & INJ, EP3 & BUPC & INJ, i] <- m_remain_1[EP3 & BUPC & INJ, i]
a_TDP_2[EP3 & BUPC & INJ, EP3 & BUPC & INJ, i] <- m_remain_2[EP3 & BUPC & INJ, i]
a_TDP_3[EP3 & BUPC & INJ, EP3 & BUPC & INJ, i] <- m_remain_3[EP3 & BUPC & INJ, i]
# MET
a_TDP_1[EP3 & MET & INJ, EP3 & MET & INJ, i] <- m_remain_1[EP3 & MET & INJ, i]
a_TDP_2[EP3 & MET & INJ, EP3 & MET & INJ, i] <- m_remain_2[EP3 & MET & INJ, i]
a_TDP_3[EP3 & MET & INJ, EP3 & MET & INJ, i] <- m_remain_3[EP3 & MET & INJ, i]
# METC
a_TDP_1[EP3 & METC & INJ, EP3 & METC & INJ, i] <- m_remain_1[EP3 & METC & INJ, i]
a_TDP_2[EP3 & METC & INJ, EP3 & METC & INJ, i] <- m_remain_2[EP3 & METC & INJ, i]
a_TDP_3[EP3 & METC & INJ, EP3 & METC & INJ, i] <- m_remain_3[EP3 & METC & INJ, i]
# ABS
a_TDP_1[EP3 & ABS & INJ, EP3 & ABS & INJ, i] <- m_remain_1[EP3 & ABS & INJ, i]
a_TDP_2[EP3 & ABS & INJ, EP3 & ABS & INJ, i] <- m_remain_2[EP3 & ABS & INJ, i]
a_TDP_3[EP3 & ABS & INJ, EP3 & ABS & INJ, i] <- m_remain_3[EP3 & ABS & INJ, i]
# REL
a_TDP_1[EP3 & REL & INJ, EP3 & REL & INJ, i] <- m_remain_1[EP3 & REL & INJ, i]
a_TDP_2[EP3 & REL & INJ, EP3 & REL & INJ, i] <- m_remain_2[EP3 & REL & INJ, i]
a_TDP_3[EP3 & REL & INJ, EP3 & REL & INJ, i] <- m_remain_3[EP3 & REL & INJ, i]
# ODF
a_TDP_1[EP3 & ODF & INJ, EP3 & ODF & INJ, i] <- m_remain_1[EP3 & ODF & INJ, i]
a_TDP_2[EP3 & ODF & INJ, EP3 & ODF & INJ, i] <- m_remain_2[EP3 & ODF & INJ, i]
a_TDP_3[EP3 & ODF & INJ, EP3 & ODF & INJ, i] <- m_remain_3[EP3 & ODF & INJ, i]
}
if(checks){
# State transitions pre-overdose
# First month (state-time)
write.csv(a_TDP_1[, , 1], "checks/state transitions/a_TDP_pre_OD_2018.csv")
write.csv(a_TDP_2[, , 1], "checks/state transitions/a_TDP_pre_OD_2019.csv")
write.csv(a_TDP_3[, , 1], "checks/state transitions/a_TDP_pre_OD_2020.csv")
}
# Modify array for non-overdose prob
for (i in 1){
a_TDP_1[, , i] <- a_TDP_1[, , i] * m_non_OD_first[, 1]
a_TDP_2[, , i] <- a_TDP_2[, , i] * m_non_OD_first[, 2]
a_TDP_3[, , i] <- a_TDP_3[, , i] * m_non_OD_first[, 3]
}
## All transitions 2+ months
for (i in 2:n_t){
#a_TDP[, , i] <- m_UP * m_leave[, i]
a_TDP_1[, , i] <- a_TDP_1[, , i] * m_non_OD[, 1]
a_TDP_2[, , i] <- a_TDP_2[, , i] * m_non_OD[, 2]
a_TDP_3[, , i] <- a_TDP_3[, , i] * m_non_OD[, 3]
}
# Add overdose probabilities
for (i in 1){
a_TDP_1[NI, ODN & NI, i] <- m_ODN_first[NI, 1]
a_TDP_2[NI, ODN & NI, i] <- m_ODN_first[NI, 2]
a_TDP_3[NI, ODN & NI, i] <- m_ODN_first[NI, 3]
a_TDP_1[INJ, ODN & INJ, i] <- m_ODN_first[INJ, 1]
a_TDP_2[INJ, ODN & INJ, i] <- m_ODN_first[INJ, 2]
a_TDP_3[INJ, ODN & INJ, i] <- m_ODN_first[INJ, 3]
a_TDP_1[NI, ODF & NI, i] <- m_ODF_first[NI, 1]
a_TDP_2[NI, ODF & NI, i] <- m_ODF_first[NI, 2]
a_TDP_3[NI, ODF & NI, i] <- m_ODF_first[NI, 3]
a_TDP_1[INJ, ODF & INJ, i] <- m_ODF_first[INJ, 1]
a_TDP_2[INJ, ODF & INJ, i] <- m_ODF_first[INJ, 2]
a_TDP_3[INJ, ODF & INJ, i] <- m_ODF_first[INJ, 3]
a_TDP_1[ODF, ODF, i] <- a_TDP_2[ODF, ODF, i] <- a_TDP_3[ODF, ODF, i] <- 1
}
## All transitions 2+ months
for (i in 2:n_t){
#a_TDP[, , i] <- m_UP * m_leave[, i]
a_TDP_1[NI, ODN & NI, i] <- m_ODN[NI, 1]
a_TDP_2[NI, ODN & NI, i] <- m_ODN[NI, 2]
a_TDP_3[NI, ODN & NI, i] <- m_ODN[NI, 3]
a_TDP_1[INJ, ODN & INJ, i] <- m_ODN[INJ, 1]
a_TDP_2[INJ, ODN & INJ, i] <- m_ODN[INJ, 2]
a_TDP_3[INJ, ODN & INJ, i] <- m_ODN[INJ, 3]
a_TDP_1[NI, ODF & NI, i] <- m_ODF[NI, 1]
a_TDP_2[NI, ODF & NI, i] <- m_ODF[NI, 2]
a_TDP_3[NI, ODF & NI, i] <- m_ODF[NI, 3]
a_TDP_1[INJ, ODF & INJ, i] <- m_ODF[INJ, 1]
a_TDP_2[INJ, ODF & INJ, i] <- m_ODF[INJ, 2]
a_TDP_3[INJ, ODF & INJ, i] <- m_ODF[INJ, 3]
a_TDP_1[ODF, ODF, i] <- a_TDP_2[ODF, ODF, i] <- a_TDP_3[ODF, ODF, i] <- 1
}
if(checks){
# State transitions post-overdose
# First month (state-time)
write.csv(a_TDP_1[, , 1], "checks/state transitions/a_TDP_post_OD_2018.csv")
write.csv(a_TDP_2[, , 1], "checks/state transitions/a_TDP_post_OD_2019.csv")
write.csv(a_TDP_3[, , 1], "checks/state transitions/a_TDP_post_OD_2020.csv")
}
#### Seroconversion ####
# Apply seroconversion probability to re-weight NEG -> POS for to-states each time period
# Probabilities applied equally across POS/NEG initially, re-weight by sero prob
# Non-injection
# BUP
# From NEG
a_TDP_1[NEG & NI, BUP & NI & NEG, ] <- a_TDP_1[NEG & NI, BUP & NI & NEG, ] * (1 - p_HIV_BUP_NI - p_HCV_BUP_NI)
a_TDP_2[NEG & NI, BUP & NI & NEG, ] <- a_TDP_2[NEG & NI, BUP & NI & NEG, ] * (1 - p_HIV_BUP_NI - p_HCV_BUP_NI)
a_TDP_3[NEG & NI, BUP & NI & NEG, ] <- a_TDP_3[NEG & NI, BUP & NI & NEG, ] * (1 - p_HIV_BUP_NI - p_HCV_BUP_NI)
a_TDP_1[NEG & NI, BUP & NI & HIV, ] <- a_TDP_1[NEG & NI, BUP & NI & HIV, ] * p_HIV_BUP_NI
a_TDP_2[NEG & NI, BUP & NI & HIV, ] <- a_TDP_2[NEG & NI, BUP & NI & HIV, ] * p_HIV_BUP_NI
a_TDP_3[NEG & NI, BUP & NI & HIV, ] <- a_TDP_3[NEG & NI, BUP & NI & HIV, ] * p_HIV_BUP_NI
a_TDP_1[NEG & NI, BUP & NI & HCV, ] <- a_TDP_1[NEG & NI, BUP & NI & HCV, ] * p_HCV_BUP_NI
a_TDP_2[NEG & NI, BUP & NI & HCV, ] <- a_TDP_2[NEG & NI, BUP & NI & HCV, ] * p_HCV_BUP_NI
a_TDP_3[NEG & NI, BUP & NI & HCV, ] <- a_TDP_3[NEG & NI, BUP & NI & HCV, ] * p_HCV_BUP_NI
# From HIV
a_TDP_1[HIV & NI, BUP & NI & HIV, ] <- a_TDP_1[HIV & NI, BUP & NI & HIV, ] * (1 - p_HIV_HCV_BUP_NI)
a_TDP_2[HIV & NI, BUP & NI & HIV, ] <- a_TDP_2[HIV & NI, BUP & NI & HIV, ] * (1 - p_HIV_HCV_BUP_NI)
a_TDP_3[HIV & NI, BUP & NI & HIV, ] <- a_TDP_3[HIV & NI, BUP & NI & HIV, ] * (1 - p_HIV_HCV_BUP_NI)
a_TDP_1[HIV & NI, BUP & NI & COI, ] <- a_TDP_1[HIV & NI, BUP & NI & COI, ] * p_HIV_HCV_BUP_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, BUP & NI & COI, ] <- a_TDP_2[HIV & NI, BUP & NI & COI, ] * p_HIV_HCV_BUP_NI
a_TDP_3[HIV & NI, BUP & NI & COI, ] <- a_TDP_3[HIV & NI, BUP & NI & COI, ] * p_HIV_HCV_BUP_NI
# From HCV
a_TDP_1[HCV & NI, BUP & NI & HCV, ] <- a_TDP_1[HCV & NI, BUP & NI & HCV, ] * (1 - p_HCV_HIV_BUP_NI)
a_TDP_2[HCV & NI, BUP & NI & HCV, ] <- a_TDP_2[HCV & NI, BUP & NI & HCV, ] * (1 - p_HCV_HIV_BUP_NI)
a_TDP_3[HCV & NI, BUP & NI & HCV, ] <- a_TDP_3[HCV & NI, BUP & NI & HCV, ] * (1 - p_HCV_HIV_BUP_NI)
a_TDP_1[HCV & NI, BUP & NI & COI, ] <- a_TDP_1[HCV & NI, BUP & NI & COI, ] * p_HCV_HIV_BUP_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, BUP & NI & COI, ] <- a_TDP_2[HCV & NI, BUP & NI & COI, ] * p_HCV_HIV_BUP_NI
a_TDP_3[HCV & NI, BUP & NI & COI, ] <- a_TDP_3[HCV & NI, BUP & NI & COI, ] * p_HCV_HIV_BUP_NI
# BUPC
# From NEG
a_TDP_1[NEG & NI, BUPC & NI & NEG, ] <- a_TDP_1[NEG & NI, BUPC & NI & NEG, ] * (1 - p_HIV_BUPC_NI - p_HCV_BUPC_NI)
a_TDP_2[NEG & NI, BUPC & NI & NEG, ] <- a_TDP_2[NEG & NI, BUPC & NI & NEG, ] * (1 - p_HIV_BUPC_NI - p_HCV_BUPC_NI)
a_TDP_3[NEG & NI, BUPC & NI & NEG, ] <- a_TDP_3[NEG & NI, BUPC & NI & NEG, ] * (1 - p_HIV_BUPC_NI - p_HCV_BUPC_NI)
a_TDP_1[NEG & NI, BUPC & NI & HIV, ] <- a_TDP_1[NEG & NI, BUPC & NI & HIV, ] * p_HIV_BUPC_NI
a_TDP_2[NEG & NI, BUPC & NI & HIV, ] <- a_TDP_2[NEG & NI, BUPC & NI & HIV, ] * p_HIV_BUPC_NI
a_TDP_3[NEG & NI, BUPC & NI & HIV, ] <- a_TDP_3[NEG & NI, BUPC & NI & HIV, ] * p_HIV_BUPC_NI
a_TDP_1[NEG & NI, BUPC & NI & HCV, ] <- a_TDP_1[NEG & NI, BUPC & NI & HCV, ] * p_HCV_BUPC_NI
a_TDP_2[NEG & NI, BUPC & NI & HCV, ] <- a_TDP_2[NEG & NI, BUPC & NI & HCV, ] * p_HCV_BUPC_NI
a_TDP_3[NEG & NI, BUPC & NI & HCV, ] <- a_TDP_3[NEG & NI, BUPC & NI & HCV, ] * p_HCV_BUPC_NI
# From HIV
a_TDP_1[HIV & NI, BUPC & NI & HIV, ] <- a_TDP_1[HIV & NI, BUPC & NI & HIV, ] * (1 - p_HIV_HCV_BUPC_NI)
a_TDP_2[HIV & NI, BUPC & NI & HIV, ] <- a_TDP_2[HIV & NI, BUPC & NI & HIV, ] * (1 - p_HIV_HCV_BUPC_NI)
a_TDP_3[HIV & NI, BUPC & NI & HIV, ] <- a_TDP_3[HIV & NI, BUPC & NI & HIV, ] * (1 - p_HIV_HCV_BUPC_NI)
a_TDP_1[HIV & NI, BUPC & NI & COI, ] <- a_TDP_1[HIV & NI, BUPC & NI & COI, ] * p_HIV_HCV_BUPC_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, BUPC & NI & COI, ] <- a_TDP_2[HIV & NI, BUPC & NI & COI, ] * p_HIV_HCV_BUPC_NI
a_TDP_3[HIV & NI, BUPC & NI & COI, ] <- a_TDP_3[HIV & NI, BUPC & NI & COI, ] * p_HIV_HCV_BUPC_NI
# From HCV
a_TDP_1[HCV & NI, BUPC & NI & HCV, ] <- a_TDP_1[HCV & NI, BUPC & NI & HCV, ] * (1 - p_HCV_HIV_BUPC_NI)
a_TDP_2[HCV & NI, BUPC & NI & HCV, ] <- a_TDP_2[HCV & NI, BUPC & NI & HCV, ] * (1 - p_HCV_HIV_BUPC_NI)
a_TDP_3[HCV & NI, BUPC & NI & HCV, ] <- a_TDP_3[HCV & NI, BUPC & NI & HCV, ] * (1 - p_HCV_HIV_BUPC_NI)
a_TDP_1[HCV & NI, BUPC & NI & COI, ] <- a_TDP_1[HCV & NI, BUPC & NI & COI, ] * p_HCV_HIV_BUPC_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, BUPC & NI & COI, ] <- a_TDP_2[HCV & NI, BUPC & NI & COI, ] * p_HCV_HIV_BUPC_NI
a_TDP_3[HCV & NI, BUPC & NI & COI, ] <- a_TDP_3[HCV & NI, BUPC & NI & COI, ] * p_HCV_HIV_BUPC_NI
# MET
# From NEG
a_TDP_1[NEG & NI, MET & NI & NEG, ] <- a_TDP_1[NEG & NI, MET & NI & NEG, ] * (1 - p_HIV_MET_NI - p_HCV_MET_NI)
a_TDP_2[NEG & NI, MET & NI & NEG, ] <- a_TDP_2[NEG & NI, MET & NI & NEG, ] * (1 - p_HIV_MET_NI - p_HCV_MET_NI)
a_TDP_3[NEG & NI, MET & NI & NEG, ] <- a_TDP_3[NEG & NI, MET & NI & NEG, ] * (1 - p_HIV_MET_NI - p_HCV_MET_NI)
a_TDP_1[NEG & NI, MET & NI & HIV, ] <- a_TDP_1[NEG & NI, MET & NI & HIV, ] * p_HIV_MET_NI
a_TDP_2[NEG & NI, MET & NI & HIV, ] <- a_TDP_2[NEG & NI, MET & NI & HIV, ] * p_HIV_MET_NI
a_TDP_3[NEG & NI, MET & NI & HIV, ] <- a_TDP_3[NEG & NI, MET & NI & HIV, ] * p_HIV_MET_NI
a_TDP_1[NEG & NI, MET & NI & HCV, ] <- a_TDP_1[NEG & NI, MET & NI & HCV, ] * p_HCV_MET_NI
a_TDP_2[NEG & NI, MET & NI & HCV, ] <- a_TDP_2[NEG & NI, MET & NI & HCV, ] * p_HCV_MET_NI
a_TDP_3[NEG & NI, MET & NI & HCV, ] <- a_TDP_3[NEG & NI, MET & NI & HCV, ] * p_HCV_MET_NI
# From HIV
a_TDP_1[HIV & NI, MET & NI & HIV, ] <- a_TDP_1[HIV & NI, MET & NI & HIV, ] * (1 - p_HIV_HCV_MET_NI)
a_TDP_2[HIV & NI, MET & NI & HIV, ] <- a_TDP_2[HIV & NI, MET & NI & HIV, ] * (1 - p_HIV_HCV_MET_NI)
a_TDP_3[HIV & NI, MET & NI & HIV, ] <- a_TDP_3[HIV & NI, MET & NI & HIV, ] * (1 - p_HIV_HCV_MET_NI)
a_TDP_1[HIV & NI, MET & NI & COI, ] <- a_TDP_1[HIV & NI, MET & NI & COI, ] * p_HIV_HCV_MET_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, MET & NI & COI, ] <- a_TDP_2[HIV & NI, MET & NI & COI, ] * p_HIV_HCV_MET_NI
a_TDP_3[HIV & NI, MET & NI & COI, ] <- a_TDP_3[HIV & NI, MET & NI & COI, ] * p_HIV_HCV_MET_NI
# From HCV
a_TDP_1[HCV & NI, MET & NI & HCV, ] <- a_TDP_1[HCV & NI, MET & NI & HCV, ] * (1 - p_HCV_HIV_MET_NI)
a_TDP_2[HCV & NI, MET & NI & HCV, ] <- a_TDP_2[HCV & NI, MET & NI & HCV, ] * (1 - p_HCV_HIV_MET_NI)
a_TDP_3[HCV & NI, MET & NI & HCV, ] <- a_TDP_3[HCV & NI, MET & NI & HCV, ] * (1 - p_HCV_HIV_MET_NI)
a_TDP_1[HCV & NI, MET & NI & COI, ] <- a_TDP_1[HCV & NI, MET & NI & COI, ] * p_HCV_HIV_MET_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, MET & NI & COI, ] <- a_TDP_2[HCV & NI, MET & NI & COI, ] * p_HCV_HIV_MET_NI
a_TDP_3[HCV & NI, MET & NI & COI, ] <- a_TDP_3[HCV & NI, MET & NI & COI, ] * p_HCV_HIV_MET_NI
# METC
# From NEG
a_TDP_1[NEG & NI, METC & NI & NEG, ] <- a_TDP_1[NEG & NI, METC & NI & NEG, ] * (1 - p_HIV_METC_NI - p_HCV_METC_NI)
a_TDP_2[NEG & NI, METC & NI & NEG, ] <- a_TDP_2[NEG & NI, METC & NI & NEG, ] * (1 - p_HIV_METC_NI - p_HCV_METC_NI)
a_TDP_3[NEG & NI, METC & NI & NEG, ] <- a_TDP_3[NEG & NI, METC & NI & NEG, ] * (1 - p_HIV_METC_NI - p_HCV_METC_NI)
a_TDP_1[NEG & NI, METC & NI & HIV, ] <- a_TDP_1[NEG & NI, METC & NI & HIV, ] * p_HIV_METC_NI
a_TDP_2[NEG & NI, METC & NI & HIV, ] <- a_TDP_2[NEG & NI, METC & NI & HIV, ] * p_HIV_METC_NI
a_TDP_3[NEG & NI, METC & NI & HIV, ] <- a_TDP_3[NEG & NI, METC & NI & HIV, ] * p_HIV_METC_NI
a_TDP_1[NEG & NI, METC & NI & HCV, ] <- a_TDP_1[NEG & NI, METC & NI & HCV, ] * p_HCV_METC_NI
a_TDP_2[NEG & NI, METC & NI & HCV, ] <- a_TDP_2[NEG & NI, METC & NI & HCV, ] * p_HCV_METC_NI
a_TDP_3[NEG & NI, METC & NI & HCV, ] <- a_TDP_3[NEG & NI, METC & NI & HCV, ] * p_HCV_METC_NI
# From HIV
a_TDP_1[HIV & NI, METC & NI & HIV, ] <- a_TDP_1[HIV & NI, METC & NI & HIV, ] * (1 - p_HIV_HCV_METC_NI)
a_TDP_2[HIV & NI, METC & NI & HIV, ] <- a_TDP_2[HIV & NI, METC & NI & HIV, ] * (1 - p_HIV_HCV_METC_NI)
a_TDP_3[HIV & NI, METC & NI & HIV, ] <- a_TDP_3[HIV & NI, METC & NI & HIV, ] * (1 - p_HIV_HCV_METC_NI)
a_TDP_1[HIV & NI, METC & NI & COI, ] <- a_TDP_1[HIV & NI, METC & NI & COI, ] * p_HIV_HCV_METC_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, METC & NI & COI, ] <- a_TDP_2[HIV & NI, METC & NI & COI, ] * p_HIV_HCV_METC_NI
a_TDP_3[HIV & NI, METC & NI & COI, ] <- a_TDP_3[HIV & NI, METC & NI & COI, ] * p_HIV_HCV_METC_NI
# From HCV
a_TDP_1[HCV & NI, METC & NI & HCV, ] <- a_TDP_1[HCV & NI, METC & NI & HCV, ] * (1 - p_HCV_HIV_METC_NI)
a_TDP_2[HCV & NI, METC & NI & HCV, ] <- a_TDP_2[HCV & NI, METC & NI & HCV, ] * (1 - p_HCV_HIV_METC_NI)
a_TDP_3[HCV & NI, METC & NI & HCV, ] <- a_TDP_3[HCV & NI, METC & NI & HCV, ] * (1 - p_HCV_HIV_METC_NI)
a_TDP_1[HCV & NI, METC & NI & COI, ] <- a_TDP_1[HCV & NI, METC & NI & COI, ] * p_HCV_HIV_METC_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, METC & NI & COI, ] <- a_TDP_2[HCV & NI, METC & NI & COI, ] * p_HCV_HIV_METC_NI
a_TDP_3[HCV & NI, METC & NI & COI, ] <- a_TDP_3[HCV & NI, METC & NI & COI, ] * p_HCV_HIV_METC_NI
# REL
# From NEG
a_TDP_1[NEG & NI, REL & NI & NEG, ] <- a_TDP_1[NEG & NI, REL & NI & NEG, ] * (1 - p_HIV_REL_NI - p_HCV_REL_NI)
a_TDP_2[NEG & NI, REL & NI & NEG, ] <- a_TDP_2[NEG & NI, REL & NI & NEG, ] * (1 - p_HIV_REL_NI - p_HCV_REL_NI)
a_TDP_3[NEG & NI, REL & NI & NEG, ] <- a_TDP_3[NEG & NI, REL & NI & NEG, ] * (1 - p_HIV_REL_NI - p_HCV_REL_NI)
a_TDP_1[NEG & NI, REL & NI & HIV, ] <- a_TDP_1[NEG & NI, REL & NI & HIV, ] * p_HIV_REL_NI
a_TDP_2[NEG & NI, REL & NI & HIV, ] <- a_TDP_2[NEG & NI, REL & NI & HIV, ] * p_HIV_REL_NI
a_TDP_3[NEG & NI, REL & NI & HIV, ] <- a_TDP_3[NEG & NI, REL & NI & HIV, ] * p_HIV_REL_NI
a_TDP_1[NEG & NI, REL & NI & HCV, ] <- a_TDP_1[NEG & NI, REL & NI & HCV, ] * p_HCV_REL_NI
a_TDP_2[NEG & NI, REL & NI & HCV, ] <- a_TDP_2[NEG & NI, REL & NI & HCV, ] * p_HCV_REL_NI
a_TDP_3[NEG & NI, REL & NI & HCV, ] <- a_TDP_3[NEG & NI, REL & NI & HCV, ] * p_HCV_REL_NI
# From HIV
a_TDP_1[HIV & NI, REL & NI & HIV, ] <- a_TDP_1[HIV & NI, REL & NI & HIV, ] * (1 - p_HIV_HCV_REL_NI)
a_TDP_2[HIV & NI, REL & NI & HIV, ] <- a_TDP_2[HIV & NI, REL & NI & HIV, ] * (1 - p_HIV_HCV_REL_NI)
a_TDP_3[HIV & NI, REL & NI & HIV, ] <- a_TDP_3[HIV & NI, REL & NI & HIV, ] * (1 - p_HIV_HCV_REL_NI)
a_TDP_1[HIV & NI, REL & NI & COI, ] <- a_TDP_1[HIV & NI, REL & NI & COI, ] * p_HIV_HCV_REL_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, REL & NI & COI, ] <- a_TDP_2[HIV & NI, REL & NI & COI, ] * p_HIV_HCV_REL_NI
a_TDP_3[HIV & NI, REL & NI & COI, ] <- a_TDP_3[HIV & NI, REL & NI & COI, ] * p_HIV_HCV_REL_NI
# From HCV
a_TDP_1[HCV & NI, REL & NI & HCV, ] <- a_TDP_1[HCV & NI, REL & NI & HCV, ] * (1 - p_HCV_HIV_REL_NI)
a_TDP_2[HCV & NI, REL & NI & HCV, ] <- a_TDP_2[HCV & NI, REL & NI & HCV, ] * (1 - p_HCV_HIV_REL_NI)
a_TDP_3[HCV & NI, REL & NI & HCV, ] <- a_TDP_3[HCV & NI, REL & NI & HCV, ] * (1 - p_HCV_HIV_REL_NI)
a_TDP_1[HCV & NI, REL & NI & COI, ] <- a_TDP_1[HCV & NI, REL & NI & COI, ] * p_HCV_HIV_REL_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, REL & NI & COI, ] <- a_TDP_2[HCV & NI, REL & NI & COI, ] * p_HCV_HIV_REL_NI
a_TDP_3[HCV & NI, REL & NI & COI, ] <- a_TDP_3[HCV & NI, REL & NI & COI, ] * p_HCV_HIV_REL_NI
# ODN
# From NEG
a_TDP_1[NEG & NI, ODN & NI & NEG, ] <- a_TDP_1[NEG & NI, ODN & NI & NEG, ] * (1 - p_HIV_ODN_NI - p_HCV_ODN_NI)
a_TDP_2[NEG & NI, ODN & NI & NEG, ] <- a_TDP_2[NEG & NI, ODN & NI & NEG, ] * (1 - p_HIV_ODN_NI - p_HCV_ODN_NI)
a_TDP_3[NEG & NI, ODN & NI & NEG, ] <- a_TDP_3[NEG & NI, ODN & NI & NEG, ] * (1 - p_HIV_ODN_NI - p_HCV_ODN_NI)
a_TDP_1[NEG & NI, ODN & NI & HIV, ] <- a_TDP_1[NEG & NI, ODN & NI & HIV, ] * p_HIV_ODN_NI
a_TDP_2[NEG & NI, ODN & NI & HIV, ] <- a_TDP_2[NEG & NI, ODN & NI & HIV, ] * p_HIV_ODN_NI
a_TDP_3[NEG & NI, ODN & NI & HIV, ] <- a_TDP_3[NEG & NI, ODN & NI & HIV, ] * p_HIV_ODN_NI
a_TDP_1[NEG & NI, ODN & NI & HCV, ] <- a_TDP_1[NEG & NI, ODN & NI & HCV, ] * p_HCV_ODN_NI
a_TDP_2[NEG & NI, ODN & NI & HCV, ] <- a_TDP_2[NEG & NI, ODN & NI & HCV, ] * p_HCV_ODN_NI
a_TDP_3[NEG & NI, ODN & NI & HCV, ] <- a_TDP_3[NEG & NI, ODN & NI & HCV, ] * p_HCV_ODN_NI
# From HIV
a_TDP_1[HIV & NI, ODN & NI & HIV, ] <- a_TDP_1[HIV & NI, ODN & NI & HIV, ] * (1 - p_HIV_HCV_ODN_NI)
a_TDP_2[HIV & NI, ODN & NI & HIV, ] <- a_TDP_2[HIV & NI, ODN & NI & HIV, ] * (1 - p_HIV_HCV_ODN_NI)
a_TDP_3[HIV & NI, ODN & NI & HIV, ] <- a_TDP_3[HIV & NI, ODN & NI & HIV, ] * (1 - p_HIV_HCV_ODN_NI)
a_TDP_1[HIV & NI, ODN & NI & COI, ] <- a_TDP_1[HIV & NI, ODN & NI & COI, ] * p_HIV_HCV_ODN_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, ODN & NI & COI, ] <- a_TDP_2[HIV & NI, ODN & NI & COI, ] * p_HIV_HCV_ODN_NI
a_TDP_3[HIV & NI, ODN & NI & COI, ] <- a_TDP_3[HIV & NI, ODN & NI & COI, ] * p_HIV_HCV_ODN_NI
# From HCV
a_TDP_1[HCV & NI, ODN & NI & HCV, ] <- a_TDP_1[HCV & NI, ODN & NI & HCV, ] * (1 - p_HCV_HIV_ODN_NI)
a_TDP_2[HCV & NI, ODN & NI & HCV, ] <- a_TDP_2[HCV & NI, ODN & NI & HCV, ] * (1 - p_HCV_HIV_ODN_NI)
a_TDP_3[HCV & NI, ODN & NI & HCV, ] <- a_TDP_3[HCV & NI, ODN & NI & HCV, ] * (1 - p_HCV_HIV_ODN_NI)
a_TDP_1[HCV & NI, ODN & NI & COI, ] <- a_TDP_1[HCV & NI, ODN & NI & COI, ] * p_HCV_HIV_ODN_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, ODN & NI & COI, ] <- a_TDP_2[HCV & NI, ODN & NI & COI, ] * p_HCV_HIV_ODN_NI
a_TDP_3[HCV & NI, ODN & NI & COI, ] <- a_TDP_3[HCV & NI, ODN & NI & COI, ] * p_HCV_HIV_ODN_NI
# ODF
# From NEG
a_TDP_1[NEG & NI, ODF & NI & NEG, ] <- a_TDP_1[NEG & NI, ODF & NI & NEG, ] * 1
a_TDP_2[NEG & NI, ODF & NI & NEG, ] <- a_TDP_2[NEG & NI, ODF & NI & NEG, ] * 1
a_TDP_3[NEG & NI, ODF & NI & NEG, ] <- a_TDP_3[NEG & NI, ODF & NI & NEG, ] * 1
a_TDP_1[NEG & NI, ODF & NI & HIV, ] <- a_TDP_1[NEG & NI, ODF & NI & HIV, ] * 0
a_TDP_2[NEG & NI, ODF & NI & HIV, ] <- a_TDP_2[NEG & NI, ODF & NI & HIV, ] * 0
a_TDP_3[NEG & NI, ODF & NI & HIV, ] <- a_TDP_3[NEG & NI, ODF & NI & HIV, ] * 0
a_TDP_1[NEG & NI, ODF & NI & HCV, ] <- a_TDP_1[NEG & NI, ODF & NI & HCV, ] * 0
a_TDP_2[NEG & NI, ODF & NI & HCV, ] <- a_TDP_2[NEG & NI, ODF & NI & HCV, ] * 0
a_TDP_3[NEG & NI, ODF & NI & HCV, ] <- a_TDP_3[NEG & NI, ODF & NI & HCV, ] * 0
# From HIV
a_TDP_1[HIV & NI, ODF & NI & HIV, ] <- a_TDP_1[HIV & NI, ODF & NI & HIV, ] * 1
a_TDP_2[HIV & NI, ODF & NI & HIV, ] <- a_TDP_2[HIV & NI, ODF & NI & HIV, ] * 1
a_TDP_3[HIV & NI, ODF & NI & HIV, ] <- a_TDP_3[HIV & NI, ODF & NI & HIV, ] * 1
a_TDP_1[HIV & NI, ODF & NI & COI, ] <- a_TDP_1[HIV & NI, ODF & NI & COI, ] * 0
a_TDP_2[HIV & NI, ODF & NI & COI, ] <- a_TDP_2[HIV & NI, ODF & NI & COI, ] * 0
a_TDP_3[HIV & NI, ODF & NI & COI, ] <- a_TDP_3[HIV & NI, ODF & NI & COI, ] * 0
# From HCV
a_TDP_1[HCV & NI, ODF & NI & HCV, ] <- a_TDP_1[HCV & NI, ODF & NI & HCV, ] * 1
a_TDP_2[HCV & NI, ODF & NI & HCV, ] <- a_TDP_2[HCV & NI, ODF & NI & HCV, ] * 1
a_TDP_3[HCV & NI, ODF & NI & HCV, ] <- a_TDP_3[HCV & NI, ODF & NI & HCV, ] * 1
a_TDP_1[HCV & NI, ODF & NI & COI, ] <- a_TDP_1[HCV & NI, ODF & NI & COI, ] * 0
a_TDP_2[HCV & NI, ODF & NI & COI, ] <- a_TDP_2[HCV & NI, ODF & NI & COI, ] * 0
a_TDP_3[HCV & NI, ODF & NI & COI, ] <- a_TDP_3[HCV & NI, ODF & NI & COI, ] * 0
# ABS
# From NEG
a_TDP_1[NEG & NI, ABS & NI & NEG, ] <- a_TDP_1[NEG & NI, ABS & NI & NEG, ] * (1 - p_HIV_ABS_NI - p_HCV_ABS_NI)
a_TDP_2[NEG & NI, ABS & NI & NEG, ] <- a_TDP_2[NEG & NI, ABS & NI & NEG, ] * (1 - p_HIV_ABS_NI - p_HCV_ABS_NI)
a_TDP_3[NEG & NI, ABS & NI & NEG, ] <- a_TDP_3[NEG & NI, ABS & NI & NEG, ] * (1 - p_HIV_ABS_NI - p_HCV_ABS_NI)
a_TDP_1[NEG & NI, ABS & NI & HIV, ] <- a_TDP_1[NEG & NI, ABS & NI & HIV, ] * p_HIV_ABS_NI
a_TDP_2[NEG & NI, ABS & NI & HIV, ] <- a_TDP_2[NEG & NI, ABS & NI & HIV, ] * p_HIV_ABS_NI
a_TDP_3[NEG & NI, ABS & NI & HIV, ] <- a_TDP_3[NEG & NI, ABS & NI & HIV, ] * p_HIV_ABS_NI
a_TDP_1[NEG & NI, ABS & NI & HCV, ] <- a_TDP_1[NEG & NI, ABS & NI & HCV, ] * p_HCV_ABS_NI
a_TDP_2[NEG & NI, ABS & NI & HCV, ] <- a_TDP_2[NEG & NI, ABS & NI & HCV, ] * p_HCV_ABS_NI
a_TDP_3[NEG & NI, ABS & NI & HCV, ] <- a_TDP_3[NEG & NI, ABS & NI & HCV, ] * p_HCV_ABS_NI
# From HIV
a_TDP_1[HIV & NI, ABS & NI & HIV, ] <- a_TDP_1[HIV & NI, ABS & NI & HIV, ] * (1 - p_HIV_HCV_ABS_NI)
a_TDP_2[HIV & NI, ABS & NI & HIV, ] <- a_TDP_2[HIV & NI, ABS & NI & HIV, ] * (1 - p_HIV_HCV_ABS_NI)
a_TDP_3[HIV & NI, ABS & NI & HIV, ] <- a_TDP_3[HIV & NI, ABS & NI & HIV, ] * (1 - p_HIV_HCV_ABS_NI)
a_TDP_1[HIV & NI, ABS & NI & COI, ] <- a_TDP_1[HIV & NI, ABS & NI & COI, ] * p_HIV_HCV_ABS_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, ABS & NI & COI, ] <- a_TDP_2[HIV & NI, ABS & NI & COI, ] * p_HIV_HCV_ABS_NI
a_TDP_3[HIV & NI, ABS & NI & COI, ] <- a_TDP_3[HIV & NI, ABS & NI & COI, ] * p_HIV_HCV_ABS_NI
# From HCV
a_TDP_1[HCV & NI, ABS & NI & HCV, ] <- a_TDP_1[HCV & NI, ABS & NI & HCV, ] * (1 - p_HCV_HIV_ABS_NI)
a_TDP_2[HCV & NI, ABS & NI & HCV, ] <- a_TDP_2[HCV & NI, ABS & NI & HCV, ] * (1 - p_HCV_HIV_ABS_NI)
a_TDP_3[HCV & NI, ABS & NI & HCV, ] <- a_TDP_3[HCV & NI, ABS & NI & HCV, ] * (1 - p_HCV_HIV_ABS_NI)
a_TDP_1[HCV & NI, ABS & NI & COI, ] <- a_TDP_1[HCV & NI, ABS & NI & COI, ] * p_HCV_HIV_ABS_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, ABS & NI & COI, ] <- a_TDP_2[HCV & NI, ABS & NI & COI, ] * p_HCV_HIV_ABS_NI
a_TDP_3[HCV & NI, ABS & NI & COI, ] <- a_TDP_3[HCV & NI, ABS & NI & COI, ] * p_HCV_HIV_ABS_NI
# Injection
# BUP
# From NEG
a_TDP_1[NEG & INJ, BUP & INJ & NEG, ] <- a_TDP_1[NEG & INJ, BUP & INJ & NEG, ] * (1 - p_HIV_BUP_INJ - p_HCV_BUP_INJ)
a_TDP_2[NEG & INJ, BUP & INJ & NEG, ] <- a_TDP_2[NEG & INJ, BUP & INJ & NEG, ] * (1 - p_HIV_BUP_INJ - p_HCV_BUP_INJ)
a_TDP_3[NEG & INJ, BUP & INJ & NEG, ] <- a_TDP_3[NEG & INJ, BUP & INJ & NEG, ] * (1 - p_HIV_BUP_INJ - p_HCV_BUP_INJ)
a_TDP_1[NEG & INJ, BUP & INJ & HIV, ] <- a_TDP_1[NEG & INJ, BUP & INJ & HIV, ] * p_HIV_BUP_INJ
a_TDP_2[NEG & INJ, BUP & INJ & HIV, ] <- a_TDP_2[NEG & INJ, BUP & INJ & HIV, ] * p_HIV_BUP_INJ
a_TDP_3[NEG & INJ, BUP & INJ & HIV, ] <- a_TDP_3[NEG & INJ, BUP & INJ & HIV, ] * p_HIV_BUP_INJ
a_TDP_1[NEG & INJ, BUP & INJ & HCV, ] <- a_TDP_1[NEG & INJ, BUP & INJ & HCV, ] * p_HCV_BUP_INJ
a_TDP_2[NEG & INJ, BUP & INJ & HCV, ] <- a_TDP_2[NEG & INJ, BUP & INJ & HCV, ] * p_HCV_BUP_INJ
a_TDP_3[NEG & INJ, BUP & INJ & HCV, ] <- a_TDP_3[NEG & INJ, BUP & INJ & HCV, ] * p_HCV_BUP_INJ
# From HIV
a_TDP_1[HIV & INJ, BUP & INJ & HIV, ] <- a_TDP_1[HIV & INJ, BUP & INJ & HIV, ] * (1 - p_HIV_HCV_BUP_INJ)
a_TDP_2[HIV & INJ, BUP & INJ & HIV, ] <- a_TDP_2[HIV & INJ, BUP & INJ & HIV, ] * (1 - p_HIV_HCV_BUP_INJ)
a_TDP_3[HIV & INJ, BUP & INJ & HIV, ] <- a_TDP_3[HIV & INJ, BUP & INJ & HIV, ] * (1 - p_HIV_HCV_BUP_INJ)
a_TDP_1[HIV & INJ, BUP & INJ & COI, ] <- a_TDP_1[HIV & INJ, BUP & INJ & COI, ] * p_HIV_HCV_BUP_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, BUP & INJ & COI, ] <- a_TDP_2[HIV & INJ, BUP & INJ & COI, ] * p_HIV_HCV_BUP_INJ
a_TDP_3[HIV & INJ, BUP & INJ & COI, ] <- a_TDP_3[HIV & INJ, BUP & INJ & COI, ] * p_HIV_HCV_BUP_INJ
# From HCV
a_TDP_1[HCV & INJ, BUP & INJ & HCV, ] <- a_TDP_1[HCV & INJ, BUP & INJ & HCV, ] * (1 - p_HCV_HIV_BUP_INJ)
a_TDP_2[HCV & INJ, BUP & INJ & HCV, ] <- a_TDP_2[HCV & INJ, BUP & INJ & HCV, ] * (1 - p_HCV_HIV_BUP_INJ)
a_TDP_3[HCV & INJ, BUP & INJ & HCV, ] <- a_TDP_3[HCV & INJ, BUP & INJ & HCV, ] * (1 - p_HCV_HIV_BUP_INJ)
a_TDP_1[HCV & INJ, BUP & INJ & COI, ] <- a_TDP_1[HCV & INJ, BUP & INJ & COI, ] * p_HCV_HIV_BUP_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, BUP & INJ & COI, ] <- a_TDP_2[HCV & INJ, BUP & INJ & COI, ] * p_HCV_HIV_BUP_INJ
a_TDP_3[HCV & INJ, BUP & INJ & COI, ] <- a_TDP_3[HCV & INJ, BUP & INJ & COI, ] * p_HCV_HIV_BUP_INJ
# BUPC
# From NEG
a_TDP_1[NEG & INJ, BUPC & INJ & NEG, ] <- a_TDP_1[NEG & INJ, BUPC & INJ & NEG, ] * (1 - p_HIV_BUPC_INJ - p_HCV_BUPC_INJ)
a_TDP_2[NEG & INJ, BUPC & INJ & NEG, ] <- a_TDP_2[NEG & INJ, BUPC & INJ & NEG, ] * (1 - p_HIV_BUPC_INJ - p_HCV_BUPC_INJ)
a_TDP_3[NEG & INJ, BUPC & INJ & NEG, ] <- a_TDP_3[NEG & INJ, BUPC & INJ & NEG, ] * (1 - p_HIV_BUPC_INJ - p_HCV_BUPC_INJ)
a_TDP_1[NEG & INJ, BUPC & INJ & HIV, ] <- a_TDP_1[NEG & INJ, BUPC & INJ & HIV, ] * p_HIV_BUPC_INJ
a_TDP_2[NEG & INJ, BUPC & INJ & HIV, ] <- a_TDP_2[NEG & INJ, BUPC & INJ & HIV, ] * p_HIV_BUPC_INJ
a_TDP_3[NEG & INJ, BUPC & INJ & HIV, ] <- a_TDP_3[NEG & INJ, BUPC & INJ & HIV, ] * p_HIV_BUPC_INJ
a_TDP_1[NEG & INJ, BUPC & INJ & HCV, ] <- a_TDP_1[NEG & INJ, BUPC & INJ & HCV, ] * p_HCV_BUPC_INJ
a_TDP_2[NEG & INJ, BUPC & INJ & HCV, ] <- a_TDP_2[NEG & INJ, BUPC & INJ & HCV, ] * p_HCV_BUPC_INJ
a_TDP_3[NEG & INJ, BUPC & INJ & HCV, ] <- a_TDP_3[NEG & INJ, BUPC & INJ & HCV, ] * p_HCV_BUPC_INJ
# From HIV
a_TDP_1[HIV & INJ, BUPC & INJ & HIV, ] <- a_TDP_1[HIV & INJ, BUPC & INJ & HIV, ] * (1 - p_HIV_HCV_BUPC_INJ)
a_TDP_2[HIV & INJ, BUPC & INJ & HIV, ] <- a_TDP_2[HIV & INJ, BUPC & INJ & HIV, ] * (1 - p_HIV_HCV_BUPC_INJ)
a_TDP_3[HIV & INJ, BUPC & INJ & HIV, ] <- a_TDP_3[HIV & INJ, BUPC & INJ & HIV, ] * (1 - p_HIV_HCV_BUPC_INJ)
a_TDP_1[HIV & INJ, BUPC & INJ & COI, ] <- a_TDP_1[HIV & INJ, BUPC & INJ & COI, ] * p_HIV_HCV_BUPC_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, BUPC & INJ & COI, ] <- a_TDP_2[HIV & INJ, BUPC & INJ & COI, ] * p_HIV_HCV_BUPC_INJ
a_TDP_3[HIV & INJ, BUPC & INJ & COI, ] <- a_TDP_3[HIV & INJ, BUPC & INJ & COI, ] * p_HIV_HCV_BUPC_INJ
# From HCV
a_TDP_1[HCV & INJ, BUPC & INJ & HCV, ] <- a_TDP_1[HCV & INJ, BUPC & INJ & HCV, ] * (1 - p_HCV_HIV_BUPC_INJ)
a_TDP_2[HCV & INJ, BUPC & INJ & HCV, ] <- a_TDP_2[HCV & INJ, BUPC & INJ & HCV, ] * (1 - p_HCV_HIV_BUPC_INJ)
a_TDP_3[HCV & INJ, BUPC & INJ & HCV, ] <- a_TDP_3[HCV & INJ, BUPC & INJ & HCV, ] * (1 - p_HCV_HIV_BUPC_INJ)
a_TDP_1[HCV & INJ, BUPC & INJ & COI, ] <- a_TDP_1[HCV & INJ, BUPC & INJ & COI, ] * p_HCV_HIV_BUPC_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, BUPC & INJ & COI, ] <- a_TDP_2[HCV & INJ, BUPC & INJ & COI, ] * p_HCV_HIV_BUPC_INJ
a_TDP_3[HCV & INJ, BUPC & INJ & COI, ] <- a_TDP_3[HCV & INJ, BUPC & INJ & COI, ] * p_HCV_HIV_BUPC_INJ
# MET
# From NEG
a_TDP_1[NEG & INJ, MET & INJ & NEG, ] <- a_TDP_1[NEG & INJ, MET & INJ & NEG, ] * (1 - p_HIV_MET_INJ - p_HCV_MET_INJ)
a_TDP_2[NEG & INJ, MET & INJ & NEG, ] <- a_TDP_2[NEG & INJ, MET & INJ & NEG, ] * (1 - p_HIV_MET_INJ - p_HCV_MET_INJ)
a_TDP_3[NEG & INJ, MET & INJ & NEG, ] <- a_TDP_3[NEG & INJ, MET & INJ & NEG, ] * (1 - p_HIV_MET_INJ - p_HCV_MET_INJ)
a_TDP_1[NEG & INJ, MET & INJ & HIV, ] <- a_TDP_1[NEG & INJ, MET & INJ & HIV, ] * p_HIV_MET_INJ
a_TDP_2[NEG & INJ, MET & INJ & HIV, ] <- a_TDP_2[NEG & INJ, MET & INJ & HIV, ] * p_HIV_MET_INJ
a_TDP_3[NEG & INJ, MET & INJ & HIV, ] <- a_TDP_3[NEG & INJ, MET & INJ & HIV, ] * p_HIV_MET_INJ
a_TDP_1[NEG & INJ, MET & INJ & HCV, ] <- a_TDP_1[NEG & INJ, MET & INJ & HCV, ] * p_HCV_MET_INJ
a_TDP_2[NEG & INJ, MET & INJ & HCV, ] <- a_TDP_2[NEG & INJ, MET & INJ & HCV, ] * p_HCV_MET_INJ
a_TDP_3[NEG & INJ, MET & INJ & HCV, ] <- a_TDP_3[NEG & INJ, MET & INJ & HCV, ] * p_HCV_MET_INJ
# From HIV
a_TDP_1[HIV & INJ, MET & INJ & HIV, ] <- a_TDP_1[HIV & INJ, MET & INJ & HIV, ] * (1 - p_HIV_HCV_MET_INJ)
a_TDP_2[HIV & INJ, MET & INJ & HIV, ] <- a_TDP_2[HIV & INJ, MET & INJ & HIV, ] * (1 - p_HIV_HCV_MET_INJ)
a_TDP_3[HIV & INJ, MET & INJ & HIV, ] <- a_TDP_3[HIV & INJ, MET & INJ & HIV, ] * (1 - p_HIV_HCV_MET_INJ)
a_TDP_1[HIV & INJ, MET & INJ & COI, ] <- a_TDP_1[HIV & INJ, MET & INJ & COI, ] * p_HIV_HCV_MET_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, MET & INJ & COI, ] <- a_TDP_2[HIV & INJ, MET & INJ & COI, ] * p_HIV_HCV_MET_INJ
a_TDP_3[HIV & INJ, MET & INJ & COI, ] <- a_TDP_3[HIV & INJ, MET & INJ & COI, ] * p_HIV_HCV_MET_INJ
# From HCV
a_TDP_1[HCV & INJ, MET & INJ & HCV, ] <- a_TDP_1[HCV & INJ, MET & INJ & HCV, ] * (1 - p_HCV_HIV_MET_INJ)
a_TDP_2[HCV & INJ, MET & INJ & HCV, ] <- a_TDP_2[HCV & INJ, MET & INJ & HCV, ] * (1 - p_HCV_HIV_MET_INJ)
a_TDP_3[HCV & INJ, MET & INJ & HCV, ] <- a_TDP_3[HCV & INJ, MET & INJ & HCV, ] * (1 - p_HCV_HIV_MET_INJ)
a_TDP_1[HCV & INJ, MET & INJ & COI, ] <- a_TDP_1[HCV & INJ, MET & INJ & COI, ] * p_HCV_HIV_MET_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, MET & INJ & COI, ] <- a_TDP_2[HCV & INJ, MET & INJ & COI, ] * p_HCV_HIV_MET_INJ
a_TDP_3[HCV & INJ, MET & INJ & COI, ] <- a_TDP_3[HCV & INJ, MET & INJ & COI, ] * p_HCV_HIV_MET_INJ
# METC
# From NEG
a_TDP_1[NEG & INJ, METC & INJ & NEG, ] <- a_TDP_1[NEG & INJ, METC & INJ & NEG, ] * (1 - p_HIV_METC_INJ - p_HCV_METC_INJ)
a_TDP_2[NEG & INJ, METC & INJ & NEG, ] <- a_TDP_2[NEG & INJ, METC & INJ & NEG, ] * (1 - p_HIV_METC_INJ - p_HCV_METC_INJ)
a_TDP_3[NEG & INJ, METC & INJ & NEG, ] <- a_TDP_3[NEG & INJ, METC & INJ & NEG, ] * (1 - p_HIV_METC_INJ - p_HCV_METC_INJ)
a_TDP_1[NEG & INJ, METC & INJ & HIV, ] <- a_TDP_1[NEG & INJ, METC & INJ & HIV, ] * p_HIV_METC_INJ
a_TDP_2[NEG & INJ, METC & INJ & HIV, ] <- a_TDP_2[NEG & INJ, METC & INJ & HIV, ] * p_HIV_METC_INJ
a_TDP_3[NEG & INJ, METC & INJ & HIV, ] <- a_TDP_3[NEG & INJ, METC & INJ & HIV, ] * p_HIV_METC_INJ
a_TDP_1[NEG & INJ, METC & INJ & HCV, ] <- a_TDP_1[NEG & INJ, METC & INJ & HCV, ] * p_HCV_METC_INJ
a_TDP_2[NEG & INJ, METC & INJ & HCV, ] <- a_TDP_2[NEG & INJ, METC & INJ & HCV, ] * p_HCV_METC_INJ
a_TDP_3[NEG & INJ, METC & INJ & HCV, ] <- a_TDP_3[NEG & INJ, METC & INJ & HCV, ] * p_HCV_METC_INJ
# From HIV
a_TDP_1[HIV & INJ, METC & INJ & HIV, ] <- a_TDP_1[HIV & INJ, METC & INJ & HIV, ] * (1 - p_HIV_HCV_METC_INJ)
a_TDP_2[HIV & INJ, METC & INJ & HIV, ] <- a_TDP_2[HIV & INJ, METC & INJ & HIV, ] * (1 - p_HIV_HCV_METC_INJ)
a_TDP_3[HIV & INJ, METC & INJ & HIV, ] <- a_TDP_3[HIV & INJ, METC & INJ & HIV, ] * (1 - p_HIV_HCV_METC_INJ)
a_TDP_1[HIV & INJ, METC & INJ & COI, ] <- a_TDP_1[HIV & INJ, METC & INJ & COI, ] * p_HIV_HCV_METC_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, METC & INJ & COI, ] <- a_TDP_2[HIV & INJ, METC & INJ & COI, ] * p_HIV_HCV_METC_INJ
a_TDP_3[HIV & INJ, METC & INJ & COI, ] <- a_TDP_3[HIV & INJ, METC & INJ & COI, ] * p_HIV_HCV_METC_INJ
# From HCV
a_TDP_1[HCV & INJ, METC & INJ & HCV, ] <- a_TDP_1[HCV & INJ, METC & INJ & HCV, ] * (1 - p_HCV_HIV_METC_INJ)
a_TDP_2[HCV & INJ, METC & INJ & HCV, ] <- a_TDP_2[HCV & INJ, METC & INJ & HCV, ] * (1 - p_HCV_HIV_METC_INJ)
a_TDP_3[HCV & INJ, METC & INJ & HCV, ] <- a_TDP_3[HCV & INJ, METC & INJ & HCV, ] * (1 - p_HCV_HIV_METC_INJ)
a_TDP_1[HCV & INJ, METC & INJ & COI, ] <- a_TDP_1[HCV & INJ, METC & INJ & COI, ] * p_HCV_HIV_METC_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, METC & INJ & COI, ] <- a_TDP_2[HCV & INJ, METC & INJ & COI, ] * p_HCV_HIV_METC_INJ
a_TDP_3[HCV & INJ, METC & INJ & COI, ] <- a_TDP_3[HCV & INJ, METC & INJ & COI, ] * p_HCV_HIV_METC_INJ
# REL
# From NEG
a_TDP_1[NEG & INJ, REL & INJ & NEG, ] <- a_TDP_1[NEG & INJ, REL & INJ & NEG, ] * (1 - p_HIV_REL_INJ - p_HCV_REL_INJ)
a_TDP_2[NEG & INJ, REL & INJ & NEG, ] <- a_TDP_2[NEG & INJ, REL & INJ & NEG, ] * (1 - p_HIV_REL_INJ - p_HCV_REL_INJ)
a_TDP_3[NEG & INJ, REL & INJ & NEG, ] <- a_TDP_3[NEG & INJ, REL & INJ & NEG, ] * (1 - p_HIV_REL_INJ - p_HCV_REL_INJ)
a_TDP_1[NEG & INJ, REL & INJ & HIV, ] <- a_TDP_1[NEG & INJ, REL & INJ & HIV, ] * p_HIV_REL_INJ
a_TDP_2[NEG & INJ, REL & INJ & HIV, ] <- a_TDP_2[NEG & INJ, REL & INJ & HIV, ] * p_HIV_REL_INJ
a_TDP_3[NEG & INJ, REL & INJ & HIV, ] <- a_TDP_3[NEG & INJ, REL & INJ & HIV, ] * p_HIV_REL_INJ
a_TDP_1[NEG & INJ, REL & INJ & HCV, ] <- a_TDP_1[NEG & INJ, REL & INJ & HCV, ] * p_HCV_REL_INJ
a_TDP_2[NEG & INJ, REL & INJ & HCV, ] <- a_TDP_2[NEG & INJ, REL & INJ & HCV, ] * p_HCV_REL_INJ
a_TDP_3[NEG & INJ, REL & INJ & HCV, ] <- a_TDP_3[NEG & INJ, REL & INJ & HCV, ] * p_HCV_REL_INJ
# From HIV
a_TDP_1[HIV & INJ, REL & INJ & HIV, ] <- a_TDP_1[HIV & INJ, REL & INJ & HIV, ] * (1 - p_HIV_HCV_REL_INJ)
a_TDP_2[HIV & INJ, REL & INJ & HIV, ] <- a_TDP_2[HIV & INJ, REL & INJ & HIV, ] * (1 - p_HIV_HCV_REL_INJ)
a_TDP_3[HIV & INJ, REL & INJ & HIV, ] <- a_TDP_3[HIV & INJ, REL & INJ & HIV, ] * (1 - p_HIV_HCV_REL_INJ)
a_TDP_1[HIV & INJ, REL & INJ & COI, ] <- a_TDP_1[HIV & INJ, REL & INJ & COI, ] * p_HIV_HCV_REL_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, REL & INJ & COI, ] <- a_TDP_2[HIV & INJ, REL & INJ & COI, ] * p_HIV_HCV_REL_INJ
a_TDP_3[HIV & INJ, REL & INJ & COI, ] <- a_TDP_3[HIV & INJ, REL & INJ & COI, ] * p_HIV_HCV_REL_INJ
# From HCV
a_TDP_1[HCV & INJ, REL & INJ & HCV, ] <- a_TDP_1[HCV & INJ, REL & INJ & HCV, ] * (1 - p_HCV_HIV_REL_INJ)
a_TDP_2[HCV & INJ, REL & INJ & HCV, ] <- a_TDP_2[HCV & INJ, REL & INJ & HCV, ] * (1 - p_HCV_HIV_REL_INJ)
a_TDP_3[HCV & INJ, REL & INJ & HCV, ] <- a_TDP_3[HCV & INJ, REL & INJ & HCV, ] * (1 - p_HCV_HIV_REL_INJ)
a_TDP_1[HCV & INJ, REL & INJ & COI, ] <- a_TDP_1[HCV & INJ, REL & INJ & COI, ] * p_HCV_HIV_REL_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, REL & INJ & COI, ] <- a_TDP_2[HCV & INJ, REL & INJ & COI, ] * p_HCV_HIV_REL_INJ
a_TDP_3[HCV & INJ, REL & INJ & COI, ] <- a_TDP_3[HCV & INJ, REL & INJ & COI, ] * p_HCV_HIV_REL_INJ
# ODN
# From NEG
a_TDP_1[NEG & INJ, ODN & INJ & NEG, ] <- a_TDP_1[NEG & INJ, ODN & INJ & NEG, ] * (1 - p_HIV_ODN_INJ - p_HCV_ODN_INJ)
a_TDP_2[NEG & INJ, ODN & INJ & NEG, ] <- a_TDP_2[NEG & INJ, ODN & INJ & NEG, ] * (1 - p_HIV_ODN_INJ - p_HCV_ODN_INJ)
a_TDP_3[NEG & INJ, ODN & INJ & NEG, ] <- a_TDP_3[NEG & INJ, ODN & INJ & NEG, ] * (1 - p_HIV_ODN_INJ - p_HCV_ODN_INJ)
a_TDP_1[NEG & INJ, ODN & INJ & HIV, ] <- a_TDP_1[NEG & INJ, ODN & INJ & HIV, ] * p_HIV_ODN_INJ
a_TDP_2[NEG & INJ, ODN & INJ & HIV, ] <- a_TDP_2[NEG & INJ, ODN & INJ & HIV, ] * p_HIV_ODN_INJ
a_TDP_3[NEG & INJ, ODN & INJ & HIV, ] <- a_TDP_3[NEG & INJ, ODN & INJ & HIV, ] * p_HIV_ODN_INJ
a_TDP_1[NEG & INJ, ODN & INJ & HCV, ] <- a_TDP_1[NEG & INJ, ODN & INJ & HCV, ] * p_HCV_ODN_INJ
a_TDP_2[NEG & INJ, ODN & INJ & HCV, ] <- a_TDP_2[NEG & INJ, ODN & INJ & HCV, ] * p_HCV_ODN_INJ
a_TDP_3[NEG & INJ, ODN & INJ & HCV, ] <- a_TDP_3[NEG & INJ, ODN & INJ & HCV, ] * p_HCV_ODN_INJ
# From HIV
a_TDP_1[HIV & INJ, ODN & INJ & HIV, ] <- a_TDP_1[HIV & INJ, ODN & INJ & HIV, ] * (1 - p_HIV_HCV_ODN_INJ)
a_TDP_2[HIV & INJ, ODN & INJ & HIV, ] <- a_TDP_2[HIV & INJ, ODN & INJ & HIV, ] * (1 - p_HIV_HCV_ODN_INJ)
a_TDP_3[HIV & INJ, ODN & INJ & HIV, ] <- a_TDP_3[HIV & INJ, ODN & INJ & HIV, ] * (1 - p_HIV_HCV_ODN_INJ)
a_TDP_1[HIV & INJ, ODN & INJ & COI, ] <- a_TDP_1[HIV & INJ, ODN & INJ & COI, ] * p_HIV_HCV_ODN_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, ODN & INJ & COI, ] <- a_TDP_2[HIV & INJ, ODN & INJ & COI, ] * p_HIV_HCV_ODN_INJ
a_TDP_3[HIV & INJ, ODN & INJ & COI, ] <- a_TDP_3[HIV & INJ, ODN & INJ & COI, ] * p_HIV_HCV_ODN_INJ
# From HCV
a_TDP_1[HCV & INJ, ODN & INJ & HCV, ] <- a_TDP_1[HCV & INJ, ODN & INJ & HCV, ] * (1 - p_HCV_HIV_ODN_INJ)
a_TDP_2[HCV & INJ, ODN & INJ & HCV, ] <- a_TDP_2[HCV & INJ, ODN & INJ & HCV, ] * (1 - p_HCV_HIV_ODN_INJ)
a_TDP_3[HCV & INJ, ODN & INJ & HCV, ] <- a_TDP_3[HCV & INJ, ODN & INJ & HCV, ] * (1 - p_HCV_HIV_ODN_INJ)
a_TDP_1[HCV & INJ, ODN & INJ & COI, ] <- a_TDP_1[HCV & INJ, ODN & INJ & COI, ] * p_HCV_HIV_ODN_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, ODN & INJ & COI, ] <- a_TDP_2[HCV & INJ, ODN & INJ & COI, ] * p_HCV_HIV_ODN_INJ
a_TDP_3[HCV & INJ, ODN & INJ & COI, ] <- a_TDP_3[HCV & INJ, ODN & INJ & COI, ] * p_HCV_HIV_ODN_INJ
# ODF
# From NEG
a_TDP_1[NEG & INJ, ODF & INJ & NEG, ] <- a_TDP_1[NEG & INJ, ODF & INJ & NEG, ] * 1
a_TDP_2[NEG & INJ, ODF & INJ & NEG, ] <- a_TDP_2[NEG & INJ, ODF & INJ & NEG, ] * 1
a_TDP_3[NEG & INJ, ODF & INJ & NEG, ] <- a_TDP_3[NEG & INJ, ODF & INJ & NEG, ] * 1
a_TDP_1[NEG & INJ, ODF & INJ & HIV, ] <- a_TDP_1[NEG & INJ, ODF & INJ & HIV, ] * 0
a_TDP_2[NEG & INJ, ODF & INJ & HIV, ] <- a_TDP_2[NEG & INJ, ODF & INJ & HIV, ] * 0
a_TDP_3[NEG & INJ, ODF & INJ & HIV, ] <- a_TDP_3[NEG & INJ, ODF & INJ & HIV, ] * 0
a_TDP_1[NEG & INJ, ODF & INJ & HCV, ] <- a_TDP_1[NEG & INJ, ODF & INJ & HCV, ] * 0
a_TDP_2[NEG & INJ, ODF & INJ & HCV, ] <- a_TDP_2[NEG & INJ, ODF & INJ & HCV, ] * 0
a_TDP_3[NEG & INJ, ODF & INJ & HCV, ] <- a_TDP_3[NEG & INJ, ODF & INJ & HCV, ] * 0
# From HIV
a_TDP_1[HIV & INJ, ODF & INJ & HIV, ] <- a_TDP_1[HIV & INJ, ODF & INJ & HIV, ] * 1
a_TDP_2[HIV & INJ, ODF & INJ & HIV, ] <- a_TDP_2[HIV & INJ, ODF & INJ & HIV, ] * 1
a_TDP_3[HIV & INJ, ODF & INJ & HIV, ] <- a_TDP_3[HIV & INJ, ODF & INJ & HIV, ] * 1
a_TDP_1[HIV & INJ, ODF & INJ & COI, ] <- a_TDP_1[HIV & INJ, ODF & INJ & COI, ] * 0
a_TDP_2[HIV & INJ, ODF & INJ & COI, ] <- a_TDP_2[HIV & INJ, ODF & INJ & COI, ] * 0
a_TDP_3[HIV & INJ, ODF & INJ & COI, ] <- a_TDP_3[HIV & INJ, ODF & INJ & COI, ] * 0
# From HCV
a_TDP_1[HCV & INJ, ODF & INJ & HCV, ] <- a_TDP_1[HCV & INJ, ODF & INJ & HCV, ] * 1
a_TDP_2[HCV & INJ, ODF & INJ & HCV, ] <- a_TDP_2[HCV & INJ, ODF & INJ & HCV, ] * 1
a_TDP_3[HCV & INJ, ODF & INJ & HCV, ] <- a_TDP_3[HCV & INJ, ODF & INJ & HCV, ] * 1
a_TDP_1[HCV & INJ, ODF & INJ & COI, ] <- a_TDP_1[HCV & INJ, ODF & INJ & COI, ] * 0
a_TDP_2[HCV & INJ, ODF & INJ & COI, ] <- a_TDP_2[HCV & INJ, ODF & INJ & COI, ] * 0
a_TDP_3[HCV & INJ, ODF & INJ & COI, ] <- a_TDP_3[HCV & INJ, ODF & INJ & COI, ] * 0
# ABS
# From NEG
a_TDP_1[NEG & INJ, ABS & INJ & NEG, ] <- a_TDP_1[NEG & INJ, ABS & INJ & NEG, ] * (1 - p_HIV_ABS_INJ - p_HCV_ABS_INJ)
a_TDP_2[NEG & INJ, ABS & INJ & NEG, ] <- a_TDP_2[NEG & INJ, ABS & INJ & NEG, ] * (1 - p_HIV_ABS_INJ - p_HCV_ABS_INJ)
a_TDP_3[NEG & INJ, ABS & INJ & NEG, ] <- a_TDP_3[NEG & INJ, ABS & INJ & NEG, ] * (1 - p_HIV_ABS_INJ - p_HCV_ABS_INJ)
a_TDP_1[NEG & INJ, ABS & INJ & HIV, ] <- a_TDP_1[NEG & INJ, ABS & INJ & HIV, ] * p_HIV_ABS_INJ
a_TDP_2[NEG & INJ, ABS & INJ & HIV, ] <- a_TDP_2[NEG & INJ, ABS & INJ & HIV, ] * p_HIV_ABS_INJ
a_TDP_3[NEG & INJ, ABS & INJ & HIV, ] <- a_TDP_3[NEG & INJ, ABS & INJ & HIV, ] * p_HIV_ABS_INJ
a_TDP_1[NEG & INJ, ABS & INJ & HCV, ] <- a_TDP_1[NEG & INJ, ABS & INJ & HCV, ] * p_HCV_ABS_INJ
a_TDP_2[NEG & INJ, ABS & INJ & HCV, ] <- a_TDP_2[NEG & INJ, ABS & INJ & HCV, ] * p_HCV_ABS_INJ
a_TDP_3[NEG & INJ, ABS & INJ & HCV, ] <- a_TDP_3[NEG & INJ, ABS & INJ & HCV, ] * p_HCV_ABS_INJ
# From HIV
a_TDP_1[HIV & INJ, ABS & INJ & HIV, ] <- a_TDP_1[HIV & INJ, ABS & INJ & HIV, ] * (1 - p_HIV_HCV_ABS_INJ)
a_TDP_2[HIV & INJ, ABS & INJ & HIV, ] <- a_TDP_2[HIV & INJ, ABS & INJ & HIV, ] * (1 - p_HIV_HCV_ABS_INJ)
a_TDP_3[HIV & INJ, ABS & INJ & HIV, ] <- a_TDP_3[HIV & INJ, ABS & INJ & HIV, ] * (1 - p_HIV_HCV_ABS_INJ)
a_TDP_1[HIV & INJ, ABS & INJ & COI, ] <- a_TDP_1[HIV & INJ, ABS & INJ & COI, ] * p_HIV_HCV_ABS_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, ABS & INJ & COI, ] <- a_TDP_2[HIV & INJ, ABS & INJ & COI, ] * p_HIV_HCV_ABS_INJ
a_TDP_3[HIV & INJ, ABS & INJ & COI, ] <- a_TDP_3[HIV & INJ, ABS & INJ & COI, ] * p_HIV_HCV_ABS_INJ
# From HCV
a_TDP_1[HCV & INJ, ABS & INJ & HCV, ] <- a_TDP_1[HCV & INJ, ABS & INJ & HCV, ] * (1 - p_HCV_HIV_ABS_INJ)
a_TDP_2[HCV & INJ, ABS & INJ & HCV, ] <- a_TDP_2[HCV & INJ, ABS & INJ & HCV, ] * (1 - p_HCV_HIV_ABS_INJ)
a_TDP_3[HCV & INJ, ABS & INJ & HCV, ] <- a_TDP_3[HCV & INJ, ABS & INJ & HCV, ] * (1 - p_HCV_HIV_ABS_INJ)
a_TDP_1[HCV & INJ, ABS & INJ & COI, ] <- a_TDP_1[HCV & INJ, ABS & INJ & COI, ] * p_HCV_HIV_ABS_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, ABS & INJ & COI, ] <- a_TDP_2[HCV & INJ, ABS & INJ & COI, ] * p_HCV_HIV_ABS_INJ
a_TDP_3[HCV & INJ, ABS & INJ & COI, ] <- a_TDP_3[HCV & INJ, ABS & INJ & COI, ] * p_HCV_HIV_ABS_INJ
#### Disallowed transitions (ensure that impossible transitions are set to zero) ####
# Episode rules
a_TDP_1[EP1, EP3, ] <- a_TDP_2[EP1, EP3, ] <- a_TDP_3[EP1, EP3, ] <- 0
a_TDP_1[EP2, EP1, ] <- a_TDP_2[EP2, EP1, ] <- a_TDP_3[EP2, EP1, ] <- 0
a_TDP_1[EP3, EP1, ] <- a_TDP_2[EP3, EP1, ] <- a_TDP_3[EP3, EP1, ] <- 0
a_TDP_1[EP3, EP2, ] <- a_TDP_2[EP3, EP2, ] <- a_TDP_3[EP3, EP2, ] <- 0
# Injection <> Non-injection
a_TDP_1[INJ, NI,] <- a_TDP_2[INJ, NI,] <- a_TDP_3[INJ, NI,] <- 0
a_TDP_1[NI, INJ,] <- a_TDP_2[NI, INJ,] <- a_TDP_3[NI, INJ,] <- 0
# Seroconversions
a_TDP_1[HIV, NEG, ] <- a_TDP_2[HIV, NEG, ] <- a_TDP_3[HIV, NEG, ] <- 0
a_TDP_1[HCV, NEG, ] <- a_TDP_2[HCV, NEG, ] <- a_TDP_3[HCV, NEG, ] <- 0
a_TDP_1[COI, NEG, ] <- a_TDP_2[COI, NEG, ] <- a_TDP_3[COI, NEG, ] <- 0
a_TDP_1[HIV, HCV, ] <- a_TDP_2[HIV, HCV, ] <- a_TDP_3[HIV, HCV, ] <- 0
a_TDP_1[HCV, HIV, ] <- a_TDP_2[HCV, HIV, ] <- a_TDP_3[HCV, HIV, ] <- 0
a_TDP_1[COI, HIV, ] <- a_TDP_2[COI, HIV, ] <- a_TDP_3[COI, HIV, ] <- 0
a_TDP_1[COI, HCV, ] <- a_TDP_2[COI, HCV, ] <- a_TDP_3[COI, HCV, ] <- 0
a_TDP_1[COI, NEG, ] <- a_TDP_2[COI, NEG, ] <- a_TDP_3[COI, NEG, ] <- 0
a_TDP_1[NEG, COI, ] <- a_TDP_2[NEG, COI, ] <- a_TDP_3[NEG, COI, ] <- 0
# Conditional transitions
# Next episode with out-of-treatment(OOT) EPi -> treatment(TX) EP(i+1)
a_TDP_1[all_TX & EP1, all_TX & EP2, ] <- a_TDP_2[all_TX & EP1, all_TX & EP2, ] <- a_TDP_3[all_TX & EP1, all_TX & EP2, ] <- 0
a_TDP_1[all_TX & EP1, all_TX & EP3, ] <- a_TDP_2[all_TX & EP1, all_TX & EP3, ] <- a_TDP_3[all_TX & EP1, all_TX & EP3, ] <- 0
a_TDP_1[all_TX & EP2, all_TX & EP3, ] <- a_TDP_2[all_TX & EP2, all_TX & EP3, ] <- a_TDP_3[all_TX & EP2, all_TX & EP3, ] <- 0
a_TDP_1[OOT & EP1, OOT & EP2, ] <- a_TDP_2[OOT & EP1, OOT & EP2, ] <- a_TDP_3[OOT & EP1, OOT & EP2, ] <- 0
a_TDP_1[OOT & EP1, OOT & EP3, ] <- a_TDP_2[OOT & EP1, OOT & EP3, ] <- a_TDP_3[OOT & EP1, OOT & EP3, ] <- 0
a_TDP_1[OOT & EP2, OOT & EP3, ] <- a_TDP_2[OOT & EP2, OOT & EP3, ] <- a_TDP_3[OOT & EP2, OOT & EP3, ] <- 0
a_TDP_1[all_TX & EP1, OOT & EP2, ] <- a_TDP_2[all_TX & EP1, OOT & EP2, ] <- a_TDP_3[all_TX & EP1, OOT & EP2, ] <- 0
a_TDP_1[all_TX & EP2, OOT & EP3, ] <- a_TDP_2[all_TX & EP2, OOT & EP3, ] <- a_TDP_3[all_TX & EP2, OOT & EP3, ] <- 0
a_TDP_1[OOT & EP1, all_TX & EP1, ] <- a_TDP_2[OOT & EP1, all_TX & EP1, ] <- a_TDP_3[OOT & EP1, all_TX & EP1, ] <- 0
a_TDP_1[OOT & EP2, all_TX & EP2, ] <- a_TDP_2[OOT & EP2, all_TX & EP2, ] <- a_TDP_3[OOT & EP2, all_TX & EP2, ] <- 0
if(checks){
# State transitions
# First month (state-time)
#write.csv(a_UP_first[, , 1], "checks/state transitions/a_UP_first_2018.csv")
#write.csv(a_UP_first[, , 2], "checks/state transitions/a_UP_first_2019.csv")
#write.csv(a_UP_first[, , 3], "checks/state transitions/a_UP_first_2020.csv")
# Month 2+ (state-time)
#write.csv(a_UP[, , 1], "checks/state transitions/a_UP_2018.csv")
#write.csv(a_UP[, , 2], "checks/state transitions/a_UP_2019.csv")
#write.csv(a_UP[, , 3], "checks/state transitions/a_UP_2020.csv")
# Full array at time = 1
array_2018_1m <- a_TDP_1[, , 1]
array_2019_1m <- a_TDP_2[, , 1]
array_2020_1m <- a_TDP_3[, , 1]
write.csv(array_2018_1m,"checks/full array/array_2018_1m.csv", row.names = TRUE)
write.csv(array_2019_1m,"checks/full array/array_2019_1m.csv", row.names = TRUE)
write.csv(array_2020_1m,"checks/full array/array_2020_1m.csv", row.names = TRUE)
# Full array at time = 24 months
array_2018_24m <- a_TDP_1[, , 24]
array_2019_24m <- a_TDP_2[, , 24]
array_2020_24m <- a_TDP_3[, , 24]
write.csv(array_2018_24m,"checks/full array/array_2018_24m.csv", row.names = TRUE)
write.csv(array_2019_24m,"checks/full array/array_2019_24m.csv", row.names = TRUE)
write.csv(array_2020_24m,"checks/full array/array_2020_24m.csv", row.names = TRUE)
# Full array at time = max
array_2018_last <- a_TDP_1[, , n_t]
array_2019_last <- a_TDP_2[, , n_t]
array_2020_last <- a_TDP_3[, , n_t]
write.csv(array_2018_last,"checks/full array/array_2018_last.csv", row.names = TRUE)
write.csv(array_2019_last,"checks/full array/array_2019_last.csv", row.names = TRUE)
write.csv(array_2020_last,"checks/full array/array_2020_last.csv", row.names = TRUE)
} else{}
#### Check transition array ####
#check_transition_probability(a_P = a_TDP, err_stop = err_stop, verbose = verbose) # check all probs [0, 1]
#check_sum_of_transition_array(a_P = a_TDP, n_states = n_states, n_t = n_t, err_stop = err_stop, verbose = verbose) # check prob sums = 1
#### Run Markov model ####
# Create empty initial state vectors
v_s_init <- rep(0, n_states)
names(v_s_init) <- v_n_states
#### Set initial state vector ####
# Baseline
# Populate baseline states
# Think about this e.g. (all start in EP1, or according to observed %'s in each episode)
# Episode 1
v_s_init[BUP & EP1] <- v_init_dist["pe", "BUP"] # Empirically observed proportions from base states
v_s_init[BUPC & EP1] <- v_init_dist["pe", "BUPC"]
v_s_init[MET & EP1] <- v_init_dist["pe", "MET"]
v_s_init[METC & EP1] <- v_init_dist["pe", "METC"]
v_s_init[REL & EP1] <- v_init_dist["pe", "REL"]
v_s_init[ODN & EP1] <- v_init_dist["pe", "ODN"]
v_s_init[ODF & EP1] <- v_init_dist["pe", "ODF"]
v_s_init[ABS & EP1] <- v_init_dist["pe", "ABS"]
# Distribute by injection/non-injection
v_s_init[NI] <- v_s_init[NI] * (1 - n_INJ)
v_s_init[INJ] <- v_s_init[INJ] * n_INJ
# Distribute HIV/HCV/COI
# Injection
v_s_init[NEG & INJ] <- v_s_init[NEG & INJ] * (1 - n_HIV_INJ - n_HCV_INJ - n_COI_INJ)
v_s_init[HIV & INJ] <- v_s_init[HIV & INJ] * n_HIV_INJ
v_s_init[HCV & INJ] <- v_s_init[HCV & INJ] * n_HCV_INJ
v_s_init[COI & INJ] <- v_s_init[COI & INJ] * n_COI_INJ
# Non-injection
v_s_init[NEG & NI] <- v_s_init[NEG & NI] * (1 - n_HIV_NI - n_HCV_NI - n_COI_NI)
v_s_init[HIV & NI] <- v_s_init[HIV & NI] * n_HIV_NI
v_s_init[HCV & NI] <- v_s_init[HCV & NI] * n_HCV_NI
v_s_init[COI & NI] <- v_s_init[COI & NI] * n_COI_NI
if(checks){
write.csv(v_s_init,"checks/initial/v_s_init.csv", row.names = TRUE)
}
# Create Markov Trace
# Initialize population
a_M_trace <- array(0, dim = c((n_t + 1), n_states, (n_t + 1)),
dimnames = list(0:n_t, v_n_states, 0:n_t))
a_M_trace[1, , 1] <- v_s_init
# Calbrate over three time points (2018, 2019, 2020)
if(cali == TRUE){
# All model time periods
# Split into three periods 0-12; 12-24; 24+ to account for overall time-varying overdose parameters
# Months 0-12 (model-time)
for(i in 2:11){
# Time spent in given health state
# First month (state-time)
for(j in 1:(i - 1)){
# state-time-dependent transition probability (j) * age (model-time)-specific mortality (i) * model-time-specific overdose (track in separate matrix)
# Conditional state transition matrix at time (j) ~ sojourn time is continuous time spent in health state
# Remove deaths from all states (depends only on cohort age (i) and health state-specific SMR
m_sojourn <- a_TDP_1[, , j] * m_alive[, i - 1] # state-time transition matrix at state-time j, re-weighted for model-time (age) varying mortality at each time point
# Current health states from prior cycle
# Row vector of individuals across all health states
v_current_state <- as.vector(a_M_trace[i - 1, , j]) # all in current state
# Transitions remaining in current states
# Multiply current vector of state occupancy by diagonal of state-time-dependent array (i.e., the conditional probability of remaining in given health state)
v_same_state <- as.vector(v_current_state * diag(m_sojourn)) # individuals remaining in state next period
# Add remain probabilities to next period, increase sojourn time by 1
# a_M_trace already initialized for i = 1 above
# Add % individuals remaining in subsequent period only
a_M_trace[i, ,j + 1] <- v_same_state # add remain to next period
# Set diagonal to zero as these have been counted
# Reset only remain (diagonal) to zero and keep state transitions
diag(m_sojourn) <- 0 # reset remain to 0 once counted
# Transitions to new health states
# Create vector of states following transition according to conditional state-transition matrix excluding remain (i.e., multiply same states by zero)
v_new_state <- as.vector(v_current_state %*% m_sojourn) # populate new states post-transition (excluding remaining)
# Add new state %'s to markov trace
a_M_trace[i, ,1] <- v_new_state + a_M_trace[i, ,1] # add new state %'s to array
}
}
# Months 12-23 (model-time)
for(i in 12:23){
# Time spent in given health state
# First month (state-time)
for(j in 1:(i - 1)){
# state-time-dependent transition probability (j) * age (model-time)-specific mortality (i) * model-time-specific overdose (track in separate matrix)
m_sojourn <- a_TDP_2[, , j] * m_alive[, i - 1] # state-time transition matrix at state-time j, re-weighted for model-time (age) varying mortality at each time point
v_current_state <- as.vector(a_M_trace[i - 1, , j]) # all in current state
v_same_state <- as.vector(v_current_state * diag(m_sojourn)) # individuals remaining in state next period
a_M_trace[i, ,j + 1] <- v_same_state # add remain to next period
diag(m_sojourn) <- 0 # reset remain to 0 once counted
v_new_state <- as.vector(v_current_state %*% m_sojourn) # populate new states post-transition (excluding remaining)
a_M_trace[i, ,1] <- v_new_state + a_M_trace[i, ,1] # add new state %'s to array
}
}
# Months 24+ (model-time)
for(i in 24:(n_t)){
# Time spent in given health state
# First month (state-time)
for(j in 1:(i - 1)){
m_sojourn <- a_TDP_3[, , j] * m_alive[, i - 1] # state-time transition matrix at state-time j, re-weighted for model-time (age) varying mortality at each time point, time-varying overdose (t=3)
v_current_state <- as.vector(a_M_trace[i - 1, , j]) # all in current state
v_same_state <- as.vector(v_current_state * diag(m_sojourn)) # individuals remaining in state next period
a_M_trace[i, ,j + 1] <- v_same_state # add remain to next period
diag(m_sojourn) <- 0 # reset remain to 0 once counted
v_new_state <- as.vector(v_current_state %*% m_sojourn) # populate new states post-transition (excluding remaining)
a_M_trace[i, ,1] <- v_new_state + a_M_trace[i, ,1] # add new state %'s to array
}
}
} else{ # For non-calibration, run model for 2020+
# Full periods (model-time)
for(i in 2:(n_t)){
# Time spent in given health state
# First month (state-time)
for(j in 1:(i - 1)){
m_sojourn <- a_TDP_3[, , j] * m_alive[, i - 1] # state-time transition matrix at state-time j, re-weighted for model-time (age) varying mortality at each time point, time-varying overdose (t=3)
v_current_state <- as.vector(a_M_trace[i - 1, , j]) # all in current state
v_same_state <- as.vector(v_current_state * diag(m_sojourn)) # individuals remaining in state next period
a_M_trace[i, ,j + 1] <- v_same_state # add remain to next period
diag(m_sojourn) <- 0 # reset remain to 0 once counted
v_new_state <- as.vector(v_current_state %*% m_sojourn) # populate new states post-transition (excluding remaining)
a_M_trace[i, ,1] <- v_new_state + a_M_trace[i, ,1] # add new state %'s to array
}
}
}
# Array checks
if(checks){
a_M_trace_1 <- a_M_trace[, , 1]
a_M_trace_2 <- a_M_trace[, , 2]
a_M_trace_3 <- a_M_trace[, , 3]
write.csv(a_M_trace_1,"checks/full trace array/a_M_trace_1.csv", row.names = TRUE)
write.csv(a_M_trace_2,"checks/full trace array/a_M_trace_2.csv", row.names = TRUE)
write.csv(a_M_trace_3,"checks/full trace array/a_M_trace_3.csv", row.names = TRUE)
} else{}
# Collect trace for time-periods across all model states
m_M_trace <- array(0, dim = c((n_t + 1), n_states),
dimnames = list(0:n_t, v_n_states))
for (i in 1:n_t){
m_M_trace[i, ] <- rowSums(a_M_trace[i, ,])
}
# Count cumulative state-specific deaths
m_M_trace_death <- array(0, dim = c((n_t + 1), n_states),
dimnames = list(0:n_t, v_n_states))
for (i in 2:n_t){
m_M_trace_death[i, ] <- m_M_trace[i - 1, ] * m_mort[, i - 1] # State-specific deaths at each time point as function of state-occupancy in t-1
}
m_M_trace_cumsum_death <- apply(m_M_trace_death, 2, cumsum) # Cumulative non-overdose deaths at each time point (use m_M_trace_death for individual period deaths)
#### Create aggregated trace matrices ####
v_agg_trace_states <- c("Alive", "Death", "ODN", "ODF", "REL", "BUP", "BUPC", "MET", "METC", "ABS") # states to aggregate
v_agg_trace_death_states <- c("Total", "ODN", "ODF", "REL", "BUP", "BUPC", "MET", "METC", "ABS") # states to aggregate
v_agg_trace_sero_states <- c("NEG-Alive", "HIV-Alive", "HCV-Alive", "COI-Alive", "NEG-Dead", "HIV-Dead", "HCV-Dead", "COI-Dead") # states to aggregate
n_agg_trace_states <- length(v_agg_trace_states)
n_agg_trace_death_states <- length(v_agg_trace_death_states)
n_agg_trace_sero_states <- length(v_agg_trace_sero_states)
m_M_agg_trace <- array(0, dim = c((n_t + 1), n_agg_trace_states),
dimnames = list(0:n_t, v_agg_trace_states))
m_M_agg_trace_death <- array(0, dim = c((n_t + 1), n_agg_trace_death_states),
dimnames = list(0:n_t, v_agg_trace_death_states))
m_M_agg_trace_sero <- array(0, dim = c((n_t + 1), n_agg_trace_sero_states),
dimnames = list(0:n_t, v_agg_trace_sero_states))
for (i in 1:n_t){
#m_M_agg_trace[i, "Alive"] <- sum(m_M_trace[i, ])
m_M_agg_trace[i, "BUP"] <- sum(m_M_trace[i, BUP])
m_M_agg_trace[i, "BUPC"] <- sum(m_M_trace[i, BUPC])
m_M_agg_trace[i, "MET"] <- sum(m_M_trace[i, MET])
m_M_agg_trace[i, "METC"] <- sum(m_M_trace[i, METC])
m_M_agg_trace[i, "REL"] <- sum(m_M_trace[i, REL])
m_M_agg_trace[i, "ABS"] <- sum(m_M_trace[i, ABS])
m_M_agg_trace[i, "ODN"] <- sum(m_M_trace[i, ODN])
m_M_agg_trace[i, "ODF"] <- sum(m_M_trace[i, ODF])
m_M_agg_trace[i, "Death"] <- 1 - sum(m_M_trace[i, ])
}
# Aggregated state occupancy matrix
write.csv(m_M_agg_trace,"outputs/trace/m_M_agg_trace.csv", row.names = TRUE)
for (i in 1:n_t){
m_M_agg_trace_death[i, "Total"] <- sum(m_M_trace_cumsum_death[i, ])
m_M_agg_trace_death[i, "ODN"] <- sum(m_M_trace_cumsum_death[i, ODN])
m_M_agg_trace_death[i, "ODF"] <- sum(m_M_trace_cumsum_death[i, ODF])
m_M_agg_trace_death[i, "REL"] <- sum(m_M_trace_cumsum_death[i, REL])
m_M_agg_trace_death[i, "BUP"] <- sum(m_M_trace_cumsum_death[i, BUP])
m_M_agg_trace_death[i, "BUPC"] <- sum(m_M_trace_cumsum_death[i, BUPC])
m_M_agg_trace_death[i, "MET"] <- sum(m_M_trace_cumsum_death[i, MET])
m_M_agg_trace_death[i, "METC"] <- sum(m_M_trace_cumsum_death[i, METC])
m_M_agg_trace_death[i, "ABS"] <- sum(m_M_trace_cumsum_death[i, ABS])
}
for (i in 1:n_t){
m_M_agg_trace_sero[i, "NEG-Alive"] <- sum(m_M_trace[i, NEG & !ODF])
m_M_agg_trace_sero[i, "HIV-Alive"] <- sum(m_M_trace[i, HIV & !ODF])
m_M_agg_trace_sero[i, "HCV-Alive"] <- sum(m_M_trace[i, HCV & !ODF])
m_M_agg_trace_sero[i, "COI-Alive"] <- sum(m_M_trace[i, COI & !ODF])
m_M_agg_trace_sero[i, "NEG-Dead"] <- sum(m_M_trace_cumsum_death[i, NEG], m_M_trace[i, NEG & ODF])
m_M_agg_trace_sero[i, "HIV-Dead"] <- sum(m_M_trace_cumsum_death[i, HIV], m_M_trace[i, HIV & ODF])
m_M_agg_trace_sero[i, "HCV-Dead"] <- sum(m_M_trace_cumsum_death[i, HCV], m_M_trace[i, HCV & ODF])
m_M_agg_trace_sero[i, "COI-Dead"] <- sum(m_M_trace_cumsum_death[i, COI], m_M_trace[i, COI & ODF])
}
return(list(l_index_s = l_index_s,
a_M_trace = a_M_trace,
m_M_trace = m_M_trace,
m_M_agg_trace = m_M_agg_trace,
m_M_agg_trace_death = m_M_agg_trace_death,
m_M_agg_trace_sero = m_M_agg_trace_sero))
}
)
}
#' Check if transition array is valid
#'
#' \code{check_transition_probability} checks if individual transition probabilities are in range \[0, 1\].
#'
#' @param a_P A transition probability array.
#' @param err_stop Logical variable to stop model run if set up as TRUE. Default = FALSE.
#' @param verbose Logical variable to indicate print out of messages.
#' Default = FALSE
#'
#' @return
#' This function stops if transition probability array is not valid and shows which entries are invalid
#' @import utils
#' @export
check_transition_probability <- function(a_P,
err_stop = FALSE,
verbose = FALSE) {
m_indices_notvalid <- arrayInd(which(a_P < 0 | a_P > 1),
dim(a_P))
if(dim(m_indices_notvalid)[1] != 0){
v_rows_notval <- rownames(a_P)[m_indices_notvalid[, 1]]
v_cols_notval <- colnames(a_P)[m_indices_notvalid[, 2]]
v_cycles_notval <- dimnames(a_P)[[3]][m_indices_notvalid[, 3]]
df_notvalid <- data.frame(`Transition probabilities not valid:` =
matrix(paste0(paste(v_rows_notval, v_cols_notval, sep = "->"),
"; at cycle ",
v_cycles_notval), ncol = 1),
check.names = FALSE)
if(err_stop) {
stop("Not valid transition probabilities\n",
paste(capture.output(df_notvalid), collapse = "\n"))
}
if(verbose){
warning("Not valid transition probabilities\n",
paste(capture.output(df_notvalid), collapse = "\n"))
}
}
}
#' Check if the sum of transition probabilities from each state are equal to one.
#'
#' \code{check_sum_of_transition_array} checks if each of the rows of the
#' transition matrices sum to one.
#'
#' @param a_P Transition probability array.
#' @param n_states Number of health states.
#' @param n_t Number of time periods.
#' @param err_stop Logical variable to stop model run if set up as TRUE. Default = FALSE.
#' @param verbose Logical variable to indicate print out of messages. Default = FALSE.
#' @return
#' The transition probability array and the cohort trace matrix.
#' @import dplyr
#' @export
check_sum_of_transition_array <- function(a_P,
n_states,
n_t,
err_stop = FALSE,
verbose = FALSE) {
valid <- (apply(a_P, 3, function(x) sum(rowSums(x))) == n_states)
if (!isTRUE(all_equal(as.numeric(sum(valid)), as.numeric(n_t)))) {
if(err_stop) {
stop("This is not a valid transition Matrix")
}
if(verbose){
warning("This is not a valid transition Matrix")
}
}
}
benenns/OUD-Model documentation built on Dec. 15, 2024, 3:52 a.m.
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Defines functions check_sum_of_transition_array check_transition_probability markov_model
#' Markov model
#'
#' \code{markov_model} implements the main model functions to calculate Markov trace.
#'
#' @param l_params_all List with all parameters
#' @param err_stop Logical variable to stop model run if transition array is invalid, if TRUE. Default = FALSE.
#' @param verbose Logical variable to indicate print out of messages. Default = FALSE
#' @param checks Logical variable to indicate output of visual checks (e.g. slices of transition array)
#' @param cali Logical variable to adjust model cutoff to only calibration period
#' @return
#' a_TDP: Transition probability array
#' m_M_trace: Fully stratified markov cohort trace
#' m_M_agg_trace: Aggregated markov trace over base health states
#' m_M_agg_trace_death: State-specific mortality from each health state
#' m_M_agg_trace_sero: HIV seroconversions from each health state
#' @export
markov_model <- function(l_params_all, err_stop = FALSE, verbose = FALSE, checks = FALSE, cali = FALSE){
### Definition:
## Markov model implementation function
### Prefixes:
## l_* denotes list
## n_* denotes number
## a_* denotes 3-D array
## m_* denotes 2-D matrix
## v_* denotes vector
## df_* denotes data frame
## p_* denotes transition parameters
## c_* denotes costs
## u_* denotes utilities
### Arguments:
## l_params_all: List with all parameters
## verbose: Logical variable to indicate print out of messages
### Returns:
## a_TDP: Transition probability array.
## m_M_trace: Fully disaggregated matrix cohort trace.
## m_M_agg_trace: Aggregated trace over selected base health states.
## m_M_agg_trace_death: State-specific mortality from each health state.
## m_M_agg_trace_sero: HIV seroconversions from each health state.
##
with(as.list(l_params_all), {
#### Set up model states ####
l_dim_s <- list() # list of health states
# Base health states
BASE <- l_dim_s[[1]] <- c("MET", "METC", "BUP", "BUPC", "ABS", "REL", "ODN", "ODF")
# Injection/non-injection stratification
INJECT <- l_dim_s[[2]] <- c("NI", "INJ")
# Episodes (1-3)
EP <- l_dim_s[[3]] <- c("1", "2", "3")
# HIV/HCV status
SERO <- l_dim_s[[4]] <- c("NEG", "HIV", "HCV", "COI")
# Set model periods
if(cali == TRUE){
# Calibration periods
n_t <- (n_cali_max_per + 1) # if calibrating, cut model off at max calibration output (e.g. 36 months for three-years)
} else{
# Maximum model periods(regular)
n_t <- (n_age_max - n_age_init) * n_per # convert years
}
df_flat <- expand.grid(l_dim_s) #combine all elements together into vector of health states
df_flat <- dplyr::rename(df_flat, BASE = Var1,
INJECT = Var2,
EP = Var3,
SERO = Var4)
# Create index of states to populate transition matrices
# All treatment
TX <- df_flat$BASE == "BUP" | df_flat$BASE == "MET"
TXC <- df_flat$BASE == "BUPC" | df_flat$BASE == "METC"
all_TX <- df_flat$BASE == "BUP" | df_flat$BASE == "BUPC" | df_flat$BASE == "MET" | df_flat$BASE == "METC"
# All out-of-treatment (incl ABS)
OOT <- df_flat$BASE == "REL" | df_flat$BASE == "ABS" | df_flat$BASE == "ODN" | df_flat$BASE == "ODF"
# Buprenorphine
BUP <- df_flat$BASE == "BUP" # treatment only
BUPC <- df_flat$BASE == "BUPC" # concurrent opioid use
all_BUP <- df_flat$BASE == "BUP" | df_flat$BASE == "BUPC"
# Methadone
MET <- df_flat$BASE == "MET" # treatment only
METC <- df_flat$BASE == "METC" # concurrent opioid use
all_MET <- df_flat$BASE == "MET" | df_flat$BASE == "METC"
# Relapse
REL <- df_flat$BASE == "REL"
# Overdose
all_OD <- df_flat$BASE == "ODN" | df_flat$BASE == "ODF"
non_OD <- df_flat$BASE != "ODN" & df_flat$BASE != "ODF"
ODN <- df_flat$BASE == "ODN" # non-fatal overdose
ODF <- df_flat$BASE == "ODF" # fatal overdose
# Abstinence
ABS <- df_flat$BASE == "ABS"
# Serostatus
NEG <- df_flat$SERO == "NEG"
HIV <- df_flat$SERO == "HIV"
HCV <- df_flat$SERO == "HCV"
COI <- df_flat$SERO == "COI"
all_HIV <- df_flat$SERO == "HIV" | df_flat$SERO == "COI"
all_HCV <- df_flat$SERO == "HCV" | df_flat$SERO == "COI"
# Injection
INJ <- df_flat$INJECT == "INJ"
NI <- df_flat$INJECT == "NI"
# Episodes
EP1 <- df_flat$EP == "1"
EP2 <- df_flat$EP == "2"
EP3 <- df_flat$EP == "3"
df_n <- unite(df_flat, newCol) # combine columns into one data frame of all health states
v_n_states <- df_n[,1] # convert df into vector
n_states <- length(v_n_states) # total number of health states
l_index_s <- list(TX = TX, OOT = OOT,
BUP = BUP, BUPC = BUPC,
MET = MET, METC = METC,
REL = REL,
all_OD = all_OD, ODN = ODN, ODF = ODF,
ABS = ABS,
NEG = NEG, HIV = HIV, HCV = HCV, COI = COI,
INJ = INJ, NI = NI,
EP1 = EP1, EP2 = EP2, EP3 = EP3)
#### Overdose probability ####
#' Probability of non-fatal and fatal overdose
#'
#' \code{p_OD} is used to calculate overdose probabilities from health states. This function also requires additional overdose/fentanyl/naloxone parameters included in `l_params_all`
#'
#' @param rate Baseline overdose rate for health states
#' @param rate_fatal Fatal overdose rate
#' @param rate_fent Fentanyl overdose rate
#' @param multiplier Multiplier for elevated overdose in first month of health state
#' @param fent_mult Multiplier for overdose rate in health states when exposed to fentanyl
#' @param first_month Logical parameter to switch between month 1 and month 2+ for parameter estimation
#' @param fatal Logical parameter to switch between fatal/non-fatal overdose
#' @param injection Logical parameter to adjust rate calculation for injection/non-injection use
#' @param time Time period for time-varying parameters
#'
#' @return
#' `p_OD` monthly probability of fatal or non-fatal overdose from a given health state
#' @export
p_OD <- function(rate,# = rate,
rate_fatal,# = rate_fatal,
#rate_fent = n_fent_OD,
multiplier,# = multiplier,
fent_mult,# = fent_mult,
#fent_reduction_state = fent_reduction_state,
time,# = time,
first_month = FALSE,
fatal = FALSE,
injection = FALSE){
# Probability of successful naloxone use
p_NX_rev <- (p_witness * p_NX_used * p_NX_success)
# Probability of mortality from overdose accounting for baseline overdose fatality and effectiveness of naloxone
# Subsets overdose into fatal and non-fatal, conditional on different parameters
# Convert fatal overdose rate into probability of death following overdose
p_fatal_OD <- 1 - exp(-(rate_fatal))
# Convert fentanyl overdose rate into probability
#p_fent_OD <- 1 - exp(-(rate_fent))
# Probability of fentanyl exposure
# Generate time-varying probability of fentanyl exposure
# Currently modeling logarithmic growth based on 2018-2020 period (consider cutting off at some point, e.g., 5-years, 10-years)
#v_fent_exp_rate <- rep(0, n_t)
#for(i in 2:n_t){
# v_fent_exp_rate[1] <- -log(1- p_fent_exp_base)
# v_fent_exp_rate[i] <- v_fent_exp_rate[i-1] + n_fent_growth_rate
#}
#v_fent_exp_prob <- 1 - exp(-v_fent_exp_rate) # create vector of monthly fentanyl exposure probabilities (generated by growth rates from 2018-2020)
v_fent_exp_prob <- c(p_fent_exp_2018, p_fent_exp_2019, p_fent_exp_2020)
# Adjustment for injection/non-injection
#if (injection){
# v_fent_exp_prob <- v_fent_exp_prob
#} else{
# v_fent_exp_prob <- v_fent_exp_prob * p_ni_fent_reduction
#}
# Convert input monthly rates to monthly probabilities - multiply rates by first month multiplier before converting
if (injection == TRUE && first_month == TRUE){
p_base_OD <- 1 - exp(-(rate * n_INJ_OD_mult * multiplier * (v_fent_exp_prob[time] * fent_mult)))
#p_fent_OD <- 1 - exp(-(rate_fent * multiplier))
}
else if (injection == TRUE && first_month == FALSE){
p_base_OD <- 1 - exp(-(rate * n_INJ_OD_mult * (v_fent_exp_prob[time] * fent_mult)))
#p_fent_OD <- 1 - exp(-(rate_fent))
}
else if (injection == FALSE && first_month == TRUE){
p_base_OD <- 1 - exp(-(rate * multiplier * (v_fent_exp_prob[time] * p_ni_fent_reduction * fent_mult)))
#p_fent_OD <- 1 - exp(-(rate_fent * multiplier))
}
else if (injection == FALSE && first_month == FALSE){
p_base_OD <- 1 - exp(-(rate * (v_fent_exp_prob[time] * p_ni_fent_reduction * fent_mult)))
#p_fent_OD <- 1 - exp(-(rate_fent))
}
# Naloxone effect on fatal overdose
p_fatal_OD_NX <- p_fatal_OD * (1 - p_NX_rev)
# Probability of fentanyl exposure (adjusted for injection/non-injection)
#if (injection){
#p_fent_exp <- p_fent_exp
#} else{
# p_fent_exp <- p_fent_exp * p_ni_fent_reduction
#}
# Calculate fatal and non-fatal overdose probabilities
if (fatal == TRUE){
p_OD <- p_base_OD * p_fatal_OD_NX #((p_base_OD * (1 - p_fent_exp)) + (p_fent_OD * (p_fent_exp))) * p_fatal_OD_NX
} else{
p_OD <- p_base_OD * (1 - p_fatal_OD_NX) #((p_base_OD * (1 - p_fent_exp)) + (p_fent_OD * (p_fent_exp))) * (1 - p_fatal_OD_NX)
}
return(p_OD)
}
# Module to calculate probability of overdose from states
# Four separate matrices to account for state-time (first month vs. second+), and model-time (changing fentanyl prevalence, etc.)
#### Time-dependent overdose probabilities ####
# Time periods
time_periods <- n_cali_per
# Empty 2-D matrix
m_ODN <- m_ODN_first <- m_ODF <- m_ODF_first <- array(0, dim = c(n_states, time_periods),
dimnames = list(v_n_states, 1:time_periods))
#test<- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_TX_OD_mult, fent_mult = n_fent_OD_mult, time = 1, first_month = TRUE, fatal = FALSE, injection = FALSE)
for(i in 1:time_periods){
# Probability of overdose
# Non-fatal (first month)
m_ODN_first[BUP & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[MET & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[TXC & NI, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[REL & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[ODN & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[ABS & NI, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = FALSE)
m_ODN_first[BUP & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[MET & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[TXC & INJ, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[REL & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[ODN & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
m_ODN_first[ABS & INJ, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = FALSE, injection = TRUE)
# Fatal (first month)
m_ODF_first[BUP & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[MET & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[TXC & NI, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[REL & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[ODN & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[ABS & NI, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = FALSE)
m_ODF_first[BUP & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[MET & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[TXC & INJ, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[REL & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[ODN & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
m_ODF_first[ABS & INJ, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = TRUE, fatal = TRUE, injection = TRUE)
# Non-fatal (month 2+)
m_ODN[BUP & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[MET & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[TXC & NI, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[REL & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[ODN & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[ABS & NI, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = FALSE)
m_ODN[BUP & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[MET & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[TXC & INJ, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[REL & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[ODN & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
m_ODN[ABS & INJ, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = FALSE, injection = TRUE)
# Fatal (month 2+)
m_ODF[BUP & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[MET & NI, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[TXC & NI, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[REL & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[ODN & NI, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[ABS & NI, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = FALSE)
m_ODF[BUP & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_BUP_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[MET & INJ, i] <- p_OD(rate = n_TX_OD, rate_fatal = n_fatal_OD, multiplier = n_MET_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[TXC & INJ, i] <- p_OD(rate = n_TXC_OD, rate_fatal = n_fatal_OD, multiplier = n_TXC_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[REL & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[ODN & INJ, i] <- p_OD(rate = n_REL_OD, rate_fatal = n_fatal_OD, multiplier = n_REL_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
m_ODF[ABS & INJ, i] <- p_OD(rate = n_ABS_OD, rate_fatal = n_fatal_OD, multiplier = n_ABS_OD_mult, fent_mult = n_fent_OD_mult, time = i, first_month = FALSE, fatal = TRUE, injection = TRUE)
}
if (checks){
# Overdose
write.csv(m_ODN_first,"checks/overdose/m_ODN_first.csv", row.names = TRUE)
write.csv(m_ODF_first,"checks/overdose/m_ODF_first.csv", row.names = TRUE)
write.csv(m_ODN,"checks/overdose/m_ODN.csv", row.names = TRUE)
write.csv(m_ODF,"checks/overdose/m_ODF.csv", row.names = TRUE)
} else{}
# Probability of non-overdose
m_non_OD_first <- 1 - (m_ODN_first + m_ODF_first)
m_non_OD <- 1 - (m_ODN + m_ODF)
#### Time-dependent remain probabilities ####
# Empty 2-D matrix
# Three matrices to account for overdose probabilities in 2018, 2019, and 2020+
#m_TDP_1 <- m_TDP_2 <- m_TDP_3 <- m_TDP_1_non_OD <- m_TDP_2_non_OD <- m_TDP_3_non_OD <- array(0, dim = c(n_states, n_t),
# dimnames = list(v_n_states, 1:n_t))
a_remain <- array(0, dim = c(n_states, time_periods, n_t),
dimnames = list(v_n_states, 1:time_periods, 1:n_t))
# Generate state-specific weibull parameters
# Shape
p_weibull_shape_BUP_NI <- p_weibull_shape_BUP_INJ <- p_weibull_shape_BUP
p_weibull_shape_MET_NI <- p_weibull_shape_MET_INJ <- p_weibull_shape_MET
p_weibull_shape_ABS_NI <- p_weibull_shape_ABS_INJ <- p_weibull_shape_ABS
p_weibull_shape_REL_NI <- p_weibull_shape_REL_INJ <- p_weibull_shape_REL
# Scale
p_weibull_scale_BUP_NI <- p_weibull_scale_BUP_INJ <- p_weibull_scale_BUP
p_weibull_scale_MET_NI <- p_weibull_scale_MET_INJ <- p_weibull_scale_MET
p_weibull_scale_ABS_NI <- p_weibull_scale_ABS_INJ <- p_weibull_scale_ABS
p_weibull_scale_REL_NI <- p_weibull_scale_REL_INJ <- p_weibull_scale_REL
# Generate state-specific frailty terms
# Non-injection
p_frailty_BUP_NI_1 <- p_frailty_BUP_1
p_frailty_BUP_NI_2 <- p_frailty_BUP_2
p_frailty_BUP_NI_3 <- p_frailty_BUP_3
p_frailty_BUPC_NI_1 <- p_frailty_BUP_1 * p_frailty_BUPC
p_frailty_BUPC_NI_2 <- p_frailty_BUP_2 * p_frailty_BUPC
p_frailty_BUPC_NI_3 <- p_frailty_BUP_3 * p_frailty_BUPC
p_frailty_MET_NI_1 <- p_frailty_MET_1
p_frailty_MET_NI_2 <- p_frailty_MET_2
p_frailty_MET_NI_3 <- p_frailty_MET_3
p_frailty_METC_NI_1 <- p_frailty_MET_1 * p_frailty_METC
p_frailty_METC_NI_2 <- p_frailty_MET_2 * p_frailty_METC
p_frailty_METC_NI_3 <- p_frailty_MET_3 * p_frailty_METC
p_frailty_ABS_NI_1 <- p_frailty_ABS_1
p_frailty_ABS_NI_2 <- p_frailty_ABS_2
p_frailty_ABS_NI_3 <- p_frailty_ABS_3
p_frailty_REL_NI_1 <- p_frailty_REL_1
p_frailty_REL_NI_2 <- p_frailty_REL_2
p_frailty_REL_NI_3 <- p_frailty_REL_3
# Injection
p_frailty_BUP_INJ_1 <- p_frailty_BUP_1 * p_frailty_BUP_INJ
p_frailty_BUP_INJ_2 <- p_frailty_BUP_2 * p_frailty_BUP_INJ
p_frailty_BUP_INJ_3 <- p_frailty_BUP_3 * p_frailty_BUP_INJ
p_frailty_BUPC_INJ_1 <- p_frailty_BUP_1 * p_frailty_BUP_INJ * p_frailty_BUPC
p_frailty_BUPC_INJ_2 <- p_frailty_BUP_2 * p_frailty_BUP_INJ * p_frailty_BUPC
p_frailty_BUPC_INJ_3 <- p_frailty_BUP_3 * p_frailty_BUP_INJ * p_frailty_BUPC
p_frailty_MET_INJ_1 <- p_frailty_MET_1 * p_frailty_MET_INJ
p_frailty_MET_INJ_2 <- p_frailty_MET_2 * p_frailty_MET_INJ
p_frailty_MET_INJ_3 <- p_frailty_MET_3 * p_frailty_MET_INJ
p_frailty_METC_INJ_1 <- p_frailty_MET_1 * p_frailty_MET_INJ * p_frailty_METC
p_frailty_METC_INJ_2 <- p_frailty_MET_2 * p_frailty_MET_INJ * p_frailty_METC
p_frailty_METC_INJ_3 <- p_frailty_MET_3 * p_frailty_MET_INJ * p_frailty_METC
p_frailty_ABS_INJ_1 <- p_frailty_ABS_1 * p_frailty_ABS_INJ
p_frailty_ABS_INJ_2 <- p_frailty_ABS_2 * p_frailty_ABS_INJ
p_frailty_ABS_INJ_3 <- p_frailty_ABS_3 * p_frailty_ABS_INJ
p_frailty_REL_INJ_1 <- p_frailty_REL_1 * p_frailty_REL_INJ
p_frailty_REL_INJ_2 <- p_frailty_REL_2 * p_frailty_REL_INJ
p_frailty_REL_INJ_3 <- p_frailty_REL_3 * p_frailty_REL_INJ
# Probability of remaining in health state
# All remain in fatal overdose, remain probability = 1
for(j in 1:time_periods){
for(i in 1:n_t){
# Non-injection
# Episode 1
a_remain[EP1 & BUP & NI, j, i] <- as.vector(exp(p_frailty_BUP_NI_1 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP1 & BUPC & NI, j, i] <- as.vector(exp(p_frailty_BUPC_NI_1 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP1 & MET & NI, j, i] <- as.vector(exp(p_frailty_MET_NI_1 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP1 & METC & NI, j, i] <- as.vector(exp(p_frailty_METC_NI_1 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP1 & ABS & NI, j, i] <- as.vector(exp(p_frailty_ABS_NI_1 * p_weibull_scale_ABS_NI * (((i - 1)^p_weibull_shape_ABS_NI) - (i^p_weibull_shape_ABS_NI))))
a_remain[EP1 & REL & NI, j, i] <- as.vector(exp(p_frailty_REL_NI_1 * p_weibull_scale_REL_NI * (((i - 1)^p_weibull_shape_REL_NI) - (i^p_weibull_shape_REL_NI))))
a_remain[EP1 & ODN & NI, j, i] <- 0
a_remain[EP1 & ODF & NI, j, i] <- 1
# Episode 2
a_remain[EP2 & BUP & NI, j, i] <- as.vector(exp(p_frailty_BUP_NI_2 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP2 & BUPC & NI, j, i] <- as.vector(exp(p_frailty_BUPC_NI_2 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP2 & MET & NI, j, i] <- as.vector(exp(p_frailty_MET_NI_2 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP2 & METC & NI, j, i] <- as.vector(exp(p_frailty_METC_NI_2 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP2 & ABS & NI, j, i] <- as.vector(exp(p_frailty_ABS_NI_2 * p_weibull_scale_ABS_NI * (((i - 1)^p_weibull_shape_ABS_NI) - (i^p_weibull_shape_ABS_NI))))
a_remain[EP2 & REL & NI, j, i] <- as.vector(exp(p_frailty_REL_NI_2 * p_weibull_scale_REL_NI * (((i - 1)^p_weibull_shape_REL_NI) - (i^p_weibull_shape_REL_NI))))
a_remain[EP2 & ODN & NI, j, i] <- 0
a_remain[EP2 & ODF & NI, j, i] <- 1
# Episode 3
a_remain[EP3 & BUP & NI, j, i] <- as.vector(exp(p_frailty_BUP_NI_3 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP3 & BUPC & NI, j, i] <- as.vector(exp(p_frailty_BUPC_NI_3 * p_weibull_scale_BUP_NI * (((i - 1)^p_weibull_shape_BUP_NI) - (i^p_weibull_shape_BUP_NI))))
a_remain[EP3 & MET & NI, j, i] <- as.vector(exp(p_frailty_MET_NI_3 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP3 & METC & NI, j, i] <- as.vector(exp(p_frailty_METC_NI_3 * p_weibull_scale_MET_NI * (((i - 1)^p_weibull_shape_MET_NI) - (i^p_weibull_shape_MET_NI))))
a_remain[EP3 & ABS & NI, j, i] <- as.vector(exp(p_frailty_ABS_NI_3 * p_weibull_scale_ABS_NI * (((i - 1)^p_weibull_shape_ABS_NI) - (i^p_weibull_shape_ABS_NI))))
a_remain[EP3 & REL & NI, j, i] <- as.vector(exp(p_frailty_REL_NI_3 * p_weibull_scale_REL_NI * (((i - 1)^p_weibull_shape_REL_NI) - (i^p_weibull_shape_REL_NI))))
a_remain[EP3 & ODN & NI, j, i] <- 0
a_remain[EP3 & ODF & NI, j, i] <- 1
# Injection
# Episode 1
a_remain[EP1 & BUP & INJ, j, i] <- as.vector(exp(p_frailty_BUP_INJ_1 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP1 & BUPC & INJ, j, i] <- as.vector(exp(p_frailty_BUPC_INJ_1 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP1 & MET & INJ, j, i] <- as.vector(exp(p_frailty_MET_INJ_1 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP1 & METC & INJ, j, i] <- as.vector(exp(p_frailty_METC_INJ_1 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP1 & ABS & INJ, j, i] <- as.vector(exp(p_frailty_ABS_INJ_1 * p_weibull_scale_ABS_INJ * (((i - 1)^p_weibull_shape_ABS_INJ) - (i^p_weibull_shape_ABS_INJ))))
a_remain[EP1 & REL & INJ, j, i] <- as.vector(exp(p_frailty_REL_INJ_1 * p_weibull_scale_REL_INJ * (((i - 1)^p_weibull_shape_REL_INJ) - (i^p_weibull_shape_REL_INJ))))
a_remain[EP1 & ODN & INJ, j, i] <- 0
a_remain[EP1 & ODF & INJ, j, i] <- 1
# Episode 2
a_remain[EP2 & BUP & INJ, j, i] <- as.vector(exp(p_frailty_BUP_INJ_2 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP2 & BUPC & INJ, j, i] <- as.vector(exp(p_frailty_BUPC_INJ_2 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP2 & MET & INJ, j, i] <- as.vector(exp(p_frailty_MET_INJ_2 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP2 & METC & INJ, j, i] <- as.vector(exp(p_frailty_METC_INJ_2 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP2 & ABS & INJ, j, i] <- as.vector(exp(p_frailty_ABS_INJ_2 * p_weibull_scale_ABS_INJ * (((i - 1)^p_weibull_shape_ABS_INJ) - (i^p_weibull_shape_ABS_INJ))))
a_remain[EP2 & REL & INJ, j, i] <- as.vector(exp(p_frailty_REL_INJ_2 * p_weibull_scale_REL_INJ * (((i - 1)^p_weibull_shape_REL_INJ) - (i^p_weibull_shape_REL_INJ))))
a_remain[EP2 & ODN & INJ, j, i] <- 0
a_remain[EP2 & ODF & INJ, j, i] <- 1
# Episode 3
a_remain[EP3 & BUP & INJ, j, i] <- as.vector(exp(p_frailty_BUP_INJ_3 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP3 & BUPC & INJ, j, i] <- as.vector(exp(p_frailty_BUPC_INJ_3 * p_weibull_scale_BUP_INJ * (((i - 1)^p_weibull_shape_BUP_INJ) - (i^p_weibull_shape_BUP_INJ))))
a_remain[EP3 & MET & INJ, j, i] <- as.vector(exp(p_frailty_MET_INJ_3 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP3 & METC & INJ, j, i] <- as.vector(exp(p_frailty_METC_INJ_3 * p_weibull_scale_MET_INJ * (((i - 1)^p_weibull_shape_MET_INJ) - (i^p_weibull_shape_MET_INJ))))
a_remain[EP3 & ABS & INJ, j, i] <- as.vector(exp(p_frailty_ABS_INJ_3 * p_weibull_scale_ABS_INJ * (((i - 1)^p_weibull_shape_ABS_INJ) - (i^p_weibull_shape_ABS_INJ))))
a_remain[EP3 & REL & INJ, j, i] <- as.vector(exp(p_frailty_REL_INJ_3 * p_weibull_scale_REL_INJ * (((i - 1)^p_weibull_shape_REL_INJ) - (i^p_weibull_shape_REL_INJ))))
a_remain[EP3 & ODN & INJ, j, i] <- 0
a_remain[EP3 & ODF & INJ, j, i] <- 1
}
}
# Modify TDP for non-overdose
#for(j in 1:time_periods){
# for(i in 1){
# a_remain_non_OD[, j, i] <- a_remain[, j, i] * m_non_OD_first[, j]
# }
# for(i in 2:n_t){
# a_remain_non_OD[, j, i] <- a_remain_non_OD[, j, i] * m_non_OD[, j]
# }
#}
# Probability of state-exit
m_remain_1 <- a_remain[, 1, ]
m_remain_2 <- a_remain[, 2, ]
m_remain_3 <- a_remain[, 3, ]
m_leave_1 <- 1 - a_remain[, 1, ]
m_leave_2 <- 1 - a_remain[, 2, ]
m_leave_3 <- 1 - a_remain[, 3, ]
#m_leave_1_non_OD <- 1 - m_TDP_1_non_OD
#m_leave_2_non_OD <- 1 - m_TDP_2_non_OD
#m_leave_3_non_OD <- 1 - m_TDP_3_non_OD
if(checks){
# Time dependent state-exit probabilities (from weibull estimates)
write.csv(m_remain_1,"checks/state-time dependent transitions/m_TDP_1.csv", row.names = TRUE)
write.csv(m_remain_2,"checks/state-time dependent transitions/m_TDP_2.csv", row.names = TRUE)
write.csv(m_remain_3,"checks/state-time dependent transitions/m_TDP_3.csv", row.names = TRUE)
#write.csv(m_TDP_1_non_OD,"checks/state-time dependent transitions/m_TDP_1_non_OD.csv", row.names = TRUE)
#write.csv(m_TDP_2_non_OD,"checks/state-time dependent transitions/m_TDP_2_non_OD.csv", row.names = TRUE)
#write.csv(m_TDP_3_non_OD,"checks/state-time dependent transitions/m_TDP_3_non_OD.csv", row.names = TRUE)
write.csv(m_leave_1,"checks/state-time dependent transitions/m_leave_1.csv", row.names = TRUE)
write.csv(m_leave_2,"checks/state-time dependent transitions/m_leave_2.csv", row.names = TRUE)
write.csv(m_leave_3,"checks/state-time dependent transitions/m_leave_3.csv", row.names = TRUE)
#write.csv(m_leave_1_non_OD,"checks/state-time dependent transitions/m_leave_1_non_OD.csv", row.names = TRUE)
#write.csv(m_leave_2_non_OD,"checks/state-time dependent transitions/m_leave_2_non_OD.csv", row.names = TRUE)
#write.csv(m_leave_3_non_OD,"checks/state-time dependent transitions/m_leave_3_non_OD.csv", row.names = TRUE)
} else{}
#### Mortality ####
#' Mortality probability estimates
#'
#' \code{v_mort} is used to populate mortality probability vectors.
#'
#' @param hr
#' @param per
#' @return
#' Mortality vectors for each age applied to model periods (months or weeks), includes state-specific hr.
#' Overdose deaths tracked as "ODF"
#' @export
v_mort <- function(hr = hr, per = per){
v_mort <- rep((1 - exp(-v_r_mort_by_age[n_age_init:(n_age_max - 1), ] * (1/per) * hr)), each = per) #currently working in months
return(v_mort)
}
# Non-injection
v_mort_BUP_NI <- v_mort(hr = hr_BUP_NI, per = n_per)
v_mort_BUPC_NI <- v_mort(hr = hr_BUPC_NI, per = n_per)
v_mort_MET_NI <- v_mort(hr = hr_MET_NI, per = n_per)
v_mort_METC_NI <- v_mort(hr = hr_METC_NI, per = n_per)
v_mort_REL_NI <- v_mort(hr = hr_REL_NI, per = n_per)
v_mort_ODN_NI <- v_mort(hr = hr_ODN_NI, per = n_per) # Mortality equal for REL/ODN (fatal overdoses counted separately)
v_mort_ODF_NI <- rep(0, n_t) # stay in ODF, not tracked in "death"
v_mort_ABS_NEG_NI <- v_mort(hr = hr_ABS_NI, per = n_per)
v_mort_ABS_HIV_NI <- v_mort(hr = hr_HIV_NI, per = n_per)
v_mort_ABS_HCV_NI <- v_mort(hr = hr_HCV_NI, per = n_per)
v_mort_ABS_COI_NI <- v_mort(hr = hr_COI_NI, per = n_per)
# Injection
v_mort_BUP_INJ <- v_mort(hr = hr_BUP_INJ, per = n_per)
v_mort_BUPC_INJ <- v_mort(hr = hr_BUPC_INJ, per = n_per)
v_mort_MET_INJ <- v_mort(hr = hr_MET_INJ, per = n_per)
v_mort_METC_INJ <- v_mort(hr = hr_METC_INJ, per = n_per)
v_mort_REL_INJ <- v_mort(hr = hr_REL_INJ, per = n_per)
v_mort_ODN_INJ <- v_mort(hr = hr_ODN_INJ, per = n_per) # Mortality equal for REL/ODN (fatal overdoses counted separately)
v_mort_ODF_INJ <- rep(0, n_t) # stay in ODF, not tracked in "death"
v_mort_ABS_NEG_INJ <- v_mort(hr = hr_ABS_INJ, per = n_per)
v_mort_ABS_HIV_INJ <- v_mort(hr = hr_HIV_INJ, per = n_per)
v_mort_ABS_HCV_INJ <- v_mort(hr = hr_HCV_INJ, per = n_per)
v_mort_ABS_COI_INJ <- v_mort(hr = hr_COI_INJ, per = n_per)
# Create empty mortality matrix
m_mort <- array(0, dim = c(n_states, n_t),
dimnames = list(v_n_states, 1:n_t))
# Populate mortality matrix (death probability from each state)
for (i in 1:n_t){
# Non-injection
m_mort[BUP & NI, i] <- v_mort_BUP_NI[i]
m_mort[BUPC & NI, i] <- v_mort_BUPC_NI[i]
m_mort[MET & NI, i] <- v_mort_MET_NI[i]
m_mort[METC & NI, i] <- v_mort_METC_NI[i]
m_mort[REL & NI, i] <- v_mort_REL_NI[i]
m_mort[ODN & NI, i] <- v_mort_ODN_NI[i] # using background excess mortality for relapse in non-fatal overdose
m_mort[ODF & NI, i] <- v_mort_ODF_NI[i] # transition to death = 0
m_mort[ABS & NI & NEG, i] <- v_mort_ABS_NEG_NI[i]
m_mort[ABS & NI & HIV, i] <- v_mort_ABS_HIV_NI[i]
m_mort[ABS & NI & HCV, i] <- v_mort_ABS_HCV_NI[i]
m_mort[ABS & NI & COI, i] <- v_mort_ABS_COI_NI[i]
# Injection
m_mort[BUP & INJ, i] <- v_mort_BUP_INJ[i]
m_mort[BUPC & INJ, i] <- v_mort_BUPC_INJ[i]
m_mort[MET & INJ, i] <- v_mort_MET_INJ[i]
m_mort[METC & INJ, i] <- v_mort_METC_INJ[i]
m_mort[REL & INJ, i] <- v_mort_REL_INJ[i]
m_mort[ODN & INJ, i] <- v_mort_ODN_INJ[i] # using background excess mortality for relapse in non-fatal overdose
m_mort[ODF & INJ, i] <- v_mort_ODF_INJ[i] # transition to death = 0
m_mort[ABS & INJ & NEG, i] <- v_mort_ABS_NEG_INJ[i]
m_mort[ABS & INJ & HIV, i] <- v_mort_ABS_HIV_INJ[i]
m_mort[ABS & INJ & HCV, i] <- v_mort_ABS_HCV_INJ[i]
m_mort[ABS & INJ & COI, i] <- v_mort_ABS_COI_INJ[i]
}
if(checks){
# Mortality matrix
write.csv(m_mort,"checks/mortality/m_mort.csv", row.names = TRUE)
} else{}
# Alive probability in each period
m_alive <- 1 - m_mort
#### Unconditional transition probabilities ####
# Empty 2-D unconditional transition matrix (from states, to states)
# Create 2 matrices: 1 - First four weeks (higher OD prob)
#m_UP <- m_UP_4wk <- array(0, dim = c(n_states, n_states),
# dimnames = list(v_n_states, v_n_states))
# Create as array (different probabilities for model-time varying overdose)
a_UP <- a_UP_first <- array(0, dim = c(n_states, n_states, time_periods),
dimnames = list(v_n_states, v_n_states, 1:time_periods))
# Populate unconditional transition matrix
# Remove overdose and non-overdose remain probabilities
#p_BUP_non_OD_remain_NI <- 1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i] - a_remain_non_OD[BUP & NI, ]
#p_BUPC_non_OD_remain_NI <- 1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i] - m_TDP_1_non_OD[BUPC & NI, ]
#p_MET_non_OD_remain_NI <- 1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i] - m_TDP_1_non_OD[MET & NI, ]
#p_METC_non_OD_remain_NI <- 1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i] - m_TDP_1_non_OD[METC & NI, ]
#p_ABS_non_OD_remain_NI <- 1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i] - m_TDP_1_non_OD[ABS & NI, ]
#p_REL_non_OD_remain_NI <- 1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i] - m_TDP_1_non_OD[REL & NI, ]
# Overdose probability populated first, accounting for higher probability of overdose transition in first month
for (i in 1:time_periods){
# Non-Injection
# From BUP
# First month
a_UP_first[BUP & NI, BUPC & NI, i] <- p_BUP_BUPC_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i] - m_TDP_1_non_OD[BUP & NI, ])
a_UP_first[BUP & NI, MET & NI, i] <- p_BUP_MET_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i])
a_UP_first[BUP & NI, METC & NI, i] <- p_BUP_METC_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i])
a_UP_first[BUP & NI, ABS & NI, i] <- p_BUP_ABS_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i])
a_UP_first[BUP & NI, REL & NI, i] <- p_BUP_REL_NI #* (1 - m_ODN_first[BUP & NI, i] - m_ODF_first[BUP & NI, i])
#a_UP_first[BUP & NI, ODN & NI, i] <- m_ODN_first[BUP & NI, i]
#a_UP_first[BUP & NI, ODF & NI, i] <- m_ODF_first[BUP & NI, i]
# Month 2+
a_UP[BUP & NI, BUPC & NI, i] <- p_BUP_BUPC_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
a_UP[BUP & NI, MET & NI, i] <- p_BUP_MET_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
a_UP[BUP & NI, METC & NI, i] <- p_BUP_METC_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
a_UP[BUP & NI, ABS & NI, i] <- p_BUP_ABS_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
a_UP[BUP & NI, REL & NI, i] <- p_BUP_REL_NI #* (1 - m_ODN[BUP & NI, i] - m_ODF[BUP & NI, i])
#a_UP[BUP & NI, ODN & NI, i] <- m_ODN[BUP & NI, i]
#a_UP[BUP & NI, ODF & NI, i] <- m_ODF[BUP & NI, i]
# From BUPC
# First month
a_UP_first[BUPC & NI, BUP & NI, i] <- p_BUPC_BUP_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
a_UP_first[BUPC & NI, MET & NI, i] <- p_BUPC_MET_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
a_UP_first[BUPC & NI, METC & NI, i] <- p_BUPC_METC_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
a_UP_first[BUPC & NI, ABS & NI, i] <- p_BUPC_ABS_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
a_UP_first[BUPC & NI, REL & NI, i] <- p_BUPC_REL_NI #* (1 - m_ODN_first[BUPC & NI, i] - m_ODF_first[BUPC & NI, i])
#a_UP_first[BUPC & NI, ODN & NI, i] <- m_ODN_first[BUPC & NI, i]
#a_UP_first[BUPC & NI, ODF & NI, i] <- m_ODF_first[BUPC & NI, i]
# Month 2+
a_UP[BUPC & NI, BUP & NI, i] <- p_BUPC_BUP_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
a_UP[BUPC & NI, MET & NI, i] <- p_BUPC_MET_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
a_UP[BUPC & NI, METC & NI, i] <- p_BUPC_METC_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
a_UP[BUPC & NI, ABS & NI, i] <- p_BUPC_ABS_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
a_UP[BUPC & NI, REL & NI, i] <- p_BUPC_REL_NI #* (1 - m_ODN[BUPC & NI, i] - m_ODF[BUPC & NI, i])
#a_UP[BUPC & NI, ODN & NI, i] <- m_ODN[BUPC & NI, i]
#a_UP[BUPC & NI, ODF & NI, i] <- m_ODF[BUPC & NI, i]
# From MET
# First month
a_UP_first[MET & NI, METC & NI, i] <- p_MET_METC_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
a_UP_first[MET & NI, BUP & NI, i] <- p_MET_BUP_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
a_UP_first[MET & NI, BUPC & NI, i] <- p_MET_BUPC_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
a_UP_first[MET & NI, ABS & NI, i] <- p_MET_ABS_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
a_UP_first[MET & NI, REL & NI, i] <- p_MET_REL_NI #* (1 - m_ODN_first[MET & NI, i] - m_ODF_first[MET & NI, i])
#a_UP_first[MET & NI, ODN & NI, i] <- m_ODN_first[MET & NI, i]
#a_UP_first[MET & NI, ODF & NI, i] <- m_ODF_first[MET & NI, i]
# Month 2+
a_UP[MET & NI, METC & NI, i] <- p_MET_METC_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
a_UP[MET & NI, BUP & NI, i] <- p_MET_BUP_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
a_UP[MET & NI, BUPC & NI, i] <- p_MET_BUPC_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
a_UP[MET & NI, ABS & NI, i] <- p_MET_ABS_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
a_UP[MET & NI, REL & NI, i] <- p_MET_REL_NI #* (1 - m_ODN[MET & NI, i] - m_ODF[MET & NI, i])
#a_UP[MET & NI, ODN & NI, i] <- m_ODN[MET & NI, i]
#a_UP[MET & NI, ODF & NI, i] <- m_ODF[MET & NI, i]
# From METC
# First month
a_UP_first[METC & NI, MET & NI, i] <- p_METC_MET_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
a_UP_first[METC & NI, BUP & NI, i] <- p_METC_BUP_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
a_UP_first[METC & NI, BUPC & NI, i] <- p_METC_BUPC_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
a_UP_first[METC & NI, ABS & NI, i] <- p_METC_ABS_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
a_UP_first[METC & NI, REL & NI, i] <- p_METC_REL_NI #* (1 - m_ODN_first[METC & NI, i] - m_ODF_first[METC & NI, i])
#a_UP_first[METC & NI, ODN & NI, i] <- m_ODN_first[METC & NI, i]
#a_UP_first[METC & NI, ODF & NI, i] <- m_ODF_first[METC & NI, i]
# Month 2+
a_UP[METC & NI, MET & NI, i] <- p_METC_MET_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
a_UP[METC & NI, BUP & NI, i] <- p_METC_BUP_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
a_UP[METC & NI, BUPC & NI, i] <- p_METC_BUPC_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
a_UP[METC & NI, ABS & NI, i] <- p_METC_ABS_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
a_UP[METC & NI, REL & NI, i] <- p_METC_REL_NI #* (1 - m_ODN[METC & NI, i] - m_ODF[METC & NI, i])
#a_UP[METC & NI, ODN & NI, i] <- m_ODN[METC & NI, i]
#a_UP[METC & NI, ODF & NI, i] <- m_ODF[METC & NI, i]
# From ABS
# First month
a_UP_first[ABS & NI, REL & NI, i] <- p_ABS_REL_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
a_UP_first[ABS & NI, MET & NI, i] <- p_ABS_MET_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
a_UP_first[ABS & NI, METC & NI, i] <- p_ABS_METC_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
a_UP_first[ABS & NI, BUP & NI, i] <- p_ABS_BUP_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
a_UP_first[ABS & NI, BUPC & NI, i] <- p_ABS_BUPC_NI #* (1 - m_ODN_first[ABS & NI, i] - m_ODF_first[ABS & NI, i])
#a_UP_first[ABS & NI, ODN & NI, i] <- m_ODN_first[ABS & NI, i]
#a_UP_first[ABS & NI, ODF & NI, i] <- m_ODF_first[ABS & NI, i]
# Month 2+
a_UP[ABS & NI, REL & NI, i] <- p_ABS_REL_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
a_UP[ABS & NI, MET & NI, i] <- p_ABS_MET_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
a_UP[ABS & NI, METC & NI, i] <- p_ABS_METC_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
a_UP[ABS & NI, BUP & NI, i] <- p_ABS_BUP_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
a_UP[ABS & NI, BUPC & NI, i] <- p_ABS_BUPC_NI #* (1 - m_ODN[ABS & NI, i] - m_ODF[ABS & NI, i])
#a_UP[ABS & NI, ODN & NI, i] <- m_ODN[ABS & NI, i]
#a_UP[ABS & NI, ODF & NI, i] <- m_ODF[ABS & NI, i]
# From REL
# First month
a_UP_first[REL & NI, MET & NI, i] <- p_REL_MET_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
a_UP_first[REL & NI, METC & NI, i] <- p_REL_METC_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
a_UP_first[REL & NI, BUP & NI, i] <- p_REL_BUP_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
a_UP_first[REL & NI, BUPC & NI, i] <- p_REL_BUPC_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
a_UP_first[REL & NI, ABS & NI, i] <- p_REL_ABS_NI #* (1 - m_ODN_first[REL & NI, i] - m_ODF_first[REL & NI, i])
#a_UP_first[REL & NI, ODN & NI, i] <- m_ODN_first[REL & NI, i]
#a_UP_first[REL & NI, ODF & NI, i] <- m_ODF_first[REL & NI, i]
# Month 2+
a_UP[REL & NI, MET & NI, i] <- p_REL_MET_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
a_UP[REL & NI, METC & NI, i] <- p_REL_METC_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
a_UP[REL & NI, BUP & NI, i] <- p_REL_BUP_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
a_UP[REL & NI, BUPC & NI, i] <- p_REL_BUPC_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
a_UP[REL & NI, ABS & NI, i] <- p_REL_ABS_NI #* (1 - m_ODN[REL & NI, i] - m_ODF[REL & NI, i])
#a_UP[REL & NI, ODN & NI, i] <- m_ODN[REL & NI, i]
#a_UP[REL & NI, ODF & NI, i] <- m_ODF[REL & NI, i]
# From OD (first month same)
a_UP[ODN & NI, MET & NI, i] <- a_UP_first[ODN & NI, MET & NI, i] <- p_ODN_MET_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, METC & NI, i] <- a_UP_first[ODN & NI, METC & NI, i] <- p_ODN_METC_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, BUP & NI, i] <- a_UP_first[ODN & NI, BUP & NI, i] <- p_ODN_BUP_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, BUPC & NI, i] <- a_UP_first[ODN & NI, BUPC & NI, i] <- p_ODN_BUPC_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, ABS & NI, i] <- a_UP_first[ODN & NI, ABS & NI, i] <- p_ODN_ABS_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
a_UP[ODN & NI, REL & NI, i] <- a_UP_first[ODN & NI, REL & NI, i] <- p_ODN_REL_NI #* (1 - m_ODN[ODN & NI, i] - m_ODF[ODN & NI, i])
#a_UP[ODN & NI, ODF & NI, i] <- m_ODF[ODN & NI, i]
# Injection
# From BUP
# First month
a_UP_first[BUP & INJ, BUPC & INJ, i] <- p_BUP_BUPC_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
a_UP_first[BUP & INJ, MET & INJ, i] <- p_BUP_MET_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
a_UP_first[BUP & INJ, METC & INJ, i] <- p_BUP_METC_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
a_UP_first[BUP & INJ, ABS & INJ, i] <- p_BUP_ABS_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
a_UP_first[BUP & INJ, REL & INJ, i] <- p_BUP_REL_INJ #* (1 - m_ODN_first[BUP & INJ, i] - m_ODF_first[BUP & INJ, i])
#a_UP_first[BUP & INJ, ODN & INJ, i] <- m_ODN_first[BUP & INJ, i]
#a_UP_first[BUP & INJ, ODF & INJ, i] <- m_ODF_first[BUP & INJ, i]
# Month 2+
a_UP[BUP & INJ, BUPC & INJ, i] <- p_BUP_BUPC_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
a_UP[BUP & INJ, MET & INJ, i] <- p_BUP_MET_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
a_UP[BUP & INJ, METC & INJ, i] <- p_BUP_METC_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
a_UP[BUP & INJ, ABS & INJ, i] <- p_BUP_ABS_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
a_UP[BUP & INJ, REL & INJ, i] <- p_BUP_REL_INJ #* (1 - m_ODN[BUP & INJ, i] - m_ODF[BUP & INJ, i])
#a_UP[BUP & INJ, ODN & INJ, i] <- m_ODN[BUP & INJ, i]
#a_UP[BUP & INJ, ODF & INJ, i] <- m_ODF[BUP & INJ, i]
# From BUPC
# First month
a_UP_first[BUPC & INJ, BUP & INJ, i] <- p_BUPC_BUP_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
a_UP_first[BUPC & INJ, MET & INJ, i] <- p_BUPC_MET_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
a_UP_first[BUPC & INJ, METC & INJ, i] <- p_BUPC_METC_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
a_UP_first[BUPC & INJ, ABS & INJ, i] <- p_BUPC_ABS_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
a_UP_first[BUPC & INJ, REL & INJ, i] <- p_BUPC_REL_INJ #* (1 - m_ODN_first[BUPC & INJ, i] - m_ODF_first[BUPC & INJ, i])
#a_UP_first[BUPC & INJ, ODN & INJ, i] <- m_ODN_first[BUPC & INJ, i]
#a_UP_first[BUPC & INJ, ODF & INJ, i] <- m_ODF_first[BUPC & INJ, i]
# Month 2+
a_UP[BUPC & INJ, BUP & INJ, i] <- p_BUPC_BUP_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
a_UP[BUPC & INJ, MET & INJ, i] <- p_BUPC_MET_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
a_UP[BUPC & INJ, METC & INJ, i] <- p_BUPC_METC_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
a_UP[BUPC & INJ, ABS & INJ, i] <- p_BUPC_ABS_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
a_UP[BUPC & INJ, REL & INJ, i] <- p_BUPC_REL_INJ #* (1 - m_ODN[BUPC & INJ, i] - m_ODF[BUPC & INJ, i])
#a_UP[BUPC & INJ, ODN & INJ, i] <- m_ODN[BUPC & INJ, i]
#a_UP[BUPC & INJ, ODF & INJ, i] <- m_ODF[BUPC & INJ, i]
# From MET
# First month
a_UP_first[MET & INJ, METC & INJ, i] <- p_MET_METC_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
a_UP_first[MET & INJ, BUP & INJ, i] <- p_MET_BUP_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
a_UP_first[MET & INJ, BUPC & INJ, i] <- p_MET_BUPC_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
a_UP_first[MET & INJ, ABS & INJ, i] <- p_MET_ABS_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
a_UP_first[MET & INJ, REL & INJ, i] <- p_MET_REL_INJ #* (1 - m_ODN_first[MET & INJ, i] - m_ODF_first[MET & INJ, i])
#a_UP_first[MET & INJ, ODN & INJ, i] <- m_ODN_first[MET & INJ, i]
#a_UP_first[MET & INJ, ODF & INJ, i] <- m_ODF_first[MET & INJ, i]
# Month 2+
a_UP[MET & INJ, METC & INJ, i] <- p_MET_METC_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
a_UP[MET & INJ, BUP & INJ, i] <- p_MET_BUP_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
a_UP[MET & INJ, BUPC & INJ, i] <- p_MET_BUPC_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
a_UP[MET & INJ, ABS & INJ, i] <- p_MET_ABS_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
a_UP[MET & INJ, REL & INJ, i] <- p_MET_REL_INJ #* (1 - m_ODN[MET & INJ, i] - m_ODF[MET & INJ, i])
#a_UP[MET & INJ, ODN & INJ, i] <- m_ODN[MET & INJ, i]
#a_UP[MET & INJ, ODF & INJ, i] <- m_ODF[MET & INJ, i]
# From METC
# First month
a_UP_first[METC & INJ, MET & INJ, i] <- p_METC_MET_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
a_UP_first[METC & INJ, BUP & INJ, i] <- p_METC_BUP_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
a_UP_first[METC & INJ, BUPC & INJ, i] <- p_METC_BUPC_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
a_UP_first[METC & INJ, ABS & INJ, i] <- p_METC_ABS_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
a_UP_first[METC & INJ, REL & INJ, i] <- p_METC_REL_INJ #* (1 - m_ODN_first[METC & INJ, i] - m_ODF_first[METC & INJ, i])
#a_UP_first[METC & INJ, ODN & INJ, i] <- m_ODN_first[METC & INJ, i]
#a_UP_first[METC & INJ, ODF & INJ, i] <- m_ODF_first[METC & INJ, i]
# Month 2+
a_UP[METC & INJ, MET & INJ, i] <- p_METC_MET_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
a_UP[METC & INJ, BUP & INJ, i] <- p_METC_BUP_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
a_UP[METC & INJ, BUPC & INJ, i] <- p_METC_BUPC_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
a_UP[METC & INJ, ABS & INJ, i] <- p_METC_ABS_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
a_UP[METC & INJ, REL & INJ, i] <- p_METC_REL_INJ #* (1 - m_ODN[METC & INJ, i] - m_ODF[METC & INJ, i])
#a_UP[METC & INJ, ODN & INJ, i] <- m_ODN[METC & INJ, i]
#a_UP[METC & INJ, ODF & INJ, i] <- m_ODF[METC & INJ, i]
# From ABS
# First month
a_UP_first[ABS & INJ, REL & INJ, i] <- p_ABS_REL_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
a_UP_first[ABS & INJ, MET & INJ, i] <- p_ABS_MET_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
a_UP_first[ABS & INJ, METC & INJ, i] <- p_ABS_METC_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
a_UP_first[ABS & INJ, BUP & INJ, i] <- p_ABS_BUP_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
a_UP_first[ABS & INJ, BUPC & INJ, i] <- p_ABS_BUPC_INJ #* (1 - m_ODN_first[ABS & INJ, i] - m_ODF_first[ABS & INJ, i])
#a_UP_first[ABS & INJ, ODN & INJ, i] <- m_ODN_first[ABS & INJ, i]
#a_UP_first[ABS & INJ, ODF & INJ, i] <- m_ODF_first[ABS & INJ, i]
# Month 2+
a_UP[ABS & INJ, REL & INJ, i] <- p_ABS_REL_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
a_UP[ABS & INJ, MET & INJ, i] <- p_ABS_MET_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
a_UP[ABS & INJ, METC & INJ, i] <- p_ABS_METC_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
a_UP[ABS & INJ, BUP & INJ, i] <- p_ABS_BUP_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
a_UP[ABS & INJ, BUPC & INJ, i] <- p_ABS_BUPC_INJ #* (1 - m_ODN[ABS & INJ, i] - m_ODF[ABS & INJ, i])
#a_UP[ABS & INJ, ODN & INJ, i] <- m_ODN[ABS & INJ, i]
#a_UP[ABS & INJ, ODF & INJ, i] <- m_ODF[ABS & INJ, i]
# From REL
# First month
a_UP_first[REL & INJ, MET & INJ, i] <- p_REL_MET_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
a_UP_first[REL & INJ, METC & INJ, i] <- p_REL_METC_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
a_UP_first[REL & INJ, BUP & INJ, i] <- p_REL_BUP_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
a_UP_first[REL & INJ, BUPC & INJ, i] <- p_REL_BUPC_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
a_UP_first[REL & INJ, ABS & INJ, i] <- p_REL_ABS_INJ #* (1 - m_ODN_first[REL & INJ, i] - m_ODF_first[REL & INJ, i])
#a_UP_first[REL & INJ, ODN & INJ, i] <- m_ODN_first[REL & INJ, i]
#a_UP_first[REL & INJ, ODF & INJ, i] <- m_ODF_first[REL & INJ, i]
# Month 2+
a_UP[REL & INJ, MET & INJ, i] <- p_REL_MET_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
a_UP[REL & INJ, METC & INJ, i] <- p_REL_METC_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
a_UP[REL & INJ, BUP & INJ, i] <- p_REL_BUP_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
a_UP[REL & INJ, BUPC & INJ, i] <- p_REL_BUPC_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
a_UP[REL & INJ, ABS & INJ, i] <- p_REL_ABS_INJ #* (1 - m_ODN[REL & INJ, i] - m_ODF[REL & INJ, i])
#a_UP[REL & INJ, ODN & INJ, i] <- m_ODN[REL & INJ, i]
#a_UP[REL & INJ, ODF & INJ, i] <- m_ODF[REL & INJ, i]
# From OD (first month same)
a_UP[ODN & INJ, MET & INJ, i] <- a_UP_first[ODN & INJ, MET & INJ, i] <- p_ODN_MET_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, METC & INJ, i] <- a_UP_first[ODN & INJ, METC & INJ, i] <- p_ODN_METC_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, BUP & INJ, i] <- a_UP_first[ODN & INJ, BUP & INJ, i] <- p_ODN_BUP_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, BUPC & INJ, i] <- a_UP_first[ODN & INJ, BUPC & INJ, i] <- p_ODN_BUPC_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, ABS & INJ, i] <- a_UP_first[ODN & INJ, ABS & INJ, i] <- p_ODN_ABS_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
a_UP[ODN & INJ, REL & INJ, i] <- a_UP_first[ODN & INJ, REL & INJ, i] <- p_ODN_REL_INJ #* (1 - m_ODN[ODN & INJ, i] - m_ODF[ODN & INJ, i])
#a_UP[ODN & INJ, ODF & INJ, i] <- m_ODF[ODN & INJ, i]
}
if(checks){
# Time dependent state-exit probabilities (from weibull estimates)
write.csv(a_UP_first[, , 1],"checks/UP/a_UP_first_1.csv", row.names = TRUE)
write.csv(a_UP_first[, , 2],"checks/UP/a_UP_first_2.csv", row.names = TRUE)
write.csv(a_UP_first[, , 3],"checks/UP/a_UP_first_3.csv", row.names = TRUE)
write.csv(a_UP[, , 1],"checks/UP/a_UP_1.csv", row.names = TRUE)
write.csv(a_UP[, , 2],"checks/UP/a_UP_2.csv", row.names = TRUE)
write.csv(a_UP[, , 3],"checks/UP/a_UP_3.csv", row.names = TRUE)
} else{}
#### Create full time-dependent transition array ####
# Empty 3-D array
a_TDP_1 <- a_TDP_2 <- a_TDP_3 <- array(0, dim = c(n_states, n_states, n_t),
dimnames = list(v_n_states, v_n_states, 1:n_t))
# Add transitions conditional on state-exit (m_leave = 1 - remain)
# Three transition arrays to account for model-time-varying overdose (2018, 2019, 2020+)
# Modified transitions for first month (state-time)
for (i in 1){
a_TDP_1[, , i] <- a_UP_first[, , 1] * m_leave_1[, i]
a_TDP_2[, , i] <- a_UP_first[, , 2] * m_leave_2[, i]
a_TDP_3[, , i] <- a_UP_first[, , 3] * m_leave_3[, i]
}
## All transitions 2+ months
for (i in 2:n_t){
#a_TDP[, , i] <- m_UP * m_leave[, i]
a_TDP_1[, , i] <- a_UP[, , 1] * m_leave_1[, i]
a_TDP_2[, , i] <- a_UP[, , 2] * m_leave_2[, i]
a_TDP_3[, , i] <- a_UP[, , 3] * m_leave_3[, i]
}
# Add time-dependent remain probabilities
for (i in 1:n_t){
# Non-injection
# Episode 1
# BUP
a_TDP_1[EP1 & BUP & NI, EP1 & BUP & NI, i] <- m_remain_1[EP1 & BUP & NI, i]
a_TDP_2[EP1 & BUP & NI, EP1 & BUP & NI, i] <- m_remain_2[EP1 & BUP & NI, i]
a_TDP_3[EP1 & BUP & NI, EP1 & BUP & NI, i] <- m_remain_3[EP1 & BUP & NI, i]
# BUPC
a_TDP_1[EP1 & BUPC & NI, EP1 & BUPC & NI, i] <- m_remain_1[EP1 & BUPC & NI, i]
a_TDP_2[EP1 & BUPC & NI, EP1 & BUPC & NI, i] <- m_remain_2[EP1 & BUPC & NI, i]
a_TDP_3[EP1 & BUPC & NI, EP1 & BUPC & NI, i] <- m_remain_3[EP1 & BUPC & NI, i]
# MET
a_TDP_1[EP1 & MET & NI, EP1 & MET & NI, i] <- m_remain_1[EP1 & MET & NI, i]
a_TDP_2[EP1 & MET & NI, EP1 & MET & NI, i] <- m_remain_2[EP1 & MET & NI, i]
a_TDP_3[EP1 & MET & NI, EP1 & MET & NI, i] <- m_remain_3[EP1 & MET & NI, i]
# METC
a_TDP_1[EP1 & METC & NI, EP1 & METC & NI, i] <- m_remain_1[EP1 & METC & NI, i]
a_TDP_2[EP1 & METC & NI, EP1 & METC & NI, i] <- m_remain_2[EP1 & METC & NI, i]
a_TDP_3[EP1 & METC & NI, EP1 & METC & NI, i] <- m_remain_3[EP1 & METC & NI, i]
# ABS
a_TDP_1[EP1 & ABS & NI, EP1 & ABS & NI, i] <- m_remain_1[EP1 & ABS & NI, i]
a_TDP_2[EP1 & ABS & NI, EP1 & ABS & NI, i] <- m_remain_2[EP1 & ABS & NI, i]
a_TDP_3[EP1 & ABS & NI, EP1 & ABS & NI, i] <- m_remain_3[EP1 & ABS & NI, i]
# REL
a_TDP_1[EP1 & REL & NI, EP1 & REL & NI, i] <- m_remain_1[EP1 & REL & NI, i]
a_TDP_2[EP1 & REL & NI, EP1 & REL & NI, i] <- m_remain_2[EP1 & REL & NI, i]
a_TDP_3[EP1 & REL & NI, EP1 & REL & NI, i] <- m_remain_3[EP1 & REL & NI, i]
# ODF
a_TDP_1[EP1 & ODF & NI, EP1 & ODF & NI, i] <- m_remain_1[EP1 & ODF & NI, i]
a_TDP_2[EP1 & ODF & NI, EP1 & ODF & NI, i] <- m_remain_2[EP1 & ODF & NI, i]
a_TDP_3[EP1 & ODF & NI, EP1 & ODF & NI, i] <- m_remain_3[EP1 & ODF & NI, i]
# Episode 2
# BUP
a_TDP_1[EP2 & BUP & NI, EP2 & BUP & NI, i] <- m_remain_1[EP2 & BUP & NI, i]
a_TDP_2[EP2 & BUP & NI, EP2 & BUP & NI, i] <- m_remain_2[EP2 & BUP & NI, i]
a_TDP_3[EP2 & BUP & NI, EP2 & BUP & NI, i] <- m_remain_3[EP2 & BUP & NI, i]
# BUPC
a_TDP_1[EP2 & BUPC & NI, EP2 & BUPC & NI, i] <- m_remain_1[EP2 & BUPC & NI, i]
a_TDP_2[EP2 & BUPC & NI, EP2 & BUPC & NI, i] <- m_remain_2[EP2 & BUPC & NI, i]
a_TDP_3[EP2 & BUPC & NI, EP2 & BUPC & NI, i] <- m_remain_3[EP2 & BUPC & NI, i]
# MET
a_TDP_1[EP2 & MET & NI, EP2 & MET & NI, i] <- m_remain_1[EP2 & MET & NI, i]
a_TDP_2[EP2 & MET & NI, EP2 & MET & NI, i] <- m_remain_2[EP2 & MET & NI, i]
a_TDP_3[EP2 & MET & NI, EP2 & MET & NI, i] <- m_remain_3[EP2 & MET & NI, i]
# METC
a_TDP_1[EP2 & METC & NI, EP2 & METC & NI, i] <- m_remain_1[EP2 & METC & NI, i]
a_TDP_2[EP2 & METC & NI, EP2 & METC & NI, i] <- m_remain_2[EP2 & METC & NI, i]
a_TDP_3[EP2 & METC & NI, EP2 & METC & NI, i] <- m_remain_3[EP2 & METC & NI, i]
# ABS
a_TDP_1[EP2 & ABS & NI, EP2 & ABS & NI, i] <- m_remain_1[EP2 & ABS & NI, i]
a_TDP_2[EP2 & ABS & NI, EP2 & ABS & NI, i] <- m_remain_2[EP2 & ABS & NI, i]
a_TDP_3[EP2 & ABS & NI, EP2 & ABS & NI, i] <- m_remain_3[EP2 & ABS & NI, i]
# REL
a_TDP_1[EP2 & REL & NI, EP2 & REL & NI, i] <- m_remain_1[EP2 & REL & NI, i]
a_TDP_2[EP2 & REL & NI, EP2 & REL & NI, i] <- m_remain_2[EP2 & REL & NI, i]
a_TDP_3[EP2 & REL & NI, EP2 & REL & NI, i] <- m_remain_3[EP2 & REL & NI, i]
# ODF
a_TDP_1[EP2 & ODF & NI, EP2 & ODF & NI, i] <- m_remain_1[EP2 & ODF & NI, i]
a_TDP_2[EP2 & ODF & NI, EP2 & ODF & NI, i] <- m_remain_2[EP2 & ODF & NI, i]
a_TDP_3[EP2 & ODF & NI, EP2 & ODF & NI, i] <- m_remain_3[EP2 & ODF & NI, i]
# Episode 3
# BUP
a_TDP_1[EP3 & BUP & NI, EP3 & BUP & NI, i] <- m_remain_1[EP3 & BUP & NI, i]
a_TDP_2[EP3 & BUP & NI, EP3 & BUP & NI, i] <- m_remain_2[EP3 & BUP & NI, i]
a_TDP_3[EP3 & BUP & NI, EP3 & BUP & NI, i] <- m_remain_3[EP3 & BUP & NI, i]
# BUPC
a_TDP_1[EP3 & BUPC & NI, EP3 & BUPC & NI, i] <- m_remain_1[EP3 & BUPC & NI, i]
a_TDP_2[EP3 & BUPC & NI, EP3 & BUPC & NI, i] <- m_remain_2[EP3 & BUPC & NI, i]
a_TDP_3[EP3 & BUPC & NI, EP3 & BUPC & NI, i] <- m_remain_3[EP3 & BUPC & NI, i]
# MET
a_TDP_1[EP3 & MET & NI, EP3 & MET & NI, i] <- m_remain_1[EP3 & MET & NI, i]
a_TDP_2[EP3 & MET & NI, EP3 & MET & NI, i] <- m_remain_2[EP3 & MET & NI, i]
a_TDP_3[EP3 & MET & NI, EP3 & MET & NI, i] <- m_remain_3[EP3 & MET & NI, i]
# METC
a_TDP_1[EP3 & METC & NI, EP3 & METC & NI, i] <- m_remain_1[EP3 & METC & NI, i]
a_TDP_2[EP3 & METC & NI, EP3 & METC & NI, i] <- m_remain_2[EP3 & METC & NI, i]
a_TDP_3[EP3 & METC & NI, EP3 & METC & NI, i] <- m_remain_3[EP3 & METC & NI, i]
# ABS
a_TDP_1[EP3 & ABS & NI, EP3 & ABS & NI, i] <- m_remain_1[EP3 & ABS & NI, i]
a_TDP_2[EP3 & ABS & NI, EP3 & ABS & NI, i] <- m_remain_2[EP3 & ABS & NI, i]
a_TDP_3[EP3 & ABS & NI, EP3 & ABS & NI, i] <- m_remain_3[EP3 & ABS & NI, i]
# REL
a_TDP_1[EP3 & REL & NI, EP3 & REL & NI, i] <- m_remain_1[EP3 & REL & NI, i]
a_TDP_2[EP3 & REL & NI, EP3 & REL & NI, i] <- m_remain_2[EP3 & REL & NI, i]
a_TDP_3[EP3 & REL & NI, EP3 & REL & NI, i] <- m_remain_3[EP3 & REL & NI, i]
# ODF
a_TDP_1[EP3 & ODF & NI, EP3 & ODF & NI, i] <- m_remain_1[EP3 & ODF & NI, i]
a_TDP_2[EP3 & ODF & NI, EP3 & ODF & NI, i] <- m_remain_2[EP3 & ODF & NI, i]
a_TDP_3[EP3 & ODF & NI, EP3 & ODF & NI, i] <- m_remain_3[EP3 & ODF & NI, i]
# Injection
# Episode 1
# BUP
a_TDP_1[EP1 & BUP & INJ, EP1 & BUP & INJ, i] <- m_remain_1[EP1 & BUP & INJ, i]
a_TDP_2[EP1 & BUP & INJ, EP1 & BUP & INJ, i] <- m_remain_2[EP1 & BUP & INJ, i]
a_TDP_3[EP1 & BUP & INJ, EP1 & BUP & INJ, i] <- m_remain_3[EP1 & BUP & INJ, i]
# BUPC
a_TDP_1[EP1 & BUPC & INJ, EP1 & BUPC & INJ, i] <- m_remain_1[EP1 & BUPC & INJ, i]
a_TDP_2[EP1 & BUPC & INJ, EP1 & BUPC & INJ, i] <- m_remain_2[EP1 & BUPC & INJ, i]
a_TDP_3[EP1 & BUPC & INJ, EP1 & BUPC & INJ, i] <- m_remain_3[EP1 & BUPC & INJ, i]
# MET
a_TDP_1[EP1 & MET & INJ, EP1 & MET & INJ, i] <- m_remain_1[EP1 & MET & INJ, i]
a_TDP_2[EP1 & MET & INJ, EP1 & MET & INJ, i] <- m_remain_2[EP1 & MET & INJ, i]
a_TDP_3[EP1 & MET & INJ, EP1 & MET & INJ, i] <- m_remain_3[EP1 & MET & INJ, i]
# METC
a_TDP_1[EP1 & METC & INJ, EP1 & METC & INJ, i] <- m_remain_1[EP1 & METC & INJ, i]
a_TDP_2[EP1 & METC & INJ, EP1 & METC & INJ, i] <- m_remain_2[EP1 & METC & INJ, i]
a_TDP_3[EP1 & METC & INJ, EP1 & METC & INJ, i] <- m_remain_3[EP1 & METC & INJ, i]
# ABS
a_TDP_1[EP1 & ABS & INJ, EP1 & ABS & INJ, i] <- m_remain_1[EP1 & ABS & INJ, i]
a_TDP_2[EP1 & ABS & INJ, EP1 & ABS & INJ, i] <- m_remain_2[EP1 & ABS & INJ, i]
a_TDP_3[EP1 & ABS & INJ, EP1 & ABS & INJ, i] <- m_remain_3[EP1 & ABS & INJ, i]
# REL
a_TDP_1[EP1 & REL & INJ, EP1 & REL & INJ, i] <- m_remain_1[EP1 & REL & INJ, i]
a_TDP_2[EP1 & REL & INJ, EP1 & REL & INJ, i] <- m_remain_2[EP1 & REL & INJ, i]
a_TDP_3[EP1 & REL & INJ, EP1 & REL & INJ, i] <- m_remain_3[EP1 & REL & INJ, i]
# ODF
a_TDP_1[EP1 & ODF & INJ, EP1 & ODF & INJ, i] <- m_remain_1[EP1 & ODF & INJ, i]
a_TDP_2[EP1 & ODF & INJ, EP1 & ODF & INJ, i] <- m_remain_2[EP1 & ODF & INJ, i]
a_TDP_3[EP1 & ODF & INJ, EP1 & ODF & INJ, i] <- m_remain_3[EP1 & ODF & INJ, i]
# Episode 2
# BUP
a_TDP_1[EP2 & BUP & INJ, EP2 & BUP & INJ, i] <- m_remain_1[EP2 & BUP & INJ, i]
a_TDP_2[EP2 & BUP & INJ, EP2 & BUP & INJ, i] <- m_remain_2[EP2 & BUP & INJ, i]
a_TDP_3[EP2 & BUP & INJ, EP2 & BUP & INJ, i] <- m_remain_3[EP2 & BUP & INJ, i]
# BUPC
a_TDP_1[EP2 & BUPC & INJ, EP2 & BUPC & INJ, i] <- m_remain_1[EP2 & BUPC & INJ, i]
a_TDP_2[EP2 & BUPC & INJ, EP2 & BUPC & INJ, i] <- m_remain_2[EP2 & BUPC & INJ, i]
a_TDP_3[EP2 & BUPC & INJ, EP2 & BUPC & INJ, i] <- m_remain_3[EP2 & BUPC & INJ, i]
# MET
a_TDP_1[EP2 & MET & INJ, EP2 & MET & INJ, i] <- m_remain_1[EP2 & MET & INJ, i]
a_TDP_2[EP2 & MET & INJ, EP2 & MET & INJ, i] <- m_remain_2[EP2 & MET & INJ, i]
a_TDP_3[EP2 & MET & INJ, EP2 & MET & INJ, i] <- m_remain_3[EP2 & MET & INJ, i]
# METC
a_TDP_1[EP2 & METC & INJ, EP2 & METC & INJ, i] <- m_remain_1[EP2 & METC & INJ, i]
a_TDP_2[EP2 & METC & INJ, EP2 & METC & INJ, i] <- m_remain_2[EP2 & METC & INJ, i]
a_TDP_3[EP2 & METC & INJ, EP2 & METC & INJ, i] <- m_remain_3[EP2 & METC & INJ, i]
# ABS
a_TDP_1[EP2 & ABS & INJ, EP2 & ABS & INJ, i] <- m_remain_1[EP2 & ABS & INJ, i]
a_TDP_2[EP2 & ABS & INJ, EP2 & ABS & INJ, i] <- m_remain_2[EP2 & ABS & INJ, i]
a_TDP_3[EP2 & ABS & INJ, EP2 & ABS & INJ, i] <- m_remain_3[EP2 & ABS & INJ, i]
# REL
a_TDP_1[EP2 & REL & INJ, EP2 & REL & INJ, i] <- m_remain_1[EP2 & REL & INJ, i]
a_TDP_2[EP2 & REL & INJ, EP2 & REL & INJ, i] <- m_remain_2[EP2 & REL & INJ, i]
a_TDP_3[EP2 & REL & INJ, EP2 & REL & INJ, i] <- m_remain_3[EP2 & REL & INJ, i]
# ODF
a_TDP_1[EP2 & ODF & INJ, EP2 & ODF & INJ, i] <- m_remain_1[EP2 & ODF & INJ, i]
a_TDP_2[EP2 & ODF & INJ, EP2 & ODF & INJ, i] <- m_remain_2[EP2 & ODF & INJ, i]
a_TDP_3[EP2 & ODF & INJ, EP2 & ODF & INJ, i] <- m_remain_3[EP2 & ODF & INJ, i]
# Episode 3
# BUP
a_TDP_1[EP3 & BUP & INJ, EP3 & BUP & INJ, i] <- m_remain_1[EP3 & BUP & INJ, i]
a_TDP_2[EP3 & BUP & INJ, EP3 & BUP & INJ, i] <- m_remain_2[EP3 & BUP & INJ, i]
a_TDP_3[EP3 & BUP & INJ, EP3 & BUP & INJ, i] <- m_remain_3[EP3 & BUP & INJ, i]
# BUPC
a_TDP_1[EP3 & BUPC & INJ, EP3 & BUPC & INJ, i] <- m_remain_1[EP3 & BUPC & INJ, i]
a_TDP_2[EP3 & BUPC & INJ, EP3 & BUPC & INJ, i] <- m_remain_2[EP3 & BUPC & INJ, i]
a_TDP_3[EP3 & BUPC & INJ, EP3 & BUPC & INJ, i] <- m_remain_3[EP3 & BUPC & INJ, i]
# MET
a_TDP_1[EP3 & MET & INJ, EP3 & MET & INJ, i] <- m_remain_1[EP3 & MET & INJ, i]
a_TDP_2[EP3 & MET & INJ, EP3 & MET & INJ, i] <- m_remain_2[EP3 & MET & INJ, i]
a_TDP_3[EP3 & MET & INJ, EP3 & MET & INJ, i] <- m_remain_3[EP3 & MET & INJ, i]
# METC
a_TDP_1[EP3 & METC & INJ, EP3 & METC & INJ, i] <- m_remain_1[EP3 & METC & INJ, i]
a_TDP_2[EP3 & METC & INJ, EP3 & METC & INJ, i] <- m_remain_2[EP3 & METC & INJ, i]
a_TDP_3[EP3 & METC & INJ, EP3 & METC & INJ, i] <- m_remain_3[EP3 & METC & INJ, i]
# ABS
a_TDP_1[EP3 & ABS & INJ, EP3 & ABS & INJ, i] <- m_remain_1[EP3 & ABS & INJ, i]
a_TDP_2[EP3 & ABS & INJ, EP3 & ABS & INJ, i] <- m_remain_2[EP3 & ABS & INJ, i]
a_TDP_3[EP3 & ABS & INJ, EP3 & ABS & INJ, i] <- m_remain_3[EP3 & ABS & INJ, i]
# REL
a_TDP_1[EP3 & REL & INJ, EP3 & REL & INJ, i] <- m_remain_1[EP3 & REL & INJ, i]
a_TDP_2[EP3 & REL & INJ, EP3 & REL & INJ, i] <- m_remain_2[EP3 & REL & INJ, i]
a_TDP_3[EP3 & REL & INJ, EP3 & REL & INJ, i] <- m_remain_3[EP3 & REL & INJ, i]
# ODF
a_TDP_1[EP3 & ODF & INJ, EP3 & ODF & INJ, i] <- m_remain_1[EP3 & ODF & INJ, i]
a_TDP_2[EP3 & ODF & INJ, EP3 & ODF & INJ, i] <- m_remain_2[EP3 & ODF & INJ, i]
a_TDP_3[EP3 & ODF & INJ, EP3 & ODF & INJ, i] <- m_remain_3[EP3 & ODF & INJ, i]
}
if(checks){
# State transitions pre-overdose
# First month (state-time)
write.csv(a_TDP_1[, , 1], "checks/state transitions/a_TDP_pre_OD_2018.csv")
write.csv(a_TDP_2[, , 1], "checks/state transitions/a_TDP_pre_OD_2019.csv")
write.csv(a_TDP_3[, , 1], "checks/state transitions/a_TDP_pre_OD_2020.csv")
}
# Modify array for non-overdose prob
for (i in 1){
a_TDP_1[, , i] <- a_TDP_1[, , i] * m_non_OD_first[, 1]
a_TDP_2[, , i] <- a_TDP_2[, , i] * m_non_OD_first[, 2]
a_TDP_3[, , i] <- a_TDP_3[, , i] * m_non_OD_first[, 3]
}
## All transitions 2+ months
for (i in 2:n_t){
#a_TDP[, , i] <- m_UP * m_leave[, i]
a_TDP_1[, , i] <- a_TDP_1[, , i] * m_non_OD[, 1]
a_TDP_2[, , i] <- a_TDP_2[, , i] * m_non_OD[, 2]
a_TDP_3[, , i] <- a_TDP_3[, , i] * m_non_OD[, 3]
}
# Add overdose probabilities
for (i in 1){
a_TDP_1[NI, ODN & NI, i] <- m_ODN_first[NI, 1]
a_TDP_2[NI, ODN & NI, i] <- m_ODN_first[NI, 2]
a_TDP_3[NI, ODN & NI, i] <- m_ODN_first[NI, 3]
a_TDP_1[INJ, ODN & INJ, i] <- m_ODN_first[INJ, 1]
a_TDP_2[INJ, ODN & INJ, i] <- m_ODN_first[INJ, 2]
a_TDP_3[INJ, ODN & INJ, i] <- m_ODN_first[INJ, 3]
a_TDP_1[NI, ODF & NI, i] <- m_ODF_first[NI, 1]
a_TDP_2[NI, ODF & NI, i] <- m_ODF_first[NI, 2]
a_TDP_3[NI, ODF & NI, i] <- m_ODF_first[NI, 3]
a_TDP_1[INJ, ODF & INJ, i] <- m_ODF_first[INJ, 1]
a_TDP_2[INJ, ODF & INJ, i] <- m_ODF_first[INJ, 2]
a_TDP_3[INJ, ODF & INJ, i] <- m_ODF_first[INJ, 3]
a_TDP_1[ODF, ODF, i] <- a_TDP_2[ODF, ODF, i] <- a_TDP_3[ODF, ODF, i] <- 1
}
## All transitions 2+ months
for (i in 2:n_t){
#a_TDP[, , i] <- m_UP * m_leave[, i]
a_TDP_1[NI, ODN & NI, i] <- m_ODN[NI, 1]
a_TDP_2[NI, ODN & NI, i] <- m_ODN[NI, 2]
a_TDP_3[NI, ODN & NI, i] <- m_ODN[NI, 3]
a_TDP_1[INJ, ODN & INJ, i] <- m_ODN[INJ, 1]
a_TDP_2[INJ, ODN & INJ, i] <- m_ODN[INJ, 2]
a_TDP_3[INJ, ODN & INJ, i] <- m_ODN[INJ, 3]
a_TDP_1[NI, ODF & NI, i] <- m_ODF[NI, 1]
a_TDP_2[NI, ODF & NI, i] <- m_ODF[NI, 2]
a_TDP_3[NI, ODF & NI, i] <- m_ODF[NI, 3]
a_TDP_1[INJ, ODF & INJ, i] <- m_ODF[INJ, 1]
a_TDP_2[INJ, ODF & INJ, i] <- m_ODF[INJ, 2]
a_TDP_3[INJ, ODF & INJ, i] <- m_ODF[INJ, 3]
a_TDP_1[ODF, ODF, i] <- a_TDP_2[ODF, ODF, i] <- a_TDP_3[ODF, ODF, i] <- 1
}
if(checks){
# State transitions post-overdose
# First month (state-time)
write.csv(a_TDP_1[, , 1], "checks/state transitions/a_TDP_post_OD_2018.csv")
write.csv(a_TDP_2[, , 1], "checks/state transitions/a_TDP_post_OD_2019.csv")
write.csv(a_TDP_3[, , 1], "checks/state transitions/a_TDP_post_OD_2020.csv")
}
#### Seroconversion ####
# Apply seroconversion probability to re-weight NEG -> POS for to-states each time period
# Probabilities applied equally across POS/NEG initially, re-weight by sero prob
# Non-injection
# BUP
# From NEG
a_TDP_1[NEG & NI, BUP & NI & NEG, ] <- a_TDP_1[NEG & NI, BUP & NI & NEG, ] * (1 - p_HIV_BUP_NI - p_HCV_BUP_NI)
a_TDP_2[NEG & NI, BUP & NI & NEG, ] <- a_TDP_2[NEG & NI, BUP & NI & NEG, ] * (1 - p_HIV_BUP_NI - p_HCV_BUP_NI)
a_TDP_3[NEG & NI, BUP & NI & NEG, ] <- a_TDP_3[NEG & NI, BUP & NI & NEG, ] * (1 - p_HIV_BUP_NI - p_HCV_BUP_NI)
a_TDP_1[NEG & NI, BUP & NI & HIV, ] <- a_TDP_1[NEG & NI, BUP & NI & HIV, ] * p_HIV_BUP_NI
a_TDP_2[NEG & NI, BUP & NI & HIV, ] <- a_TDP_2[NEG & NI, BUP & NI & HIV, ] * p_HIV_BUP_NI
a_TDP_3[NEG & NI, BUP & NI & HIV, ] <- a_TDP_3[NEG & NI, BUP & NI & HIV, ] * p_HIV_BUP_NI
a_TDP_1[NEG & NI, BUP & NI & HCV, ] <- a_TDP_1[NEG & NI, BUP & NI & HCV, ] * p_HCV_BUP_NI
a_TDP_2[NEG & NI, BUP & NI & HCV, ] <- a_TDP_2[NEG & NI, BUP & NI & HCV, ] * p_HCV_BUP_NI
a_TDP_3[NEG & NI, BUP & NI & HCV, ] <- a_TDP_3[NEG & NI, BUP & NI & HCV, ] * p_HCV_BUP_NI
# From HIV
a_TDP_1[HIV & NI, BUP & NI & HIV, ] <- a_TDP_1[HIV & NI, BUP & NI & HIV, ] * (1 - p_HIV_HCV_BUP_NI)
a_TDP_2[HIV & NI, BUP & NI & HIV, ] <- a_TDP_2[HIV & NI, BUP & NI & HIV, ] * (1 - p_HIV_HCV_BUP_NI)
a_TDP_3[HIV & NI, BUP & NI & HIV, ] <- a_TDP_3[HIV & NI, BUP & NI & HIV, ] * (1 - p_HIV_HCV_BUP_NI)
a_TDP_1[HIV & NI, BUP & NI & COI, ] <- a_TDP_1[HIV & NI, BUP & NI & COI, ] * p_HIV_HCV_BUP_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, BUP & NI & COI, ] <- a_TDP_2[HIV & NI, BUP & NI & COI, ] * p_HIV_HCV_BUP_NI
a_TDP_3[HIV & NI, BUP & NI & COI, ] <- a_TDP_3[HIV & NI, BUP & NI & COI, ] * p_HIV_HCV_BUP_NI
# From HCV
a_TDP_1[HCV & NI, BUP & NI & HCV, ] <- a_TDP_1[HCV & NI, BUP & NI & HCV, ] * (1 - p_HCV_HIV_BUP_NI)
a_TDP_2[HCV & NI, BUP & NI & HCV, ] <- a_TDP_2[HCV & NI, BUP & NI & HCV, ] * (1 - p_HCV_HIV_BUP_NI)
a_TDP_3[HCV & NI, BUP & NI & HCV, ] <- a_TDP_3[HCV & NI, BUP & NI & HCV, ] * (1 - p_HCV_HIV_BUP_NI)
a_TDP_1[HCV & NI, BUP & NI & COI, ] <- a_TDP_1[HCV & NI, BUP & NI & COI, ] * p_HCV_HIV_BUP_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, BUP & NI & COI, ] <- a_TDP_2[HCV & NI, BUP & NI & COI, ] * p_HCV_HIV_BUP_NI
a_TDP_3[HCV & NI, BUP & NI & COI, ] <- a_TDP_3[HCV & NI, BUP & NI & COI, ] * p_HCV_HIV_BUP_NI
# BUPC
# From NEG
a_TDP_1[NEG & NI, BUPC & NI & NEG, ] <- a_TDP_1[NEG & NI, BUPC & NI & NEG, ] * (1 - p_HIV_BUPC_NI - p_HCV_BUPC_NI)
a_TDP_2[NEG & NI, BUPC & NI & NEG, ] <- a_TDP_2[NEG & NI, BUPC & NI & NEG, ] * (1 - p_HIV_BUPC_NI - p_HCV_BUPC_NI)
a_TDP_3[NEG & NI, BUPC & NI & NEG, ] <- a_TDP_3[NEG & NI, BUPC & NI & NEG, ] * (1 - p_HIV_BUPC_NI - p_HCV_BUPC_NI)
a_TDP_1[NEG & NI, BUPC & NI & HIV, ] <- a_TDP_1[NEG & NI, BUPC & NI & HIV, ] * p_HIV_BUPC_NI
a_TDP_2[NEG & NI, BUPC & NI & HIV, ] <- a_TDP_2[NEG & NI, BUPC & NI & HIV, ] * p_HIV_BUPC_NI
a_TDP_3[NEG & NI, BUPC & NI & HIV, ] <- a_TDP_3[NEG & NI, BUPC & NI & HIV, ] * p_HIV_BUPC_NI
a_TDP_1[NEG & NI, BUPC & NI & HCV, ] <- a_TDP_1[NEG & NI, BUPC & NI & HCV, ] * p_HCV_BUPC_NI
a_TDP_2[NEG & NI, BUPC & NI & HCV, ] <- a_TDP_2[NEG & NI, BUPC & NI & HCV, ] * p_HCV_BUPC_NI
a_TDP_3[NEG & NI, BUPC & NI & HCV, ] <- a_TDP_3[NEG & NI, BUPC & NI & HCV, ] * p_HCV_BUPC_NI
# From HIV
a_TDP_1[HIV & NI, BUPC & NI & HIV, ] <- a_TDP_1[HIV & NI, BUPC & NI & HIV, ] * (1 - p_HIV_HCV_BUPC_NI)
a_TDP_2[HIV & NI, BUPC & NI & HIV, ] <- a_TDP_2[HIV & NI, BUPC & NI & HIV, ] * (1 - p_HIV_HCV_BUPC_NI)
a_TDP_3[HIV & NI, BUPC & NI & HIV, ] <- a_TDP_3[HIV & NI, BUPC & NI & HIV, ] * (1 - p_HIV_HCV_BUPC_NI)
a_TDP_1[HIV & NI, BUPC & NI & COI, ] <- a_TDP_1[HIV & NI, BUPC & NI & COI, ] * p_HIV_HCV_BUPC_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, BUPC & NI & COI, ] <- a_TDP_2[HIV & NI, BUPC & NI & COI, ] * p_HIV_HCV_BUPC_NI
a_TDP_3[HIV & NI, BUPC & NI & COI, ] <- a_TDP_3[HIV & NI, BUPC & NI & COI, ] * p_HIV_HCV_BUPC_NI
# From HCV
a_TDP_1[HCV & NI, BUPC & NI & HCV, ] <- a_TDP_1[HCV & NI, BUPC & NI & HCV, ] * (1 - p_HCV_HIV_BUPC_NI)
a_TDP_2[HCV & NI, BUPC & NI & HCV, ] <- a_TDP_2[HCV & NI, BUPC & NI & HCV, ] * (1 - p_HCV_HIV_BUPC_NI)
a_TDP_3[HCV & NI, BUPC & NI & HCV, ] <- a_TDP_3[HCV & NI, BUPC & NI & HCV, ] * (1 - p_HCV_HIV_BUPC_NI)
a_TDP_1[HCV & NI, BUPC & NI & COI, ] <- a_TDP_1[HCV & NI, BUPC & NI & COI, ] * p_HCV_HIV_BUPC_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, BUPC & NI & COI, ] <- a_TDP_2[HCV & NI, BUPC & NI & COI, ] * p_HCV_HIV_BUPC_NI
a_TDP_3[HCV & NI, BUPC & NI & COI, ] <- a_TDP_3[HCV & NI, BUPC & NI & COI, ] * p_HCV_HIV_BUPC_NI
# MET
# From NEG
a_TDP_1[NEG & NI, MET & NI & NEG, ] <- a_TDP_1[NEG & NI, MET & NI & NEG, ] * (1 - p_HIV_MET_NI - p_HCV_MET_NI)
a_TDP_2[NEG & NI, MET & NI & NEG, ] <- a_TDP_2[NEG & NI, MET & NI & NEG, ] * (1 - p_HIV_MET_NI - p_HCV_MET_NI)
a_TDP_3[NEG & NI, MET & NI & NEG, ] <- a_TDP_3[NEG & NI, MET & NI & NEG, ] * (1 - p_HIV_MET_NI - p_HCV_MET_NI)
a_TDP_1[NEG & NI, MET & NI & HIV, ] <- a_TDP_1[NEG & NI, MET & NI & HIV, ] * p_HIV_MET_NI
a_TDP_2[NEG & NI, MET & NI & HIV, ] <- a_TDP_2[NEG & NI, MET & NI & HIV, ] * p_HIV_MET_NI
a_TDP_3[NEG & NI, MET & NI & HIV, ] <- a_TDP_3[NEG & NI, MET & NI & HIV, ] * p_HIV_MET_NI
a_TDP_1[NEG & NI, MET & NI & HCV, ] <- a_TDP_1[NEG & NI, MET & NI & HCV, ] * p_HCV_MET_NI
a_TDP_2[NEG & NI, MET & NI & HCV, ] <- a_TDP_2[NEG & NI, MET & NI & HCV, ] * p_HCV_MET_NI
a_TDP_3[NEG & NI, MET & NI & HCV, ] <- a_TDP_3[NEG & NI, MET & NI & HCV, ] * p_HCV_MET_NI
# From HIV
a_TDP_1[HIV & NI, MET & NI & HIV, ] <- a_TDP_1[HIV & NI, MET & NI & HIV, ] * (1 - p_HIV_HCV_MET_NI)
a_TDP_2[HIV & NI, MET & NI & HIV, ] <- a_TDP_2[HIV & NI, MET & NI & HIV, ] * (1 - p_HIV_HCV_MET_NI)
a_TDP_3[HIV & NI, MET & NI & HIV, ] <- a_TDP_3[HIV & NI, MET & NI & HIV, ] * (1 - p_HIV_HCV_MET_NI)
a_TDP_1[HIV & NI, MET & NI & COI, ] <- a_TDP_1[HIV & NI, MET & NI & COI, ] * p_HIV_HCV_MET_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, MET & NI & COI, ] <- a_TDP_2[HIV & NI, MET & NI & COI, ] * p_HIV_HCV_MET_NI
a_TDP_3[HIV & NI, MET & NI & COI, ] <- a_TDP_3[HIV & NI, MET & NI & COI, ] * p_HIV_HCV_MET_NI
# From HCV
a_TDP_1[HCV & NI, MET & NI & HCV, ] <- a_TDP_1[HCV & NI, MET & NI & HCV, ] * (1 - p_HCV_HIV_MET_NI)
a_TDP_2[HCV & NI, MET & NI & HCV, ] <- a_TDP_2[HCV & NI, MET & NI & HCV, ] * (1 - p_HCV_HIV_MET_NI)
a_TDP_3[HCV & NI, MET & NI & HCV, ] <- a_TDP_3[HCV & NI, MET & NI & HCV, ] * (1 - p_HCV_HIV_MET_NI)
a_TDP_1[HCV & NI, MET & NI & COI, ] <- a_TDP_1[HCV & NI, MET & NI & COI, ] * p_HCV_HIV_MET_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, MET & NI & COI, ] <- a_TDP_2[HCV & NI, MET & NI & COI, ] * p_HCV_HIV_MET_NI
a_TDP_3[HCV & NI, MET & NI & COI, ] <- a_TDP_3[HCV & NI, MET & NI & COI, ] * p_HCV_HIV_MET_NI
# METC
# From NEG
a_TDP_1[NEG & NI, METC & NI & NEG, ] <- a_TDP_1[NEG & NI, METC & NI & NEG, ] * (1 - p_HIV_METC_NI - p_HCV_METC_NI)
a_TDP_2[NEG & NI, METC & NI & NEG, ] <- a_TDP_2[NEG & NI, METC & NI & NEG, ] * (1 - p_HIV_METC_NI - p_HCV_METC_NI)
a_TDP_3[NEG & NI, METC & NI & NEG, ] <- a_TDP_3[NEG & NI, METC & NI & NEG, ] * (1 - p_HIV_METC_NI - p_HCV_METC_NI)
a_TDP_1[NEG & NI, METC & NI & HIV, ] <- a_TDP_1[NEG & NI, METC & NI & HIV, ] * p_HIV_METC_NI
a_TDP_2[NEG & NI, METC & NI & HIV, ] <- a_TDP_2[NEG & NI, METC & NI & HIV, ] * p_HIV_METC_NI
a_TDP_3[NEG & NI, METC & NI & HIV, ] <- a_TDP_3[NEG & NI, METC & NI & HIV, ] * p_HIV_METC_NI
a_TDP_1[NEG & NI, METC & NI & HCV, ] <- a_TDP_1[NEG & NI, METC & NI & HCV, ] * p_HCV_METC_NI
a_TDP_2[NEG & NI, METC & NI & HCV, ] <- a_TDP_2[NEG & NI, METC & NI & HCV, ] * p_HCV_METC_NI
a_TDP_3[NEG & NI, METC & NI & HCV, ] <- a_TDP_3[NEG & NI, METC & NI & HCV, ] * p_HCV_METC_NI
# From HIV
a_TDP_1[HIV & NI, METC & NI & HIV, ] <- a_TDP_1[HIV & NI, METC & NI & HIV, ] * (1 - p_HIV_HCV_METC_NI)
a_TDP_2[HIV & NI, METC & NI & HIV, ] <- a_TDP_2[HIV & NI, METC & NI & HIV, ] * (1 - p_HIV_HCV_METC_NI)
a_TDP_3[HIV & NI, METC & NI & HIV, ] <- a_TDP_3[HIV & NI, METC & NI & HIV, ] * (1 - p_HIV_HCV_METC_NI)
a_TDP_1[HIV & NI, METC & NI & COI, ] <- a_TDP_1[HIV & NI, METC & NI & COI, ] * p_HIV_HCV_METC_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, METC & NI & COI, ] <- a_TDP_2[HIV & NI, METC & NI & COI, ] * p_HIV_HCV_METC_NI
a_TDP_3[HIV & NI, METC & NI & COI, ] <- a_TDP_3[HIV & NI, METC & NI & COI, ] * p_HIV_HCV_METC_NI
# From HCV
a_TDP_1[HCV & NI, METC & NI & HCV, ] <- a_TDP_1[HCV & NI, METC & NI & HCV, ] * (1 - p_HCV_HIV_METC_NI)
a_TDP_2[HCV & NI, METC & NI & HCV, ] <- a_TDP_2[HCV & NI, METC & NI & HCV, ] * (1 - p_HCV_HIV_METC_NI)
a_TDP_3[HCV & NI, METC & NI & HCV, ] <- a_TDP_3[HCV & NI, METC & NI & HCV, ] * (1 - p_HCV_HIV_METC_NI)
a_TDP_1[HCV & NI, METC & NI & COI, ] <- a_TDP_1[HCV & NI, METC & NI & COI, ] * p_HCV_HIV_METC_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, METC & NI & COI, ] <- a_TDP_2[HCV & NI, METC & NI & COI, ] * p_HCV_HIV_METC_NI
a_TDP_3[HCV & NI, METC & NI & COI, ] <- a_TDP_3[HCV & NI, METC & NI & COI, ] * p_HCV_HIV_METC_NI
# REL
# From NEG
a_TDP_1[NEG & NI, REL & NI & NEG, ] <- a_TDP_1[NEG & NI, REL & NI & NEG, ] * (1 - p_HIV_REL_NI - p_HCV_REL_NI)
a_TDP_2[NEG & NI, REL & NI & NEG, ] <- a_TDP_2[NEG & NI, REL & NI & NEG, ] * (1 - p_HIV_REL_NI - p_HCV_REL_NI)
a_TDP_3[NEG & NI, REL & NI & NEG, ] <- a_TDP_3[NEG & NI, REL & NI & NEG, ] * (1 - p_HIV_REL_NI - p_HCV_REL_NI)
a_TDP_1[NEG & NI, REL & NI & HIV, ] <- a_TDP_1[NEG & NI, REL & NI & HIV, ] * p_HIV_REL_NI
a_TDP_2[NEG & NI, REL & NI & HIV, ] <- a_TDP_2[NEG & NI, REL & NI & HIV, ] * p_HIV_REL_NI
a_TDP_3[NEG & NI, REL & NI & HIV, ] <- a_TDP_3[NEG & NI, REL & NI & HIV, ] * p_HIV_REL_NI
a_TDP_1[NEG & NI, REL & NI & HCV, ] <- a_TDP_1[NEG & NI, REL & NI & HCV, ] * p_HCV_REL_NI
a_TDP_2[NEG & NI, REL & NI & HCV, ] <- a_TDP_2[NEG & NI, REL & NI & HCV, ] * p_HCV_REL_NI
a_TDP_3[NEG & NI, REL & NI & HCV, ] <- a_TDP_3[NEG & NI, REL & NI & HCV, ] * p_HCV_REL_NI
# From HIV
a_TDP_1[HIV & NI, REL & NI & HIV, ] <- a_TDP_1[HIV & NI, REL & NI & HIV, ] * (1 - p_HIV_HCV_REL_NI)
a_TDP_2[HIV & NI, REL & NI & HIV, ] <- a_TDP_2[HIV & NI, REL & NI & HIV, ] * (1 - p_HIV_HCV_REL_NI)
a_TDP_3[HIV & NI, REL & NI & HIV, ] <- a_TDP_3[HIV & NI, REL & NI & HIV, ] * (1 - p_HIV_HCV_REL_NI)
a_TDP_1[HIV & NI, REL & NI & COI, ] <- a_TDP_1[HIV & NI, REL & NI & COI, ] * p_HIV_HCV_REL_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, REL & NI & COI, ] <- a_TDP_2[HIV & NI, REL & NI & COI, ] * p_HIV_HCV_REL_NI
a_TDP_3[HIV & NI, REL & NI & COI, ] <- a_TDP_3[HIV & NI, REL & NI & COI, ] * p_HIV_HCV_REL_NI
# From HCV
a_TDP_1[HCV & NI, REL & NI & HCV, ] <- a_TDP_1[HCV & NI, REL & NI & HCV, ] * (1 - p_HCV_HIV_REL_NI)
a_TDP_2[HCV & NI, REL & NI & HCV, ] <- a_TDP_2[HCV & NI, REL & NI & HCV, ] * (1 - p_HCV_HIV_REL_NI)
a_TDP_3[HCV & NI, REL & NI & HCV, ] <- a_TDP_3[HCV & NI, REL & NI & HCV, ] * (1 - p_HCV_HIV_REL_NI)
a_TDP_1[HCV & NI, REL & NI & COI, ] <- a_TDP_1[HCV & NI, REL & NI & COI, ] * p_HCV_HIV_REL_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, REL & NI & COI, ] <- a_TDP_2[HCV & NI, REL & NI & COI, ] * p_HCV_HIV_REL_NI
a_TDP_3[HCV & NI, REL & NI & COI, ] <- a_TDP_3[HCV & NI, REL & NI & COI, ] * p_HCV_HIV_REL_NI
# ODN
# From NEG
a_TDP_1[NEG & NI, ODN & NI & NEG, ] <- a_TDP_1[NEG & NI, ODN & NI & NEG, ] * (1 - p_HIV_ODN_NI - p_HCV_ODN_NI)
a_TDP_2[NEG & NI, ODN & NI & NEG, ] <- a_TDP_2[NEG & NI, ODN & NI & NEG, ] * (1 - p_HIV_ODN_NI - p_HCV_ODN_NI)
a_TDP_3[NEG & NI, ODN & NI & NEG, ] <- a_TDP_3[NEG & NI, ODN & NI & NEG, ] * (1 - p_HIV_ODN_NI - p_HCV_ODN_NI)
a_TDP_1[NEG & NI, ODN & NI & HIV, ] <- a_TDP_1[NEG & NI, ODN & NI & HIV, ] * p_HIV_ODN_NI
a_TDP_2[NEG & NI, ODN & NI & HIV, ] <- a_TDP_2[NEG & NI, ODN & NI & HIV, ] * p_HIV_ODN_NI
a_TDP_3[NEG & NI, ODN & NI & HIV, ] <- a_TDP_3[NEG & NI, ODN & NI & HIV, ] * p_HIV_ODN_NI
a_TDP_1[NEG & NI, ODN & NI & HCV, ] <- a_TDP_1[NEG & NI, ODN & NI & HCV, ] * p_HCV_ODN_NI
a_TDP_2[NEG & NI, ODN & NI & HCV, ] <- a_TDP_2[NEG & NI, ODN & NI & HCV, ] * p_HCV_ODN_NI
a_TDP_3[NEG & NI, ODN & NI & HCV, ] <- a_TDP_3[NEG & NI, ODN & NI & HCV, ] * p_HCV_ODN_NI
# From HIV
a_TDP_1[HIV & NI, ODN & NI & HIV, ] <- a_TDP_1[HIV & NI, ODN & NI & HIV, ] * (1 - p_HIV_HCV_ODN_NI)
a_TDP_2[HIV & NI, ODN & NI & HIV, ] <- a_TDP_2[HIV & NI, ODN & NI & HIV, ] * (1 - p_HIV_HCV_ODN_NI)
a_TDP_3[HIV & NI, ODN & NI & HIV, ] <- a_TDP_3[HIV & NI, ODN & NI & HIV, ] * (1 - p_HIV_HCV_ODN_NI)
a_TDP_1[HIV & NI, ODN & NI & COI, ] <- a_TDP_1[HIV & NI, ODN & NI & COI, ] * p_HIV_HCV_ODN_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, ODN & NI & COI, ] <- a_TDP_2[HIV & NI, ODN & NI & COI, ] * p_HIV_HCV_ODN_NI
a_TDP_3[HIV & NI, ODN & NI & COI, ] <- a_TDP_3[HIV & NI, ODN & NI & COI, ] * p_HIV_HCV_ODN_NI
# From HCV
a_TDP_1[HCV & NI, ODN & NI & HCV, ] <- a_TDP_1[HCV & NI, ODN & NI & HCV, ] * (1 - p_HCV_HIV_ODN_NI)
a_TDP_2[HCV & NI, ODN & NI & HCV, ] <- a_TDP_2[HCV & NI, ODN & NI & HCV, ] * (1 - p_HCV_HIV_ODN_NI)
a_TDP_3[HCV & NI, ODN & NI & HCV, ] <- a_TDP_3[HCV & NI, ODN & NI & HCV, ] * (1 - p_HCV_HIV_ODN_NI)
a_TDP_1[HCV & NI, ODN & NI & COI, ] <- a_TDP_1[HCV & NI, ODN & NI & COI, ] * p_HCV_HIV_ODN_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, ODN & NI & COI, ] <- a_TDP_2[HCV & NI, ODN & NI & COI, ] * p_HCV_HIV_ODN_NI
a_TDP_3[HCV & NI, ODN & NI & COI, ] <- a_TDP_3[HCV & NI, ODN & NI & COI, ] * p_HCV_HIV_ODN_NI
# ODF
# From NEG
a_TDP_1[NEG & NI, ODF & NI & NEG, ] <- a_TDP_1[NEG & NI, ODF & NI & NEG, ] * 1
a_TDP_2[NEG & NI, ODF & NI & NEG, ] <- a_TDP_2[NEG & NI, ODF & NI & NEG, ] * 1
a_TDP_3[NEG & NI, ODF & NI & NEG, ] <- a_TDP_3[NEG & NI, ODF & NI & NEG, ] * 1
a_TDP_1[NEG & NI, ODF & NI & HIV, ] <- a_TDP_1[NEG & NI, ODF & NI & HIV, ] * 0
a_TDP_2[NEG & NI, ODF & NI & HIV, ] <- a_TDP_2[NEG & NI, ODF & NI & HIV, ] * 0
a_TDP_3[NEG & NI, ODF & NI & HIV, ] <- a_TDP_3[NEG & NI, ODF & NI & HIV, ] * 0
a_TDP_1[NEG & NI, ODF & NI & HCV, ] <- a_TDP_1[NEG & NI, ODF & NI & HCV, ] * 0
a_TDP_2[NEG & NI, ODF & NI & HCV, ] <- a_TDP_2[NEG & NI, ODF & NI & HCV, ] * 0
a_TDP_3[NEG & NI, ODF & NI & HCV, ] <- a_TDP_3[NEG & NI, ODF & NI & HCV, ] * 0
# From HIV
a_TDP_1[HIV & NI, ODF & NI & HIV, ] <- a_TDP_1[HIV & NI, ODF & NI & HIV, ] * 1
a_TDP_2[HIV & NI, ODF & NI & HIV, ] <- a_TDP_2[HIV & NI, ODF & NI & HIV, ] * 1
a_TDP_3[HIV & NI, ODF & NI & HIV, ] <- a_TDP_3[HIV & NI, ODF & NI & HIV, ] * 1
a_TDP_1[HIV & NI, ODF & NI & COI, ] <- a_TDP_1[HIV & NI, ODF & NI & COI, ] * 0
a_TDP_2[HIV & NI, ODF & NI & COI, ] <- a_TDP_2[HIV & NI, ODF & NI & COI, ] * 0
a_TDP_3[HIV & NI, ODF & NI & COI, ] <- a_TDP_3[HIV & NI, ODF & NI & COI, ] * 0
# From HCV
a_TDP_1[HCV & NI, ODF & NI & HCV, ] <- a_TDP_1[HCV & NI, ODF & NI & HCV, ] * 1
a_TDP_2[HCV & NI, ODF & NI & HCV, ] <- a_TDP_2[HCV & NI, ODF & NI & HCV, ] * 1
a_TDP_3[HCV & NI, ODF & NI & HCV, ] <- a_TDP_3[HCV & NI, ODF & NI & HCV, ] * 1
a_TDP_1[HCV & NI, ODF & NI & COI, ] <- a_TDP_1[HCV & NI, ODF & NI & COI, ] * 0
a_TDP_2[HCV & NI, ODF & NI & COI, ] <- a_TDP_2[HCV & NI, ODF & NI & COI, ] * 0
a_TDP_3[HCV & NI, ODF & NI & COI, ] <- a_TDP_3[HCV & NI, ODF & NI & COI, ] * 0
# ABS
# From NEG
a_TDP_1[NEG & NI, ABS & NI & NEG, ] <- a_TDP_1[NEG & NI, ABS & NI & NEG, ] * (1 - p_HIV_ABS_NI - p_HCV_ABS_NI)
a_TDP_2[NEG & NI, ABS & NI & NEG, ] <- a_TDP_2[NEG & NI, ABS & NI & NEG, ] * (1 - p_HIV_ABS_NI - p_HCV_ABS_NI)
a_TDP_3[NEG & NI, ABS & NI & NEG, ] <- a_TDP_3[NEG & NI, ABS & NI & NEG, ] * (1 - p_HIV_ABS_NI - p_HCV_ABS_NI)
a_TDP_1[NEG & NI, ABS & NI & HIV, ] <- a_TDP_1[NEG & NI, ABS & NI & HIV, ] * p_HIV_ABS_NI
a_TDP_2[NEG & NI, ABS & NI & HIV, ] <- a_TDP_2[NEG & NI, ABS & NI & HIV, ] * p_HIV_ABS_NI
a_TDP_3[NEG & NI, ABS & NI & HIV, ] <- a_TDP_3[NEG & NI, ABS & NI & HIV, ] * p_HIV_ABS_NI
a_TDP_1[NEG & NI, ABS & NI & HCV, ] <- a_TDP_1[NEG & NI, ABS & NI & HCV, ] * p_HCV_ABS_NI
a_TDP_2[NEG & NI, ABS & NI & HCV, ] <- a_TDP_2[NEG & NI, ABS & NI & HCV, ] * p_HCV_ABS_NI
a_TDP_3[NEG & NI, ABS & NI & HCV, ] <- a_TDP_3[NEG & NI, ABS & NI & HCV, ] * p_HCV_ABS_NI
# From HIV
a_TDP_1[HIV & NI, ABS & NI & HIV, ] <- a_TDP_1[HIV & NI, ABS & NI & HIV, ] * (1 - p_HIV_HCV_ABS_NI)
a_TDP_2[HIV & NI, ABS & NI & HIV, ] <- a_TDP_2[HIV & NI, ABS & NI & HIV, ] * (1 - p_HIV_HCV_ABS_NI)
a_TDP_3[HIV & NI, ABS & NI & HIV, ] <- a_TDP_3[HIV & NI, ABS & NI & HIV, ] * (1 - p_HIV_HCV_ABS_NI)
a_TDP_1[HIV & NI, ABS & NI & COI, ] <- a_TDP_1[HIV & NI, ABS & NI & COI, ] * p_HIV_HCV_ABS_NI # Probability of HCV conditional on HIV
a_TDP_2[HIV & NI, ABS & NI & COI, ] <- a_TDP_2[HIV & NI, ABS & NI & COI, ] * p_HIV_HCV_ABS_NI
a_TDP_3[HIV & NI, ABS & NI & COI, ] <- a_TDP_3[HIV & NI, ABS & NI & COI, ] * p_HIV_HCV_ABS_NI
# From HCV
a_TDP_1[HCV & NI, ABS & NI & HCV, ] <- a_TDP_1[HCV & NI, ABS & NI & HCV, ] * (1 - p_HCV_HIV_ABS_NI)
a_TDP_2[HCV & NI, ABS & NI & HCV, ] <- a_TDP_2[HCV & NI, ABS & NI & HCV, ] * (1 - p_HCV_HIV_ABS_NI)
a_TDP_3[HCV & NI, ABS & NI & HCV, ] <- a_TDP_3[HCV & NI, ABS & NI & HCV, ] * (1 - p_HCV_HIV_ABS_NI)
a_TDP_1[HCV & NI, ABS & NI & COI, ] <- a_TDP_1[HCV & NI, ABS & NI & COI, ] * p_HCV_HIV_ABS_NI # Probability of HIV conditional on HCV
a_TDP_2[HCV & NI, ABS & NI & COI, ] <- a_TDP_2[HCV & NI, ABS & NI & COI, ] * p_HCV_HIV_ABS_NI
a_TDP_3[HCV & NI, ABS & NI & COI, ] <- a_TDP_3[HCV & NI, ABS & NI & COI, ] * p_HCV_HIV_ABS_NI
# Injection
# BUP
# From NEG
a_TDP_1[NEG & INJ, BUP & INJ & NEG, ] <- a_TDP_1[NEG & INJ, BUP & INJ & NEG, ] * (1 - p_HIV_BUP_INJ - p_HCV_BUP_INJ)
a_TDP_2[NEG & INJ, BUP & INJ & NEG, ] <- a_TDP_2[NEG & INJ, BUP & INJ & NEG, ] * (1 - p_HIV_BUP_INJ - p_HCV_BUP_INJ)
a_TDP_3[NEG & INJ, BUP & INJ & NEG, ] <- a_TDP_3[NEG & INJ, BUP & INJ & NEG, ] * (1 - p_HIV_BUP_INJ - p_HCV_BUP_INJ)
a_TDP_1[NEG & INJ, BUP & INJ & HIV, ] <- a_TDP_1[NEG & INJ, BUP & INJ & HIV, ] * p_HIV_BUP_INJ
a_TDP_2[NEG & INJ, BUP & INJ & HIV, ] <- a_TDP_2[NEG & INJ, BUP & INJ & HIV, ] * p_HIV_BUP_INJ
a_TDP_3[NEG & INJ, BUP & INJ & HIV, ] <- a_TDP_3[NEG & INJ, BUP & INJ & HIV, ] * p_HIV_BUP_INJ
a_TDP_1[NEG & INJ, BUP & INJ & HCV, ] <- a_TDP_1[NEG & INJ, BUP & INJ & HCV, ] * p_HCV_BUP_INJ
a_TDP_2[NEG & INJ, BUP & INJ & HCV, ] <- a_TDP_2[NEG & INJ, BUP & INJ & HCV, ] * p_HCV_BUP_INJ
a_TDP_3[NEG & INJ, BUP & INJ & HCV, ] <- a_TDP_3[NEG & INJ, BUP & INJ & HCV, ] * p_HCV_BUP_INJ
# From HIV
a_TDP_1[HIV & INJ, BUP & INJ & HIV, ] <- a_TDP_1[HIV & INJ, BUP & INJ & HIV, ] * (1 - p_HIV_HCV_BUP_INJ)
a_TDP_2[HIV & INJ, BUP & INJ & HIV, ] <- a_TDP_2[HIV & INJ, BUP & INJ & HIV, ] * (1 - p_HIV_HCV_BUP_INJ)
a_TDP_3[HIV & INJ, BUP & INJ & HIV, ] <- a_TDP_3[HIV & INJ, BUP & INJ & HIV, ] * (1 - p_HIV_HCV_BUP_INJ)
a_TDP_1[HIV & INJ, BUP & INJ & COI, ] <- a_TDP_1[HIV & INJ, BUP & INJ & COI, ] * p_HIV_HCV_BUP_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, BUP & INJ & COI, ] <- a_TDP_2[HIV & INJ, BUP & INJ & COI, ] * p_HIV_HCV_BUP_INJ
a_TDP_3[HIV & INJ, BUP & INJ & COI, ] <- a_TDP_3[HIV & INJ, BUP & INJ & COI, ] * p_HIV_HCV_BUP_INJ
# From HCV
a_TDP_1[HCV & INJ, BUP & INJ & HCV, ] <- a_TDP_1[HCV & INJ, BUP & INJ & HCV, ] * (1 - p_HCV_HIV_BUP_INJ)
a_TDP_2[HCV & INJ, BUP & INJ & HCV, ] <- a_TDP_2[HCV & INJ, BUP & INJ & HCV, ] * (1 - p_HCV_HIV_BUP_INJ)
a_TDP_3[HCV & INJ, BUP & INJ & HCV, ] <- a_TDP_3[HCV & INJ, BUP & INJ & HCV, ] * (1 - p_HCV_HIV_BUP_INJ)
a_TDP_1[HCV & INJ, BUP & INJ & COI, ] <- a_TDP_1[HCV & INJ, BUP & INJ & COI, ] * p_HCV_HIV_BUP_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, BUP & INJ & COI, ] <- a_TDP_2[HCV & INJ, BUP & INJ & COI, ] * p_HCV_HIV_BUP_INJ
a_TDP_3[HCV & INJ, BUP & INJ & COI, ] <- a_TDP_3[HCV & INJ, BUP & INJ & COI, ] * p_HCV_HIV_BUP_INJ
# BUPC
# From NEG
a_TDP_1[NEG & INJ, BUPC & INJ & NEG, ] <- a_TDP_1[NEG & INJ, BUPC & INJ & NEG, ] * (1 - p_HIV_BUPC_INJ - p_HCV_BUPC_INJ)
a_TDP_2[NEG & INJ, BUPC & INJ & NEG, ] <- a_TDP_2[NEG & INJ, BUPC & INJ & NEG, ] * (1 - p_HIV_BUPC_INJ - p_HCV_BUPC_INJ)
a_TDP_3[NEG & INJ, BUPC & INJ & NEG, ] <- a_TDP_3[NEG & INJ, BUPC & INJ & NEG, ] * (1 - p_HIV_BUPC_INJ - p_HCV_BUPC_INJ)
a_TDP_1[NEG & INJ, BUPC & INJ & HIV, ] <- a_TDP_1[NEG & INJ, BUPC & INJ & HIV, ] * p_HIV_BUPC_INJ
a_TDP_2[NEG & INJ, BUPC & INJ & HIV, ] <- a_TDP_2[NEG & INJ, BUPC & INJ & HIV, ] * p_HIV_BUPC_INJ
a_TDP_3[NEG & INJ, BUPC & INJ & HIV, ] <- a_TDP_3[NEG & INJ, BUPC & INJ & HIV, ] * p_HIV_BUPC_INJ
a_TDP_1[NEG & INJ, BUPC & INJ & HCV, ] <- a_TDP_1[NEG & INJ, BUPC & INJ & HCV, ] * p_HCV_BUPC_INJ
a_TDP_2[NEG & INJ, BUPC & INJ & HCV, ] <- a_TDP_2[NEG & INJ, BUPC & INJ & HCV, ] * p_HCV_BUPC_INJ
a_TDP_3[NEG & INJ, BUPC & INJ & HCV, ] <- a_TDP_3[NEG & INJ, BUPC & INJ & HCV, ] * p_HCV_BUPC_INJ
# From HIV
a_TDP_1[HIV & INJ, BUPC & INJ & HIV, ] <- a_TDP_1[HIV & INJ, BUPC & INJ & HIV, ] * (1 - p_HIV_HCV_BUPC_INJ)
a_TDP_2[HIV & INJ, BUPC & INJ & HIV, ] <- a_TDP_2[HIV & INJ, BUPC & INJ & HIV, ] * (1 - p_HIV_HCV_BUPC_INJ)
a_TDP_3[HIV & INJ, BUPC & INJ & HIV, ] <- a_TDP_3[HIV & INJ, BUPC & INJ & HIV, ] * (1 - p_HIV_HCV_BUPC_INJ)
a_TDP_1[HIV & INJ, BUPC & INJ & COI, ] <- a_TDP_1[HIV & INJ, BUPC & INJ & COI, ] * p_HIV_HCV_BUPC_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, BUPC & INJ & COI, ] <- a_TDP_2[HIV & INJ, BUPC & INJ & COI, ] * p_HIV_HCV_BUPC_INJ
a_TDP_3[HIV & INJ, BUPC & INJ & COI, ] <- a_TDP_3[HIV & INJ, BUPC & INJ & COI, ] * p_HIV_HCV_BUPC_INJ
# From HCV
a_TDP_1[HCV & INJ, BUPC & INJ & HCV, ] <- a_TDP_1[HCV & INJ, BUPC & INJ & HCV, ] * (1 - p_HCV_HIV_BUPC_INJ)
a_TDP_2[HCV & INJ, BUPC & INJ & HCV, ] <- a_TDP_2[HCV & INJ, BUPC & INJ & HCV, ] * (1 - p_HCV_HIV_BUPC_INJ)
a_TDP_3[HCV & INJ, BUPC & INJ & HCV, ] <- a_TDP_3[HCV & INJ, BUPC & INJ & HCV, ] * (1 - p_HCV_HIV_BUPC_INJ)
a_TDP_1[HCV & INJ, BUPC & INJ & COI, ] <- a_TDP_1[HCV & INJ, BUPC & INJ & COI, ] * p_HCV_HIV_BUPC_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, BUPC & INJ & COI, ] <- a_TDP_2[HCV & INJ, BUPC & INJ & COI, ] * p_HCV_HIV_BUPC_INJ
a_TDP_3[HCV & INJ, BUPC & INJ & COI, ] <- a_TDP_3[HCV & INJ, BUPC & INJ & COI, ] * p_HCV_HIV_BUPC_INJ
# MET
# From NEG
a_TDP_1[NEG & INJ, MET & INJ & NEG, ] <- a_TDP_1[NEG & INJ, MET & INJ & NEG, ] * (1 - p_HIV_MET_INJ - p_HCV_MET_INJ)
a_TDP_2[NEG & INJ, MET & INJ & NEG, ] <- a_TDP_2[NEG & INJ, MET & INJ & NEG, ] * (1 - p_HIV_MET_INJ - p_HCV_MET_INJ)
a_TDP_3[NEG & INJ, MET & INJ & NEG, ] <- a_TDP_3[NEG & INJ, MET & INJ & NEG, ] * (1 - p_HIV_MET_INJ - p_HCV_MET_INJ)
a_TDP_1[NEG & INJ, MET & INJ & HIV, ] <- a_TDP_1[NEG & INJ, MET & INJ & HIV, ] * p_HIV_MET_INJ
a_TDP_2[NEG & INJ, MET & INJ & HIV, ] <- a_TDP_2[NEG & INJ, MET & INJ & HIV, ] * p_HIV_MET_INJ
a_TDP_3[NEG & INJ, MET & INJ & HIV, ] <- a_TDP_3[NEG & INJ, MET & INJ & HIV, ] * p_HIV_MET_INJ
a_TDP_1[NEG & INJ, MET & INJ & HCV, ] <- a_TDP_1[NEG & INJ, MET & INJ & HCV, ] * p_HCV_MET_INJ
a_TDP_2[NEG & INJ, MET & INJ & HCV, ] <- a_TDP_2[NEG & INJ, MET & INJ & HCV, ] * p_HCV_MET_INJ
a_TDP_3[NEG & INJ, MET & INJ & HCV, ] <- a_TDP_3[NEG & INJ, MET & INJ & HCV, ] * p_HCV_MET_INJ
# From HIV
a_TDP_1[HIV & INJ, MET & INJ & HIV, ] <- a_TDP_1[HIV & INJ, MET & INJ & HIV, ] * (1 - p_HIV_HCV_MET_INJ)
a_TDP_2[HIV & INJ, MET & INJ & HIV, ] <- a_TDP_2[HIV & INJ, MET & INJ & HIV, ] * (1 - p_HIV_HCV_MET_INJ)
a_TDP_3[HIV & INJ, MET & INJ & HIV, ] <- a_TDP_3[HIV & INJ, MET & INJ & HIV, ] * (1 - p_HIV_HCV_MET_INJ)
a_TDP_1[HIV & INJ, MET & INJ & COI, ] <- a_TDP_1[HIV & INJ, MET & INJ & COI, ] * p_HIV_HCV_MET_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, MET & INJ & COI, ] <- a_TDP_2[HIV & INJ, MET & INJ & COI, ] * p_HIV_HCV_MET_INJ
a_TDP_3[HIV & INJ, MET & INJ & COI, ] <- a_TDP_3[HIV & INJ, MET & INJ & COI, ] * p_HIV_HCV_MET_INJ
# From HCV
a_TDP_1[HCV & INJ, MET & INJ & HCV, ] <- a_TDP_1[HCV & INJ, MET & INJ & HCV, ] * (1 - p_HCV_HIV_MET_INJ)
a_TDP_2[HCV & INJ, MET & INJ & HCV, ] <- a_TDP_2[HCV & INJ, MET & INJ & HCV, ] * (1 - p_HCV_HIV_MET_INJ)
a_TDP_3[HCV & INJ, MET & INJ & HCV, ] <- a_TDP_3[HCV & INJ, MET & INJ & HCV, ] * (1 - p_HCV_HIV_MET_INJ)
a_TDP_1[HCV & INJ, MET & INJ & COI, ] <- a_TDP_1[HCV & INJ, MET & INJ & COI, ] * p_HCV_HIV_MET_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, MET & INJ & COI, ] <- a_TDP_2[HCV & INJ, MET & INJ & COI, ] * p_HCV_HIV_MET_INJ
a_TDP_3[HCV & INJ, MET & INJ & COI, ] <- a_TDP_3[HCV & INJ, MET & INJ & COI, ] * p_HCV_HIV_MET_INJ
# METC
# From NEG
a_TDP_1[NEG & INJ, METC & INJ & NEG, ] <- a_TDP_1[NEG & INJ, METC & INJ & NEG, ] * (1 - p_HIV_METC_INJ - p_HCV_METC_INJ)
a_TDP_2[NEG & INJ, METC & INJ & NEG, ] <- a_TDP_2[NEG & INJ, METC & INJ & NEG, ] * (1 - p_HIV_METC_INJ - p_HCV_METC_INJ)
a_TDP_3[NEG & INJ, METC & INJ & NEG, ] <- a_TDP_3[NEG & INJ, METC & INJ & NEG, ] * (1 - p_HIV_METC_INJ - p_HCV_METC_INJ)
a_TDP_1[NEG & INJ, METC & INJ & HIV, ] <- a_TDP_1[NEG & INJ, METC & INJ & HIV, ] * p_HIV_METC_INJ
a_TDP_2[NEG & INJ, METC & INJ & HIV, ] <- a_TDP_2[NEG & INJ, METC & INJ & HIV, ] * p_HIV_METC_INJ
a_TDP_3[NEG & INJ, METC & INJ & HIV, ] <- a_TDP_3[NEG & INJ, METC & INJ & HIV, ] * p_HIV_METC_INJ
a_TDP_1[NEG & INJ, METC & INJ & HCV, ] <- a_TDP_1[NEG & INJ, METC & INJ & HCV, ] * p_HCV_METC_INJ
a_TDP_2[NEG & INJ, METC & INJ & HCV, ] <- a_TDP_2[NEG & INJ, METC & INJ & HCV, ] * p_HCV_METC_INJ
a_TDP_3[NEG & INJ, METC & INJ & HCV, ] <- a_TDP_3[NEG & INJ, METC & INJ & HCV, ] * p_HCV_METC_INJ
# From HIV
a_TDP_1[HIV & INJ, METC & INJ & HIV, ] <- a_TDP_1[HIV & INJ, METC & INJ & HIV, ] * (1 - p_HIV_HCV_METC_INJ)
a_TDP_2[HIV & INJ, METC & INJ & HIV, ] <- a_TDP_2[HIV & INJ, METC & INJ & HIV, ] * (1 - p_HIV_HCV_METC_INJ)
a_TDP_3[HIV & INJ, METC & INJ & HIV, ] <- a_TDP_3[HIV & INJ, METC & INJ & HIV, ] * (1 - p_HIV_HCV_METC_INJ)
a_TDP_1[HIV & INJ, METC & INJ & COI, ] <- a_TDP_1[HIV & INJ, METC & INJ & COI, ] * p_HIV_HCV_METC_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, METC & INJ & COI, ] <- a_TDP_2[HIV & INJ, METC & INJ & COI, ] * p_HIV_HCV_METC_INJ
a_TDP_3[HIV & INJ, METC & INJ & COI, ] <- a_TDP_3[HIV & INJ, METC & INJ & COI, ] * p_HIV_HCV_METC_INJ
# From HCV
a_TDP_1[HCV & INJ, METC & INJ & HCV, ] <- a_TDP_1[HCV & INJ, METC & INJ & HCV, ] * (1 - p_HCV_HIV_METC_INJ)
a_TDP_2[HCV & INJ, METC & INJ & HCV, ] <- a_TDP_2[HCV & INJ, METC & INJ & HCV, ] * (1 - p_HCV_HIV_METC_INJ)
a_TDP_3[HCV & INJ, METC & INJ & HCV, ] <- a_TDP_3[HCV & INJ, METC & INJ & HCV, ] * (1 - p_HCV_HIV_METC_INJ)
a_TDP_1[HCV & INJ, METC & INJ & COI, ] <- a_TDP_1[HCV & INJ, METC & INJ & COI, ] * p_HCV_HIV_METC_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, METC & INJ & COI, ] <- a_TDP_2[HCV & INJ, METC & INJ & COI, ] * p_HCV_HIV_METC_INJ
a_TDP_3[HCV & INJ, METC & INJ & COI, ] <- a_TDP_3[HCV & INJ, METC & INJ & COI, ] * p_HCV_HIV_METC_INJ
# REL
# From NEG
a_TDP_1[NEG & INJ, REL & INJ & NEG, ] <- a_TDP_1[NEG & INJ, REL & INJ & NEG, ] * (1 - p_HIV_REL_INJ - p_HCV_REL_INJ)
a_TDP_2[NEG & INJ, REL & INJ & NEG, ] <- a_TDP_2[NEG & INJ, REL & INJ & NEG, ] * (1 - p_HIV_REL_INJ - p_HCV_REL_INJ)
a_TDP_3[NEG & INJ, REL & INJ & NEG, ] <- a_TDP_3[NEG & INJ, REL & INJ & NEG, ] * (1 - p_HIV_REL_INJ - p_HCV_REL_INJ)
a_TDP_1[NEG & INJ, REL & INJ & HIV, ] <- a_TDP_1[NEG & INJ, REL & INJ & HIV, ] * p_HIV_REL_INJ
a_TDP_2[NEG & INJ, REL & INJ & HIV, ] <- a_TDP_2[NEG & INJ, REL & INJ & HIV, ] * p_HIV_REL_INJ
a_TDP_3[NEG & INJ, REL & INJ & HIV, ] <- a_TDP_3[NEG & INJ, REL & INJ & HIV, ] * p_HIV_REL_INJ
a_TDP_1[NEG & INJ, REL & INJ & HCV, ] <- a_TDP_1[NEG & INJ, REL & INJ & HCV, ] * p_HCV_REL_INJ
a_TDP_2[NEG & INJ, REL & INJ & HCV, ] <- a_TDP_2[NEG & INJ, REL & INJ & HCV, ] * p_HCV_REL_INJ
a_TDP_3[NEG & INJ, REL & INJ & HCV, ] <- a_TDP_3[NEG & INJ, REL & INJ & HCV, ] * p_HCV_REL_INJ
# From HIV
a_TDP_1[HIV & INJ, REL & INJ & HIV, ] <- a_TDP_1[HIV & INJ, REL & INJ & HIV, ] * (1 - p_HIV_HCV_REL_INJ)
a_TDP_2[HIV & INJ, REL & INJ & HIV, ] <- a_TDP_2[HIV & INJ, REL & INJ & HIV, ] * (1 - p_HIV_HCV_REL_INJ)
a_TDP_3[HIV & INJ, REL & INJ & HIV, ] <- a_TDP_3[HIV & INJ, REL & INJ & HIV, ] * (1 - p_HIV_HCV_REL_INJ)
a_TDP_1[HIV & INJ, REL & INJ & COI, ] <- a_TDP_1[HIV & INJ, REL & INJ & COI, ] * p_HIV_HCV_REL_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, REL & INJ & COI, ] <- a_TDP_2[HIV & INJ, REL & INJ & COI, ] * p_HIV_HCV_REL_INJ
a_TDP_3[HIV & INJ, REL & INJ & COI, ] <- a_TDP_3[HIV & INJ, REL & INJ & COI, ] * p_HIV_HCV_REL_INJ
# From HCV
a_TDP_1[HCV & INJ, REL & INJ & HCV, ] <- a_TDP_1[HCV & INJ, REL & INJ & HCV, ] * (1 - p_HCV_HIV_REL_INJ)
a_TDP_2[HCV & INJ, REL & INJ & HCV, ] <- a_TDP_2[HCV & INJ, REL & INJ & HCV, ] * (1 - p_HCV_HIV_REL_INJ)
a_TDP_3[HCV & INJ, REL & INJ & HCV, ] <- a_TDP_3[HCV & INJ, REL & INJ & HCV, ] * (1 - p_HCV_HIV_REL_INJ)
a_TDP_1[HCV & INJ, REL & INJ & COI, ] <- a_TDP_1[HCV & INJ, REL & INJ & COI, ] * p_HCV_HIV_REL_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, REL & INJ & COI, ] <- a_TDP_2[HCV & INJ, REL & INJ & COI, ] * p_HCV_HIV_REL_INJ
a_TDP_3[HCV & INJ, REL & INJ & COI, ] <- a_TDP_3[HCV & INJ, REL & INJ & COI, ] * p_HCV_HIV_REL_INJ
# ODN
# From NEG
a_TDP_1[NEG & INJ, ODN & INJ & NEG, ] <- a_TDP_1[NEG & INJ, ODN & INJ & NEG, ] * (1 - p_HIV_ODN_INJ - p_HCV_ODN_INJ)
a_TDP_2[NEG & INJ, ODN & INJ & NEG, ] <- a_TDP_2[NEG & INJ, ODN & INJ & NEG, ] * (1 - p_HIV_ODN_INJ - p_HCV_ODN_INJ)
a_TDP_3[NEG & INJ, ODN & INJ & NEG, ] <- a_TDP_3[NEG & INJ, ODN & INJ & NEG, ] * (1 - p_HIV_ODN_INJ - p_HCV_ODN_INJ)
a_TDP_1[NEG & INJ, ODN & INJ & HIV, ] <- a_TDP_1[NEG & INJ, ODN & INJ & HIV, ] * p_HIV_ODN_INJ
a_TDP_2[NEG & INJ, ODN & INJ & HIV, ] <- a_TDP_2[NEG & INJ, ODN & INJ & HIV, ] * p_HIV_ODN_INJ
a_TDP_3[NEG & INJ, ODN & INJ & HIV, ] <- a_TDP_3[NEG & INJ, ODN & INJ & HIV, ] * p_HIV_ODN_INJ
a_TDP_1[NEG & INJ, ODN & INJ & HCV, ] <- a_TDP_1[NEG & INJ, ODN & INJ & HCV, ] * p_HCV_ODN_INJ
a_TDP_2[NEG & INJ, ODN & INJ & HCV, ] <- a_TDP_2[NEG & INJ, ODN & INJ & HCV, ] * p_HCV_ODN_INJ
a_TDP_3[NEG & INJ, ODN & INJ & HCV, ] <- a_TDP_3[NEG & INJ, ODN & INJ & HCV, ] * p_HCV_ODN_INJ
# From HIV
a_TDP_1[HIV & INJ, ODN & INJ & HIV, ] <- a_TDP_1[HIV & INJ, ODN & INJ & HIV, ] * (1 - p_HIV_HCV_ODN_INJ)
a_TDP_2[HIV & INJ, ODN & INJ & HIV, ] <- a_TDP_2[HIV & INJ, ODN & INJ & HIV, ] * (1 - p_HIV_HCV_ODN_INJ)
a_TDP_3[HIV & INJ, ODN & INJ & HIV, ] <- a_TDP_3[HIV & INJ, ODN & INJ & HIV, ] * (1 - p_HIV_HCV_ODN_INJ)
a_TDP_1[HIV & INJ, ODN & INJ & COI, ] <- a_TDP_1[HIV & INJ, ODN & INJ & COI, ] * p_HIV_HCV_ODN_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, ODN & INJ & COI, ] <- a_TDP_2[HIV & INJ, ODN & INJ & COI, ] * p_HIV_HCV_ODN_INJ
a_TDP_3[HIV & INJ, ODN & INJ & COI, ] <- a_TDP_3[HIV & INJ, ODN & INJ & COI, ] * p_HIV_HCV_ODN_INJ
# From HCV
a_TDP_1[HCV & INJ, ODN & INJ & HCV, ] <- a_TDP_1[HCV & INJ, ODN & INJ & HCV, ] * (1 - p_HCV_HIV_ODN_INJ)
a_TDP_2[HCV & INJ, ODN & INJ & HCV, ] <- a_TDP_2[HCV & INJ, ODN & INJ & HCV, ] * (1 - p_HCV_HIV_ODN_INJ)
a_TDP_3[HCV & INJ, ODN & INJ & HCV, ] <- a_TDP_3[HCV & INJ, ODN & INJ & HCV, ] * (1 - p_HCV_HIV_ODN_INJ)
a_TDP_1[HCV & INJ, ODN & INJ & COI, ] <- a_TDP_1[HCV & INJ, ODN & INJ & COI, ] * p_HCV_HIV_ODN_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, ODN & INJ & COI, ] <- a_TDP_2[HCV & INJ, ODN & INJ & COI, ] * p_HCV_HIV_ODN_INJ
a_TDP_3[HCV & INJ, ODN & INJ & COI, ] <- a_TDP_3[HCV & INJ, ODN & INJ & COI, ] * p_HCV_HIV_ODN_INJ
# ODF
# From NEG
a_TDP_1[NEG & INJ, ODF & INJ & NEG, ] <- a_TDP_1[NEG & INJ, ODF & INJ & NEG, ] * 1
a_TDP_2[NEG & INJ, ODF & INJ & NEG, ] <- a_TDP_2[NEG & INJ, ODF & INJ & NEG, ] * 1
a_TDP_3[NEG & INJ, ODF & INJ & NEG, ] <- a_TDP_3[NEG & INJ, ODF & INJ & NEG, ] * 1
a_TDP_1[NEG & INJ, ODF & INJ & HIV, ] <- a_TDP_1[NEG & INJ, ODF & INJ & HIV, ] * 0
a_TDP_2[NEG & INJ, ODF & INJ & HIV, ] <- a_TDP_2[NEG & INJ, ODF & INJ & HIV, ] * 0
a_TDP_3[NEG & INJ, ODF & INJ & HIV, ] <- a_TDP_3[NEG & INJ, ODF & INJ & HIV, ] * 0
a_TDP_1[NEG & INJ, ODF & INJ & HCV, ] <- a_TDP_1[NEG & INJ, ODF & INJ & HCV, ] * 0
a_TDP_2[NEG & INJ, ODF & INJ & HCV, ] <- a_TDP_2[NEG & INJ, ODF & INJ & HCV, ] * 0
a_TDP_3[NEG & INJ, ODF & INJ & HCV, ] <- a_TDP_3[NEG & INJ, ODF & INJ & HCV, ] * 0
# From HIV
a_TDP_1[HIV & INJ, ODF & INJ & HIV, ] <- a_TDP_1[HIV & INJ, ODF & INJ & HIV, ] * 1
a_TDP_2[HIV & INJ, ODF & INJ & HIV, ] <- a_TDP_2[HIV & INJ, ODF & INJ & HIV, ] * 1
a_TDP_3[HIV & INJ, ODF & INJ & HIV, ] <- a_TDP_3[HIV & INJ, ODF & INJ & HIV, ] * 1
a_TDP_1[HIV & INJ, ODF & INJ & COI, ] <- a_TDP_1[HIV & INJ, ODF & INJ & COI, ] * 0
a_TDP_2[HIV & INJ, ODF & INJ & COI, ] <- a_TDP_2[HIV & INJ, ODF & INJ & COI, ] * 0
a_TDP_3[HIV & INJ, ODF & INJ & COI, ] <- a_TDP_3[HIV & INJ, ODF & INJ & COI, ] * 0
# From HCV
a_TDP_1[HCV & INJ, ODF & INJ & HCV, ] <- a_TDP_1[HCV & INJ, ODF & INJ & HCV, ] * 1
a_TDP_2[HCV & INJ, ODF & INJ & HCV, ] <- a_TDP_2[HCV & INJ, ODF & INJ & HCV, ] * 1
a_TDP_3[HCV & INJ, ODF & INJ & HCV, ] <- a_TDP_3[HCV & INJ, ODF & INJ & HCV, ] * 1
a_TDP_1[HCV & INJ, ODF & INJ & COI, ] <- a_TDP_1[HCV & INJ, ODF & INJ & COI, ] * 0
a_TDP_2[HCV & INJ, ODF & INJ & COI, ] <- a_TDP_2[HCV & INJ, ODF & INJ & COI, ] * 0
a_TDP_3[HCV & INJ, ODF & INJ & COI, ] <- a_TDP_3[HCV & INJ, ODF & INJ & COI, ] * 0
# ABS
# From NEG
a_TDP_1[NEG & INJ, ABS & INJ & NEG, ] <- a_TDP_1[NEG & INJ, ABS & INJ & NEG, ] * (1 - p_HIV_ABS_INJ - p_HCV_ABS_INJ)
a_TDP_2[NEG & INJ, ABS & INJ & NEG, ] <- a_TDP_2[NEG & INJ, ABS & INJ & NEG, ] * (1 - p_HIV_ABS_INJ - p_HCV_ABS_INJ)
a_TDP_3[NEG & INJ, ABS & INJ & NEG, ] <- a_TDP_3[NEG & INJ, ABS & INJ & NEG, ] * (1 - p_HIV_ABS_INJ - p_HCV_ABS_INJ)
a_TDP_1[NEG & INJ, ABS & INJ & HIV, ] <- a_TDP_1[NEG & INJ, ABS & INJ & HIV, ] * p_HIV_ABS_INJ
a_TDP_2[NEG & INJ, ABS & INJ & HIV, ] <- a_TDP_2[NEG & INJ, ABS & INJ & HIV, ] * p_HIV_ABS_INJ
a_TDP_3[NEG & INJ, ABS & INJ & HIV, ] <- a_TDP_3[NEG & INJ, ABS & INJ & HIV, ] * p_HIV_ABS_INJ
a_TDP_1[NEG & INJ, ABS & INJ & HCV, ] <- a_TDP_1[NEG & INJ, ABS & INJ & HCV, ] * p_HCV_ABS_INJ
a_TDP_2[NEG & INJ, ABS & INJ & HCV, ] <- a_TDP_2[NEG & INJ, ABS & INJ & HCV, ] * p_HCV_ABS_INJ
a_TDP_3[NEG & INJ, ABS & INJ & HCV, ] <- a_TDP_3[NEG & INJ, ABS & INJ & HCV, ] * p_HCV_ABS_INJ
# From HIV
a_TDP_1[HIV & INJ, ABS & INJ & HIV, ] <- a_TDP_1[HIV & INJ, ABS & INJ & HIV, ] * (1 - p_HIV_HCV_ABS_INJ)
a_TDP_2[HIV & INJ, ABS & INJ & HIV, ] <- a_TDP_2[HIV & INJ, ABS & INJ & HIV, ] * (1 - p_HIV_HCV_ABS_INJ)
a_TDP_3[HIV & INJ, ABS & INJ & HIV, ] <- a_TDP_3[HIV & INJ, ABS & INJ & HIV, ] * (1 - p_HIV_HCV_ABS_INJ)
a_TDP_1[HIV & INJ, ABS & INJ & COI, ] <- a_TDP_1[HIV & INJ, ABS & INJ & COI, ] * p_HIV_HCV_ABS_INJ # Probability of HCV conditional on HIV
a_TDP_2[HIV & INJ, ABS & INJ & COI, ] <- a_TDP_2[HIV & INJ, ABS & INJ & COI, ] * p_HIV_HCV_ABS_INJ
a_TDP_3[HIV & INJ, ABS & INJ & COI, ] <- a_TDP_3[HIV & INJ, ABS & INJ & COI, ] * p_HIV_HCV_ABS_INJ
# From HCV
a_TDP_1[HCV & INJ, ABS & INJ & HCV, ] <- a_TDP_1[HCV & INJ, ABS & INJ & HCV, ] * (1 - p_HCV_HIV_ABS_INJ)
a_TDP_2[HCV & INJ, ABS & INJ & HCV, ] <- a_TDP_2[HCV & INJ, ABS & INJ & HCV, ] * (1 - p_HCV_HIV_ABS_INJ)
a_TDP_3[HCV & INJ, ABS & INJ & HCV, ] <- a_TDP_3[HCV & INJ, ABS & INJ & HCV, ] * (1 - p_HCV_HIV_ABS_INJ)
a_TDP_1[HCV & INJ, ABS & INJ & COI, ] <- a_TDP_1[HCV & INJ, ABS & INJ & COI, ] * p_HCV_HIV_ABS_INJ # Probability of HIV conditional on HCV
a_TDP_2[HCV & INJ, ABS & INJ & COI, ] <- a_TDP_2[HCV & INJ, ABS & INJ & COI, ] * p_HCV_HIV_ABS_INJ
a_TDP_3[HCV & INJ, ABS & INJ & COI, ] <- a_TDP_3[HCV & INJ, ABS & INJ & COI, ] * p_HCV_HIV_ABS_INJ
#### Disallowed transitions (ensure that impossible transitions are set to zero) ####
# Episode rules
a_TDP_1[EP1, EP3, ] <- a_TDP_2[EP1, EP3, ] <- a_TDP_3[EP1, EP3, ] <- 0
a_TDP_1[EP2, EP1, ] <- a_TDP_2[EP2, EP1, ] <- a_TDP_3[EP2, EP1, ] <- 0
a_TDP_1[EP3, EP1, ] <- a_TDP_2[EP3, EP1, ] <- a_TDP_3[EP3, EP1, ] <- 0
a_TDP_1[EP3, EP2, ] <- a_TDP_2[EP3, EP2, ] <- a_TDP_3[EP3, EP2, ] <- 0
# Injection <> Non-injection
a_TDP_1[INJ, NI,] <- a_TDP_2[INJ, NI,] <- a_TDP_3[INJ, NI,] <- 0
a_TDP_1[NI, INJ,] <- a_TDP_2[NI, INJ,] <- a_TDP_3[NI, INJ,] <- 0
# Seroconversions
a_TDP_1[HIV, NEG, ] <- a_TDP_2[HIV, NEG, ] <- a_TDP_3[HIV, NEG, ] <- 0
a_TDP_1[HCV, NEG, ] <- a_TDP_2[HCV, NEG, ] <- a_TDP_3[HCV, NEG, ] <- 0
a_TDP_1[COI, NEG, ] <- a_TDP_2[COI, NEG, ] <- a_TDP_3[COI, NEG, ] <- 0
a_TDP_1[HIV, HCV, ] <- a_TDP_2[HIV, HCV, ] <- a_TDP_3[HIV, HCV, ] <- 0
a_TDP_1[HCV, HIV, ] <- a_TDP_2[HCV, HIV, ] <- a_TDP_3[HCV, HIV, ] <- 0
a_TDP_1[COI, HIV, ] <- a_TDP_2[COI, HIV, ] <- a_TDP_3[COI, HIV, ] <- 0
a_TDP_1[COI, HCV, ] <- a_TDP_2[COI, HCV, ] <- a_TDP_3[COI, HCV, ] <- 0
a_TDP_1[COI, NEG, ] <- a_TDP_2[COI, NEG, ] <- a_TDP_3[COI, NEG, ] <- 0
a_TDP_1[NEG, COI, ] <- a_TDP_2[NEG, COI, ] <- a_TDP_3[NEG, COI, ] <- 0
# Conditional transitions
# Next episode with out-of-treatment(OOT) EPi -> treatment(TX) EP(i+1)
a_TDP_1[all_TX & EP1, all_TX & EP2, ] <- a_TDP_2[all_TX & EP1, all_TX & EP2, ] <- a_TDP_3[all_TX & EP1, all_TX & EP2, ] <- 0
a_TDP_1[all_TX & EP1, all_TX & EP3, ] <- a_TDP_2[all_TX & EP1, all_TX & EP3, ] <- a_TDP_3[all_TX & EP1, all_TX & EP3, ] <- 0
a_TDP_1[all_TX & EP2, all_TX & EP3, ] <- a_TDP_2[all_TX & EP2, all_TX & EP3, ] <- a_TDP_3[all_TX & EP2, all_TX & EP3, ] <- 0
a_TDP_1[OOT & EP1, OOT & EP2, ] <- a_TDP_2[OOT & EP1, OOT & EP2, ] <- a_TDP_3[OOT & EP1, OOT & EP2, ] <- 0
a_TDP_1[OOT & EP1, OOT & EP3, ] <- a_TDP_2[OOT & EP1, OOT & EP3, ] <- a_TDP_3[OOT & EP1, OOT & EP3, ] <- 0
a_TDP_1[OOT & EP2, OOT & EP3, ] <- a_TDP_2[OOT & EP2, OOT & EP3, ] <- a_TDP_3[OOT & EP2, OOT & EP3, ] <- 0
a_TDP_1[all_TX & EP1, OOT & EP2, ] <- a_TDP_2[all_TX & EP1, OOT & EP2, ] <- a_TDP_3[all_TX & EP1, OOT & EP2, ] <- 0
a_TDP_1[all_TX & EP2, OOT & EP3, ] <- a_TDP_2[all_TX & EP2, OOT & EP3, ] <- a_TDP_3[all_TX & EP2, OOT & EP3, ] <- 0
a_TDP_1[OOT & EP1, all_TX & EP1, ] <- a_TDP_2[OOT & EP1, all_TX & EP1, ] <- a_TDP_3[OOT & EP1, all_TX & EP1, ] <- 0
a_TDP_1[OOT & EP2, all_TX & EP2, ] <- a_TDP_2[OOT & EP2, all_TX & EP2, ] <- a_TDP_3[OOT & EP2, all_TX & EP2, ] <- 0
if(checks){
# State transitions
# First month (state-time)
#write.csv(a_UP_first[, , 1], "checks/state transitions/a_UP_first_2018.csv")
#write.csv(a_UP_first[, , 2], "checks/state transitions/a_UP_first_2019.csv")
#write.csv(a_UP_first[, , 3], "checks/state transitions/a_UP_first_2020.csv")
# Month 2+ (state-time)
#write.csv(a_UP[, , 1], "checks/state transitions/a_UP_2018.csv")
#write.csv(a_UP[, , 2], "checks/state transitions/a_UP_2019.csv")
#write.csv(a_UP[, , 3], "checks/state transitions/a_UP_2020.csv")
# Full array at time = 1
array_2018_1m <- a_TDP_1[, , 1]
array_2019_1m <- a_TDP_2[, , 1]
array_2020_1m <- a_TDP_3[, , 1]
write.csv(array_2018_1m,"checks/full array/array_2018_1m.csv", row.names = TRUE)
write.csv(array_2019_1m,"checks/full array/array_2019_1m.csv", row.names = TRUE)
write.csv(array_2020_1m,"checks/full array/array_2020_1m.csv", row.names = TRUE)
# Full array at time = 24 months
array_2018_24m <- a_TDP_1[, , 24]
array_2019_24m <- a_TDP_2[, , 24]
array_2020_24m <- a_TDP_3[, , 24]
write.csv(array_2018_24m,"checks/full array/array_2018_24m.csv", row.names = TRUE)
write.csv(array_2019_24m,"checks/full array/array_2019_24m.csv", row.names = TRUE)
write.csv(array_2020_24m,"checks/full array/array_2020_24m.csv", row.names = TRUE)
# Full array at time = max
array_2018_last <- a_TDP_1[, , n_t]
array_2019_last <- a_TDP_2[, , n_t]
array_2020_last <- a_TDP_3[, , n_t]
write.csv(array_2018_last,"checks/full array/array_2018_last.csv", row.names = TRUE)
write.csv(array_2019_last,"checks/full array/array_2019_last.csv", row.names = TRUE)
write.csv(array_2020_last,"checks/full array/array_2020_last.csv", row.names = TRUE)
} else{}
#### Check transition array ####
#check_transition_probability(a_P = a_TDP, err_stop = err_stop, verbose = verbose) # check all probs [0, 1]
#check_sum_of_transition_array(a_P = a_TDP, n_states = n_states, n_t = n_t, err_stop = err_stop, verbose = verbose) # check prob sums = 1
#### Run Markov model ####
# Create empty initial state vectors
v_s_init <- rep(0, n_states)
names(v_s_init) <- v_n_states
#### Set initial state vector ####
# Baseline
# Populate baseline states
# Think about this e.g. (all start in EP1, or according to observed %'s in each episode)
# Episode 1
v_s_init[BUP & EP1] <- v_init_dist["pe", "BUP"] # Empirically observed proportions from base states
v_s_init[BUPC & EP1] <- v_init_dist["pe", "BUPC"]
v_s_init[MET & EP1] <- v_init_dist["pe", "MET"]
v_s_init[METC & EP1] <- v_init_dist["pe", "METC"]
v_s_init[REL & EP1] <- v_init_dist["pe", "REL"]
v_s_init[ODN & EP1] <- v_init_dist["pe", "ODN"]
v_s_init[ODF & EP1] <- v_init_dist["pe", "ODF"]
v_s_init[ABS & EP1] <- v_init_dist["pe", "ABS"]
# Distribute by injection/non-injection
v_s_init[NI] <- v_s_init[NI] * (1 - n_INJ)
v_s_init[INJ] <- v_s_init[INJ] * n_INJ
# Distribute HIV/HCV/COI
# Injection
v_s_init[NEG & INJ] <- v_s_init[NEG & INJ] * (1 - n_HIV_INJ - n_HCV_INJ - n_COI_INJ)
v_s_init[HIV & INJ] <- v_s_init[HIV & INJ] * n_HIV_INJ
v_s_init[HCV & INJ] <- v_s_init[HCV & INJ] * n_HCV_INJ
v_s_init[COI & INJ] <- v_s_init[COI & INJ] * n_COI_INJ
# Non-injection
v_s_init[NEG & NI] <- v_s_init[NEG & NI] * (1 - n_HIV_NI - n_HCV_NI - n_COI_NI)
v_s_init[HIV & NI] <- v_s_init[HIV & NI] * n_HIV_NI
v_s_init[HCV & NI] <- v_s_init[HCV & NI] * n_HCV_NI
v_s_init[COI & NI] <- v_s_init[COI & NI] * n_COI_NI
if(checks){
write.csv(v_s_init,"checks/initial/v_s_init.csv", row.names = TRUE)
}
# Create Markov Trace
# Initialize population
a_M_trace <- array(0, dim = c((n_t + 1), n_states, (n_t + 1)),
dimnames = list(0:n_t, v_n_states, 0:n_t))
a_M_trace[1, , 1] <- v_s_init
# Calbrate over three time points (2018, 2019, 2020)
if(cali == TRUE){
# All model time periods
# Split into three periods 0-12; 12-24; 24+ to account for overall time-varying overdose parameters
# Months 0-12 (model-time)
for(i in 2:11){
# Time spent in given health state
# First month (state-time)
for(j in 1:(i - 1)){
# state-time-dependent transition probability (j) * age (model-time)-specific mortality (i) * model-time-specific overdose (track in separate matrix)
# Conditional state transition matrix at time (j) ~ sojourn time is continuous time spent in health state
# Remove deaths from all states (depends only on cohort age (i) and health state-specific SMR
m_sojourn <- a_TDP_1[, , j] * m_alive[, i - 1] # state-time transition matrix at state-time j, re-weighted for model-time (age) varying mortality at each time point
# Current health states from prior cycle
# Row vector of individuals across all health states
v_current_state <- as.vector(a_M_trace[i - 1, , j]) # all in current state
# Transitions remaining in current states
# Multiply current vector of state occupancy by diagonal of state-time-dependent array (i.e., the conditional probability of remaining in given health state)
v_same_state <- as.vector(v_current_state * diag(m_sojourn)) # individuals remaining in state next period
# Add remain probabilities to next period, increase sojourn time by 1
# a_M_trace already initialized for i = 1 above
# Add % individuals remaining in subsequent period only
a_M_trace[i, ,j + 1] <- v_same_state # add remain to next period
# Set diagonal to zero as these have been counted
# Reset only remain (diagonal) to zero and keep state transitions
diag(m_sojourn) <- 0 # reset remain to 0 once counted
# Transitions to new health states
# Create vector of states following transition according to conditional state-transition matrix excluding remain (i.e., multiply same states by zero)
v_new_state <- as.vector(v_current_state %*% m_sojourn) # populate new states post-transition (excluding remaining)
# Add new state %'s to markov trace
a_M_trace[i, ,1] <- v_new_state + a_M_trace[i, ,1] # add new state %'s to array
}
}
# Months 12-23 (model-time)
for(i in 12:23){
# Time spent in given health state
# First month (state-time)
for(j in 1:(i - 1)){
# state-time-dependent transition probability (j) * age (model-time)-specific mortality (i) * model-time-specific overdose (track in separate matrix)
m_sojourn <- a_TDP_2[, , j] * m_alive[, i - 1] # state-time transition matrix at state-time j, re-weighted for model-time (age) varying mortality at each time point
v_current_state <- as.vector(a_M_trace[i - 1, , j]) # all in current state
v_same_state <- as.vector(v_current_state * diag(m_sojourn)) # individuals remaining in state next period
a_M_trace[i, ,j + 1] <- v_same_state # add remain to next period
diag(m_sojourn) <- 0 # reset remain to 0 once counted
v_new_state <- as.vector(v_current_state %*% m_sojourn) # populate new states post-transition (excluding remaining)
a_M_trace[i, ,1] <- v_new_state + a_M_trace[i, ,1] # add new state %'s to array
}
}
# Months 24+ (model-time)
for(i in 24:(n_t)){
# Time spent in given health state
# First month (state-time)
for(j in 1:(i - 1)){
m_sojourn <- a_TDP_3[, , j] * m_alive[, i - 1] # state-time transition matrix at state-time j, re-weighted for model-time (age) varying mortality at each time point, time-varying overdose (t=3)
v_current_state <- as.vector(a_M_trace[i - 1, , j]) # all in current state
v_same_state <- as.vector(v_current_state * diag(m_sojourn)) # individuals remaining in state next period
a_M_trace[i, ,j + 1] <- v_same_state # add remain to next period
diag(m_sojourn) <- 0 # reset remain to 0 once counted
v_new_state <- as.vector(v_current_state %*% m_sojourn) # populate new states post-transition (excluding remaining)
a_M_trace[i, ,1] <- v_new_state + a_M_trace[i, ,1] # add new state %'s to array
}
}
} else{ # For non-calibration, run model for 2020+
# Full periods (model-time)
for(i in 2:(n_t)){
# Time spent in given health state
# First month (state-time)
for(j in 1:(i - 1)){
m_sojourn <- a_TDP_3[, , j] * m_alive[, i - 1] # state-time transition matrix at state-time j, re-weighted for model-time (age) varying mortality at each time point, time-varying overdose (t=3)
v_current_state <- as.vector(a_M_trace[i - 1, , j]) # all in current state
v_same_state <- as.vector(v_current_state * diag(m_sojourn)) # individuals remaining in state next period
a_M_trace[i, ,j + 1] <- v_same_state # add remain to next period
diag(m_sojourn) <- 0 # reset remain to 0 once counted
v_new_state <- as.vector(v_current_state %*% m_sojourn) # populate new states post-transition (excluding remaining)
a_M_trace[i, ,1] <- v_new_state + a_M_trace[i, ,1] # add new state %'s to array
}
}
}
# Array checks
if(checks){
a_M_trace_1 <- a_M_trace[, , 1]
a_M_trace_2 <- a_M_trace[, , 2]
a_M_trace_3 <- a_M_trace[, , 3]
write.csv(a_M_trace_1,"checks/full trace array/a_M_trace_1.csv", row.names = TRUE)
write.csv(a_M_trace_2,"checks/full trace array/a_M_trace_2.csv", row.names = TRUE)
write.csv(a_M_trace_3,"checks/full trace array/a_M_trace_3.csv", row.names = TRUE)
} else{}
# Collect trace for time-periods across all model states
m_M_trace <- array(0, dim = c((n_t + 1), n_states),
dimnames = list(0:n_t, v_n_states))
for (i in 1:n_t){
m_M_trace[i, ] <- rowSums(a_M_trace[i, ,])
}
# Count cumulative state-specific deaths
m_M_trace_death <- array(0, dim = c((n_t + 1), n_states),
dimnames = list(0:n_t, v_n_states))
for (i in 2:n_t){
m_M_trace_death[i, ] <- m_M_trace[i - 1, ] * m_mort[, i - 1] # State-specific deaths at each time point as function of state-occupancy in t-1
}
m_M_trace_cumsum_death <- apply(m_M_trace_death, 2, cumsum) # Cumulative non-overdose deaths at each time point (use m_M_trace_death for individual period deaths)
#### Create aggregated trace matrices ####
v_agg_trace_states <- c("Alive", "Death", "ODN", "ODF", "REL", "BUP", "BUPC", "MET", "METC", "ABS") # states to aggregate
v_agg_trace_death_states <- c("Total", "ODN", "ODF", "REL", "BUP", "BUPC", "MET", "METC", "ABS") # states to aggregate
v_agg_trace_sero_states <- c("NEG-Alive", "HIV-Alive", "HCV-Alive", "COI-Alive", "NEG-Dead", "HIV-Dead", "HCV-Dead", "COI-Dead") # states to aggregate
n_agg_trace_states <- length(v_agg_trace_states)
n_agg_trace_death_states <- length(v_agg_trace_death_states)
n_agg_trace_sero_states <- length(v_agg_trace_sero_states)
m_M_agg_trace <- array(0, dim = c((n_t + 1), n_agg_trace_states),
dimnames = list(0:n_t, v_agg_trace_states))
m_M_agg_trace_death <- array(0, dim = c((n_t + 1), n_agg_trace_death_states),
dimnames = list(0:n_t, v_agg_trace_death_states))
m_M_agg_trace_sero <- array(0, dim = c((n_t + 1), n_agg_trace_sero_states),
dimnames = list(0:n_t, v_agg_trace_sero_states))
for (i in 1:n_t){
#m_M_agg_trace[i, "Alive"] <- sum(m_M_trace[i, ])
m_M_agg_trace[i, "BUP"] <- sum(m_M_trace[i, BUP])
m_M_agg_trace[i, "BUPC"] <- sum(m_M_trace[i, BUPC])
m_M_agg_trace[i, "MET"] <- sum(m_M_trace[i, MET])
m_M_agg_trace[i, "METC"] <- sum(m_M_trace[i, METC])
m_M_agg_trace[i, "REL"] <- sum(m_M_trace[i, REL])
m_M_agg_trace[i, "ABS"] <- sum(m_M_trace[i, ABS])
m_M_agg_trace[i, "ODN"] <- sum(m_M_trace[i, ODN])
m_M_agg_trace[i, "ODF"] <- sum(m_M_trace[i, ODF])
m_M_agg_trace[i, "Death"] <- 1 - sum(m_M_trace[i, ])
}
# Aggregated state occupancy matrix
write.csv(m_M_agg_trace,"outputs/trace/m_M_agg_trace.csv", row.names = TRUE)
for (i in 1:n_t){
m_M_agg_trace_death[i, "Total"] <- sum(m_M_trace_cumsum_death[i, ])
m_M_agg_trace_death[i, "ODN"] <- sum(m_M_trace_cumsum_death[i, ODN])
m_M_agg_trace_death[i, "ODF"] <- sum(m_M_trace_cumsum_death[i, ODF])
m_M_agg_trace_death[i, "REL"] <- sum(m_M_trace_cumsum_death[i, REL])
m_M_agg_trace_death[i, "BUP"] <- sum(m_M_trace_cumsum_death[i, BUP])
m_M_agg_trace_death[i, "BUPC"] <- sum(m_M_trace_cumsum_death[i, BUPC])
m_M_agg_trace_death[i, "MET"] <- sum(m_M_trace_cumsum_death[i, MET])
m_M_agg_trace_death[i, "METC"] <- sum(m_M_trace_cumsum_death[i, METC])
m_M_agg_trace_death[i, "ABS"] <- sum(m_M_trace_cumsum_death[i, ABS])
}
for (i in 1:n_t){
m_M_agg_trace_sero[i, "NEG-Alive"] <- sum(m_M_trace[i, NEG & !ODF])
m_M_agg_trace_sero[i, "HIV-Alive"] <- sum(m_M_trace[i, HIV & !ODF])
m_M_agg_trace_sero[i, "HCV-Alive"] <- sum(m_M_trace[i, HCV & !ODF])
m_M_agg_trace_sero[i, "COI-Alive"] <- sum(m_M_trace[i, COI & !ODF])
m_M_agg_trace_sero[i, "NEG-Dead"] <- sum(m_M_trace_cumsum_death[i, NEG], m_M_trace[i, NEG & ODF])
m_M_agg_trace_sero[i, "HIV-Dead"] <- sum(m_M_trace_cumsum_death[i, HIV], m_M_trace[i, HIV & ODF])
m_M_agg_trace_sero[i, "HCV-Dead"] <- sum(m_M_trace_cumsum_death[i, HCV], m_M_trace[i, HCV & ODF])
m_M_agg_trace_sero[i, "COI-Dead"] <- sum(m_M_trace_cumsum_death[i, COI], m_M_trace[i, COI & ODF])
}
return(list(l_index_s = l_index_s,
a_M_trace = a_M_trace,
m_M_trace = m_M_trace,
m_M_agg_trace = m_M_agg_trace,
m_M_agg_trace_death = m_M_agg_trace_death,
m_M_agg_trace_sero = m_M_agg_trace_sero))
}
)
}
#' Check if transition array is valid
#'
#' \code{check_transition_probability} checks if individual transition probabilities are in range \[0, 1\].
#'
#' @param a_P A transition probability array.
#' @param err_stop Logical variable to stop model run if set up as TRUE. Default = FALSE.
#' @param verbose Logical variable to indicate print out of messages.
#' Default = FALSE
#'
#' @return
#' This function stops if transition probability array is not valid and shows which entries are invalid
#' @import utils
#' @export
check_transition_probability <- function(a_P,
err_stop = FALSE,
verbose = FALSE) {
m_indices_notvalid <- arrayInd(which(a_P < 0 | a_P > 1),
dim(a_P))
if(dim(m_indices_notvalid)[1] != 0){
v_rows_notval <- rownames(a_P)[m_indices_notvalid[, 1]]
v_cols_notval <- colnames(a_P)[m_indices_notvalid[, 2]]
v_cycles_notval <- dimnames(a_P)[[3]][m_indices_notvalid[, 3]]
df_notvalid <- data.frame(`Transition probabilities not valid:` =
matrix(paste0(paste(v_rows_notval, v_cols_notval, sep = "->"),
"; at cycle ",
v_cycles_notval), ncol = 1),
check.names = FALSE)
if(err_stop) {
stop("Not valid transition probabilities\n",
paste(capture.output(df_notvalid), collapse = "\n"))
}
if(verbose){
warning("Not valid transition probabilities\n",
paste(capture.output(df_notvalid), collapse = "\n"))
}
}
}
#' Check if the sum of transition probabilities from each state are equal to one.
#'
#' \code{check_sum_of_transition_array} checks if each of the rows of the
#' transition matrices sum to one.
#'
#' @param a_P Transition probability array.
#' @param n_states Number of health states.
#' @param n_t Number of time periods.
#' @param err_stop Logical variable to stop model run if set up as TRUE. Default = FALSE.
#' @param verbose Logical variable to indicate print out of messages. Default = FALSE.
#' @return
#' The transition probability array and the cohort trace matrix.
#' @import dplyr
#' @export
check_sum_of_transition_array <- function(a_P,
n_states,
n_t,
err_stop = FALSE,
verbose = FALSE) {
valid <- (apply(a_P, 3, function(x) sum(rowSums(x))) == n_states)
if (!isTRUE(all_equal(as.numeric(sum(valid)), as.numeric(n_t)))) {
if(err_stop) {
stop("This is not a valid transition Matrix")
}
if(verbose){
warning("This is not a valid transition Matrix")
}
}
}
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