run_deterministic_SEIR_model: Run the deterministic explicit SEIR model

In mrc-ide/squire: SEIR transmission model of COVID-19

Run the deterministic explicit SEIR model

Description

Run the deterministic explicit SEIR model

Usage

run_deterministic_SEIR_model(
  country = NULL,
  population = NULL,
  tt_contact_matrix = 0,
  contact_matrix_set = NULL,
  R0 = 3,
  tt_R0 = 0,
  beta_set = NULL,
  time_period = 365,
  dt = 0.1,
  day_return = FALSE,
  replicates = 10,
  init = NULL,
  seed = stats::runif(1, 0, 1e+08),
  prob_hosp = NULL,
  prob_severe = NULL,
  prob_non_severe_death_treatment = NULL,
  prob_non_severe_death_no_treatment = NULL,
  prob_severe_death_treatment = NULL,
  prob_severe_death_no_treatment = NULL,
  p_dist = probs$p_dist,
  walker_params = FALSE,
  dur_E = 4.6,
  dur_IMild = 2.1,
  dur_ICase = 4.5,
  dur_get_ox_survive = NULL,
  tt_dur_get_ox_survive = 0,
  dur_get_ox_die = NULL,
  tt_dur_get_ox_die = 0,
  dur_not_get_ox_survive = NULL,
  dur_not_get_ox_die = NULL,
  dur_get_mv_survive = NULL,
  tt_dur_get_mv_survive = 0,
  dur_get_mv_die = NULL,
  tt_dur_get_mv_die = 0,
  dur_not_get_mv_survive = NULL,
  dur_not_get_mv_die = NULL,
  dur_rec = NULL,
  dur_R = NULL,
  hosp_bed_capacity = NULL,
  ICU_bed_capacity = NULL,
  tt_hosp_beds = 0,
  tt_ICU_beds = 0,
  seeding_cases = NULL,
  mod_gen = explicit_SEIR_deterministic
)

Arguments

country	Character for country beign simulated. WIll be used to generate population and contact_matrix_set if unprovided. Either country or population and contact_matrix_set must be provided.
population	Population vector (for each age group). Default = NULL, which will cause population to be sourced from country
tt_contact_matrix	Time change points for matrix change. Default = 0
contact_matrix_set	Contact matrices used in simulation. Default = NULL, which will generate this based on the country.
R0	Basic Reproduction Number. Default = 3
tt_R0	Change time points for R0. Default = 0
beta_set	Alternative parameterisation via beta rather than R0. Default = NULL, which causes beta to be estimated from R0
time_period	Length of simulation. Default = 365
dt	Time Step. Default = 0.1
day_return	Logical, do we want to return outut after each day rather than each dt. Default = FALSE
replicates	Number of replicates
init	Data.frame of initial conditions. Default = NULL
seed	Random Number Seed.
prob_hosp	Probability of hospitalisation by age. Default, NULL, will use c(0.000840764, 0.001182411, 0.001662887, 0.002338607, 0.003288907, 0.004625365, 0.006504897, 0.009148183, 0.012865577, 0.018093546, 0.025445917, 0.035785947, 0.050327683, 0.0707785, 0.099539573, 0.1399878, 0.233470395)
prob_severe	Probability of developing severe symptoms by age. Default, NULL, will use c(0.000840764, 0.001182411, 0.001662887, 0.002338607, 0.003288907, 0.004625365, 0.006504897, 0.009148183, 0.012865577, 0.018093546, 0.025445917, 0.035785947, 0.050327683, 0.0707785, 0.099539573, 0.1399878, 0.233470395)
prob_non_severe_death_treatment	Probability of death from non severe treated infection. Default, NULL, will use c(0.181354223, 0.181354223, 0.181354223, 0.137454906, 0.121938236, 0.122775613, 0.136057441, 0.160922182, 0.196987378, 0.242011054, 0.289368845, 0.326537862, 0.337229819, 0.309082553, 0.243794865, 0.160480254, 0.057084366)
prob_non_severe_death_no_treatment	Probability of death in non severe hospital inections that aren't treated. Default, NULL, will use rep(0.5, 17)
prob_severe_death_treatment	Probability of death from severe infection that is treated. Default, NULL, will use c(0.226668959, 0.252420241, 0.281097009, 0.413005389, 0.518451493, 0.573413613, 0.576222065, 0.54253573, 0.493557696, 0.447376527, 0.416666608, 0.411186639, 0.443382594, 0.538718871, 0.570434076, 0.643352843, 0.992620047)
prob_severe_death_no_treatment	Probability of death from severe infection that is not treated. Default, NULL, will use rep(0.95, 17)
p_dist	Preferentiality of age group receiving treatment relative to other age groups when demand exceeds healthcare capacity.
walker_params	Boolean for using parameters in Walker et al. Default = FALSE, which uses parameter update as of November 2020. For full information see parameters vignette
dur_E	Mean duration of incubation period (days). Default = 4.6
dur_IMild	Mean duration of mild infection (days). Default = 2.1
dur_ICase	Mean duration from symptom onset to hospitil admission (days). Default = 4.5
dur_get_ox_survive	Mean duration of oxygen given survive. Default = 9
tt_dur_get_ox_survive	Times at which dur_get_ox_survive changes (Default = 0 = doesn't change)
dur_get_ox_die	Mean duration of oxygen given death. Default = 9
tt_dur_get_ox_die	Times at which dur_get_ox_die changes (Default = 0 = doesn't change)
dur_not_get_ox_survive	Mean duration without oxygen given survive. Default = 4.5
dur_not_get_ox_die	Mean duration without oxygen given death. Default = 4.5
dur_get_mv_survive	Mean duration of ventilation given survive. Default = 14.8
tt_dur_get_mv_survive	Times at which dur_get_mv_survive changes (Default = 0 = doesn't change)
dur_get_mv_die	Mean duration of ventilation given death. Default = 11.1
tt_dur_get_mv_die	Times at which dur_get_mv_die changes (Default = 0 = doesn't change)
dur_not_get_mv_survive	Mean duration without ventilation given survive. Default = 7.4
dur_not_get_mv_die	Mean duration without ventilation given death. Default = 1
dur_rec	Duration of recovery after coming off ventilation. Default = 3
dur_R	Mean duration of immunity (days). Default = Inf
hosp_bed_capacity	General bed capacity. Can be single number or vector if capacity time-varies.
ICU_bed_capacity	ICU bed capacity. Can be single number or vector if capacity time-varies.
tt_hosp_beds	Times at which hospital bed capacity changes (Default = 0 = doesn't change)
tt_ICU_beds	Times at which ICU bed capacity changes (Default = 0 = doesn't change)
seeding_cases	Initial number of cases seeding the epidemic
mod_gen	An odin model generation function. Default: 'explicit_SEIR_deterministic'

Value

Simulation output

Examples

## Not run: 
pop <- get_population("Afghanistan")
m <- get_mixing_matrix("Afghanistan")
run_deterministic_SEIR_model(pop$n, m, c(0, 50), c(3, 3/2), 365, 100000,
1000000)

## End(Not run)

mrc-ide/squire documentation built on Sept. 10, 2022, 1:11 a.m.