tests/testthat/helper_taspprepodin.R
In Geidelberg/cotonou:
# helper files have functions that will be used a lot in the model tests
par_gridplot2 = function(result, parm) {
require(plyr)
fc_df = aperm(result[parm][[1]], c(2, 3, 1))
fc_df_list = alply(fc_df, 3)
fc_df_list_applied = lapply(fc_df_list, function(x) {colnames(x) = rownames(x) = c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou")
return(x)})
dat = data.frame(row =
rep(c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou"), 1, each = 9),
col =
rep(c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou"), 9),
value = unlist(lapply(fc_df_list_applied, c)),
year = unlist(sort(rep(time, 81))))
dat$row = factor(dat$row, levels = c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou"))
dat$col = factor(dat$col, levels = c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou"))
return(ggplot(dat, aes(x = year, y = value, color = value)) + geom_line(size = 2) + facet_grid(row~col) + theme_bw())
}
# best_set_default --------------------------------------------------------
best_set_default = list(
init_clientN_from_PCR=0,
initial_Ntot = 286114,
frac_women_ProFSW = 0.0024,
frac_women_LowFSW = 0.0027,
frac_women_exFSW = 0.0024,
frac_men_client = 0.2,
frac_women_virgin = 0.1,
frac_men_virgin = 0.1,
prev_init_FSW = 0.0326,
prev_init_rest = 0.0012,
# N_init = c(672, 757, 130895, 672, 27124, 100305, 14544, 11145, 0),
# fraction_F = 0.5,
fraction_F = 0.515666224,
epsilon_1985 = 0.059346131 * 1.5,
epsilon_1992 = 0.053594832 * 1.5,
epsilon_2002 = 0.026936907 * 1.5,
epsilon_2013 = 0.026936907 * 1.5,
epsilon_2016 = 0.026936907 * 1.5,
# mu = c(0.02597403, 0.02597403, 0.02597403, 0.02597403, 0.02739726, 0.02739726, 0.02597403, 0.02739726, 0.02597403), # women 1/((27 + 50)/2) # men 1/((25 + 48)/2)
# c_comm = c(750, 52, 0, 0, 13.5, 0, 0, 0, 0),
# c_noncomm = c(0.38, 0.38, 0.88, 0.88, 4, 1.065, 0, 0, 0), # partner change rate lowlevel FSW same as pro, others are approximations from various surveys
#
muF = 0.02597403,
muM = 0.02739726,
# PARTNER CHANGE RATE
c_comm_1985 = c(1229.5, 52, 0, 0, 10.15873, 0, 0, 0, 0), # (1020 + 1439)/2
c_comm_1993 = c(1229.5, 52, 0, 0, 10.15873, 0, 0, 0, 0), # (1020 + 1439)/2
c_comm_1995 = c(1280, 52, 0, 0, 10.15873, 0, 0, 0, 0), # (1135 + 1425)/2
c_comm_1998 = c(881, 52, 0, 0, 10.15873, 0, 0, 0, 0), # (757 + 1005)/2
c_comm_2002 = c(598.5, 52, 0, 0, 11.08109, 0, 0, 0, 0), # (498 + 699)/2, (13.387-10.15873)/14 * 4 + 10.15873
c_comm_2005 = c(424, 52, 0, 0, 11.77286, 0, 0, 0, 0), # (366 + 482)/2, (13.387-10.15873)/14 * 7 + 10.15873
c_comm_2008 = c(371.5, 52, 0, 0, 12.46464, 0, 0, 0, 0), # (272 + 471)/2, (13.387-10.15873)/14 * 10 + 10.15873
c_comm_2012 = c(541, 52, 0, 0, 13.387, 0, 0, 0, 0), # (459 + 623)/2
c_comm_2015 = c(400, 52, 0, 0, 17.15294, 0, 0, 0, 0), # (309 + 491)/2
c_comm_2016 = c(400, 52, 0, 0, 17.15294, 0, 0, 0, 0), # (309 + 491)/2
c_noncomm_1985 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0), # (0.4682779 + 0.3886719 + 0.2729358)/3
c_noncomm_1993 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_1995 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_1998 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_2002 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_2005 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_2008 = c(0.3766285, 0.3766285, 0.7943578, 0.7943578, 2.028986, 0.7878543, 0, 0, 0),
c_noncomm_2012 = c(0.3766285, 0.3766285, 0.7943578, 0.7943578, 8.086957, 0.7878543, 0, 0, 0),
c_noncomm_2015 = c(0.3766285, 0.3766285, 0.7943578, 0.7943578, 6.258258, 0.7878543, 0, 0, 0),
c_noncomm_2016 = c(0.3766285, 0.3766285, 0.7943578, 0.7943578, 6.258258, 0.7878543, 0, 0, 0),
#think about transforming to matrix
betaMtoF_comm = 0.00051, # RR circumcision = 0.44
betaFtoM_comm = 0.02442*0.44,
betaMtoF_noncomm = 0.003,
betaFtoM_noncomm = 0.0038*0.44,
infect_acute = 9, # RR for acute phase
infect_AIDS = 2, #7.27, # RR for AIDS phase
infect_ART = c(0, rep_len(0, 8)),
ec = rep_len(0.8, 9), # from kate's paper on nigeria SD couples
eP0 = c(0, rep_len(0, 8)), # assumptions!
eP1a = c(0.9, rep_len(0, 8)),
eP1b = c(0.45, rep_len(0, 8)),
eP1c = c(0, rep_len(0, 8)),
eP1d = c(0, rep_len(0, 8)),
dur_primary_phase = 0.4166667, # years
SC_to_death = 10,
dur_200_349 = 4.45, # years
kappaa = rep(0.2, 9),
kappab = rep(0.2, 9),
kappac = rep(0.2, 9),
kappa1 = rep(0.2, 9),
alpha01 = rep_len(0, 9),
alpha02 = rep_len(0, 9),
alpha03 = 0.03,
alpha04 = 0.07,
dur_below_200 = rep_len(0.27, 9), #1/2.9
alpha11 = rep_len(0, 9),
alpha22 = rep_len(0, 9),
alpha23 = rep_len(0.05, 9),
alpha24 = rep_len(0.08, 9),
alpha25 = rep_len(0.27, 9),
alpha32 = rep_len(0, 9),
alpha33 = rep_len(0.05, 9),
alpha34 = rep_len(0.08, 9),
alpha35 = rep_len(0.27, 9),
alpha42 = rep_len(0, 9),
alpha43 = rep_len(0.05, 9),
alpha44 = rep_len(0.08, 9),
alpha45 = rep_len(0.27, 9),
#PREP
zetaa_t = c(1985, 2013, 2015, 2016),
zetaa_y = matrix(c(rep(0, 9), 0, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
zetab_t = c(1985, 2013, 2015, 2016),
zetab_y = matrix(c(rep(0, 9), 0, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
zetac_t = c(1985, 2013, 2015, 2016),
zetac_y = matrix(c(rep(0, 9), 0, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
# zetac_y = matrix(c(rep(0, 9), 0.0075, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
psia = rep_len(0.1,9),
psib = rep_len(0.1,9),
#TESTING
test_rate_prep = c(4, 0, 0, 0, 0, 0, 0, 0, 0),
sigma = c(0.85, 0, 0, 0, 0, 0, 0, 0, 0),
prep_intervention_t = c(1985, 2013, 2015, 2016),
prep_intervention_y = matrix(c(rep(0, 9), 1, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
testing_prob_t = c(1985, 2001, 2005, 2006, 2008, 2012, 2013, 2015, 2016),
# testing_prob_y = matrix(c(0, 0, 0, 0, 0, 0, 0, 0, 0, # 1985 columns are the risk groups
# 0, 0, 0, 0, 0, 0, 0, 0, 0, # 2001
# 0, 0, 0, 0, 0, 0, 0, 0, 0, # 2005
# 0.142, 0.142, 0.142, 0.142, 0.142, 0.142, 0, 0, 0, # 2006 0.653/8 slope
# 0.21, 0.21, 0.21, 0.21, 0.21, 0.21, 0, 0, 0, # 2008 3*0.653/8
# 0.331, 0.331, 0.331, 0.331, 0.331, 0.331, 0, 0, 0, # 2012 7*0.653/8
# 0.331, 0.331, 0.331, 0.331, 0.331, 0.331, 0, 0, 0, # 2013
# 0.331, 0.331, 0.331, 0.331, 0.331, 0.331, 0, 0, 0, # 2015
# 0.331, 0.331, 0.331, 0.331, 0.331, 0.331, 0, 0, 0), # 2016
# nrow = 9, ncol = 9, byrow = T),
testing_prob_y = matrix(c(0, 0, 0, 0, 0, 0, 0, 0, 0, # 1985 columns are the risk groups
0, 0, 0, 0, 0, 0, 0, 0, 0, # 2001
0, 0, 0, 0, 0, 0, 0, 0, 0, # 2005
0.081625, 0.142, 0.142, 0.142, 0.0975, 0.0975, 0, 0, 0, # 2006 0.653/8 slope
0.244875, 0.21, 0.21, 0.21, 0.1, 0.1, 0, 0, 0, # 2008 3*0.653/8
0.571375, 0.331, 0.331, 0.331, 0.0582, 0.0582, 0, 0, 0, # 2012 7*0.653/8
0.653, 0.331, 0.331, 0.331, 0.0582, 0.0582, 0, 0, 0, # 2013
0.68, 0.331, 0.331, 0.331, 0.0582, 0.0582, 0, 0, 0, # 2015
0.68, 0.331, 0.331, 0.331, 0.0582, 0.0582, 0, 0, 0), # 2016
nrow = 9, ncol = 9, byrow = T),
#ART
ART_prob_t = c(1985, 2002, 2005, 2016),
# ART_prob_y = matrix(c(0, 0, 0, 0, 0, 0, 0, 0, 0, # 1985
# 0, 0, 0, 0, 0, 0, 0, 0, 0, # 2002
# 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0, 0, 0, # 2005 0.676/14 * 3
# 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0),
# nrow = 4, ncol = 9, byrow = T), # 2016 GP: (0.8+0.552)/2
ART_prob_y = matrix(c(0, 0, 0, 0, 0, 0, 0, 0, 0, # 1985
0, 0, 0, 0, 0, 0, 0, 0, 0, # 2002
0, 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0, 0, 0, # 2005 0.676/14 * 3
0.6739, 0.676, 0.676, 0.676, 0.676, 0.676, 0, 0, 0),
nrow = 4, ncol = 9, byrow = T), # 2016 GP: (0.8+0.552)/2
RR_ART_CD4200 = 5.39,
phi2 = c(0.105360516, rep_len(0.025,8)), # former sex workers drop out rate??!
phi3 = c(0.105360516, rep_len(0.025,8)),
phi4 = c(0.105360516, rep_len(0.025,8)),
phi5 = c(0.105360516, rep_len(0.025,8)),
ART_RR_prog = 10,
# ART_RR_mort = (1.3+3.45)/2,
#CONDOM
fc_y_comm_1985 = matrix(
c(0, 0, 0, 0, 0.145524, 0, 0, 0, 0, # 0.145524 is using John's FSW condom 1989 as prop of 1993, * our measure of 1993
0, 0, 0, 0, 0.145524, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.145524, 0.145524, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_1993 = matrix(
c(0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.536, 0.536, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_1995 = matrix(
c(0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.536, 0.536, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_1998 = matrix(
c(0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.536, 0.536, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2002 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2005 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2008 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2012 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2015 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2015 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_1985 = matrix(
c(0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_1993 = matrix(
c(0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
# 1998
# (0.33 + 0.2705314)/ 2 # average FSW client
# (0.0326087 + 0.2705314)/ 2 # average client GPF
# (0.0326087 + 0.04989035) / 2 # average gpm gpf
fc_y_noncomm_1998 = matrix(
c(0, 0, 0, 0, 0.3002657, 0, 0, 0, 0,
0, 0, 0, 0, 0.3002657, 0, 0, 0, 0,
0, 0, 0, 0, 0.15157, 0.04124952, 0, 0, 0,
0, 0, 0, 0, 0.15157, 0.04124952, 0, 0, 0,
0.3002657, 0.3002657, 0.15157, 0.15157, 0, 0, 0, 0, 0,
0, 0, 0.04124952, 0.04124952, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
# 2008
# (0.33 + 0.4)/ 2 # average FSW client (both approx)
# ((0.05042017+0.241404781)/2 + 0.4)/ 2 # average client GPF (gpf averaged from 2 estimtes)
# ((0.05042017+0.241404781)/2 + (0.07103825+0.34838295)/2) / 2 # average gpm gpf
fc_y_noncomm_2002 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_2008 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_2011 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_2015 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_2016 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_t_comm = c(1985, 1993, 1995, 1998, 2002, 2005, 2008, 2012, 2015, 2016),
fc_t_noncomm = c(1985, 1993, 1998, 2002, 2008, 2011, 2015, 2016),
n_y_comm_1985 = matrix(
c(0.01), ncol=9, nrow = 9),
n_y_comm_2002 = matrix(
c(0.01), ncol=9, nrow = 9),
n_y_comm_2015 = matrix(
c(0.02), ncol=9, nrow = 9),
n_y_comm_2016 = matrix(
c(0.01), ncol=9, nrow = 9),
n_t_comm = c(1985, 2002, 2015, 2016),
n_y_noncomm_1985 = matrix(
c(0.01), ncol=9, nrow = 9),
n_y_noncomm_2002 = matrix(
c(0.02), ncol=9, nrow = 9),
n_y_noncomm_2015 = matrix(
c(0.01), ncol=9, nrow = 9),
n_y_noncomm_2016 = matrix(
c(0.01), ncol=9, nrow = 9),
n_t_noncomm = c(1985, 1998, 2002, 2011, 2015, 2016),
rate_leave_pro_FSW = 0.2,
FSW_leave_Cotonou_fraction = 0.1,
rate_leave_low_FSW = 0.1,
rate_leave_client = 0.05,
dropout_rate_not_FSW = 0.025,
dropout_rate_FSW = 0.025,
replaceDeaths = 0,
movement = 1,
ART_recruit_rate_rest = 0.25,
ART_recruit_rate_FSW = 0.25,
ART_reinit_rate_FSW = 0.2,
ART_reinit_rate_rest = 0.2
)
par_seq_default = c("c_comm", "c_noncomm")
condom_seq_default = c("fc_y_comm", "fc_y_noncomm")
groups_seq_default = c("ProFSW", "LowFSW", "GPF", "FormerFSW", "Client", "GPM", "VirginF", "VirginM", "FormerFSWoutside")
years_seq_default = seq(1985, 2016)
time_default <- seq(1986, 2020, length.out = 35)
# ranges_default ----------------------------------------------------------
ranges_default = rbind(
# MISC
init_clientN_from_PCR = c(0,0),
who_believe_comm = c(0, 1),
# DEMOGRAPHIC
fraction_F = c(0.512, 0.52), # fraction of population born female
frac_women_ProFSW = c(0.0024, 0.0143), # fraction of women that are professional FSW
frac_men_client = c(0.151, 0.4), # fraction of men that are clients
frac_women_virgin = c(0.079, 0.2), # fraction of women that are virgins
frac_men_virgin = c(0.070, 0.17), # fraction of men that are virgins
prev_init_FSW = c(0.0132, 0.0659), # initial prevalence of FSW
prev_init_rest = c(0.000313, 0.00294), # initial prevalence of the other groups
# growth rates
epsilon_1985 = c(0.08, 0.08),
epsilon_1992 = c(0.08, 0.08),
epsilon_2002 = c(0.06, 0.07),
epsilon_2013 = c(0.04, 0.06),
epsilon_2016 = c(0.04, 0.06),
muF = c(0.01851852, 0.025), # female mortality
muM = c(0.01851852, 0.025), # male mortality
rate_leave_pro_FSW = c(0, 1), # rate of exit of professional sex work
rate_leave_low_FSW = c(0, 1), # rate of exit of low level sex work
fraction_FSW_foreign = c(0.5, 0.9),
rate_leave_client = c(0, 0.189), # rate of exit of clients
rate_enter_sexual_pop_F = c(1/(20-15), 1/(17-15)), # rate of entering sexual population women
rate_enter_sexual_pop_M = c(1/(20-15), 1/(17-15)), # rate of entering sexual population men
fraction_sexually_active_15_F = c(0.119, 0.17), # fraction of 15 year old women sexually active
fraction_sexually_active_15_M = c(0.18, 0.35), # fraction of 15 year old men sexually active
# BEHAVIOURAL
# commercial partnerships
c_comm_1993_ProFSW = c(192, 1277),
c_comm_2005_ProFSW = c(81, 562),
# c_comm_2015_ProFSW = c(71, 501),
c_comm_1998_Client = c(8.39, 11.9),
c_comm_2012_Client = c(11.8, 15),
c_comm_2015_Client = c(14.5, 19.8),
#non commercial partnerships
c_non_comm_1985_ProFSW = c(0.31, 0.86),
c_non_comm_1985_LowFSW = c(0.41, 1.04),
c_non_comm_1985_Client= c(1.6, 7.9),
c_noncomm_1998_GPF = c(0.93, 0.99),
c_noncomm_2008_GPF = c(0.77, 0.82),
c_noncomm_1998_GPM = c(1.24, 1.43),
c_noncomm_2008_GPM = c(0.73, 0.84),
# sex acts per partnership comm
n_y_comm_1985_ProFSW_Client = c(1, 10.23),
n_y_comm_1985_Client_ProFSW = c(1.45, 11.45),
n_y_comm_1985_LowFSW_Client = c(1, 1),
n_y_comm_1985_Client_LowFSW = c(1, 1),
# sex acts per partnership noncomm
n_y_noncomm_2002_ProFSW_Client = c(13, 20),
n_y_noncomm_2015_ProFSW_Client = c(38.2, 60),
n_y_noncomm_1985_GPF_GPM = c(29, 43.7),
n_y_noncomm_1985_GPM_GPF = c(19.4, 46.7),
#BETA
betaMtoF_baseline = c(0.0006, 0.00109), # baseline male to female transmission rate
RR_beta_FtM = c(0.53, 2), # RR for transmission female to male
RR_beta_HSV2_comm = c(1.4, 2.1), # RR for commercial sex acts where the susceptible individual is infected HSV2
RR_beta_HSV2_noncomm = c(2.2, 3.4), # RR for non commercial sex acts where the susceptible individual is infected HSV2
prev_HSV2_FSW = c(0.8687271, 0.9403027), # prevalence HSV2 in FSW
prev_HSV2_Client = c(0.14, 0.8687271), # prevalence HSV2 in clients
prev_HSV2_GPF = c(0.2666742, 0.3236852), # prevalence of HSV2 in GPF
prev_HSV2_GPM = c(0.09843545, 0.14108970), # prevalence of HSV2 in GPM
RR_beta_circum = c(0.34, 0.72), # RR for transmission if susceptible individual is circumcised
# Progression parameters
infect_acute = c(4.47, 18.81), # RR for transmission rate if infected is acute stage
infect_AIDS = c(4.45, 11.88), # RR for transmission rate if infected is in AIDS stage
eff_ART = c(0.96, 1), # infectiousness RR when on ART (efficacy ART assuimed 90% * % undetectable which is 52.3%)
ec = c(0.58, 0.95), # condom efficacy
eP1a = c(0.9, 0.9), # prep efficacy perfect adherence
eP1b = c(0, 0.9), # prep efficacy intermediate adherence
eP1c = c(0, 0), # prep efficacy poor adherence
SC_to_death = c(8.7, 12.3),
dur_200_349 = c(3.9, 5),
alpha03 = c(0.03, 0.07),
alpha04 = c(0.05, 0.12),
dur_below_200 = c(0.23, 0.33),
ART_RR_prog = c(8.8, 12.1),
# ART_RR_mort = c(1.3, 3.45),
dropout_rate_not_FSW = c(0.0233, 0.274),
dropout_rate_FSW = c(0.0233, 0.274),
# condoms
fc_y_comm_1985_ProFSW_Client = c(0, 0),
fc_y_comm_1993_ProFSW_Client = c(0.535, 0.687),
fc_y_comm_2002_ProFSW_Client = c(0.536, 0.992),
fc_y_noncomm_1985_ProFSW_Client = c(0, 0),
fc_y_noncomm_2002_ProFSW_Client = c(0.19, 0.62),
fc_y_noncomm_1985_GPF_GPM = 0,
fc_y_noncomm_1998_GPF_GPM = c(0.0326087, 0.05042017),
fc_y_noncomm_2011_GPF_GPM = c(0.161, 0.255),
viral_supp_y_2015_ProFSW = c(0.91, 0.92),
viral_supp_y_1986_rest = c(0.1, 0.2),
ART_eff = c(0.96, 1),
ART_recruit_rate_FSW = c(0.5, 1.5),
ART_recruit_rate_rest = c(0.5, 1.5),
ART_reinit_rate_FSW = c(0.25, 1.5),
ART_reinit_rate_rest = c(0.25, 1.5),
PrEPOnOff = 1
)
outputs_default = c("prev", "frac_N", "Ntot", "epsilon", "rate_leave_client", "alphaItot", "prev_FSW", "prev_LowFSW", "prev_client", "prev_men", "prev_women", "c_comm_balanced", "c_noncomm_balanced", "who_believe_comm")
parameter_names = names(lhs_parameters(1, par_seq = par_seq_default, condom_seq = condom_seq_default, groups_seq = groups_seq_default, years_seq = years_seq_default, set_pars = best_set_default, ranges = ranges_default, time = time_default)[[1]])
all_lambda_pars = c("c_comm", "p_comm", "N", "beta_comm", "R", "fc_comm",
"fP_comm", "n_comm", "eP0", "eP1a", "eP1b", "eP1c", "eP1d", "ec", "fc_noncomm", "fP_noncomm",
"n_noncomm", "c_noncomm", "p_noncomm", "infect_ART",
"infect_acute", "infect_AIDS", "beta_noncomm")
Geidelberg/cotonou documentation built on Aug. 29, 2020, 4:22 a.m.
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# helper files have functions that will be used a lot in the model tests
par_gridplot2 = function(result, parm) {
require(plyr)
fc_df = aperm(result[parm][[1]], c(2, 3, 1))
fc_df_list = alply(fc_df, 3)
fc_df_list_applied = lapply(fc_df_list, function(x) {colnames(x) = rownames(x) = c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou")
return(x)})
dat = data.frame(row =
rep(c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou"), 1, each = 9),
col =
rep(c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou"), 9),
value = unlist(lapply(fc_df_list_applied, c)),
year = unlist(sort(rep(time, 81))))
dat$row = factor(dat$row, levels = c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou"))
dat$col = factor(dat$col, levels = c("Pro FSW", "Low-level FSW", "GPF", "Former FSW in Cotonou", "Clients",
"GPM", "Virgin female", "Virgin male", "Former FSW outside Cotonou"))
return(ggplot(dat, aes(x = year, y = value, color = value)) + geom_line(size = 2) + facet_grid(row~col) + theme_bw())
}
# best_set_default --------------------------------------------------------
best_set_default = list(
init_clientN_from_PCR=0,
initial_Ntot = 286114,
frac_women_ProFSW = 0.0024,
frac_women_LowFSW = 0.0027,
frac_women_exFSW = 0.0024,
frac_men_client = 0.2,
frac_women_virgin = 0.1,
frac_men_virgin = 0.1,
prev_init_FSW = 0.0326,
prev_init_rest = 0.0012,
# N_init = c(672, 757, 130895, 672, 27124, 100305, 14544, 11145, 0),
# fraction_F = 0.5,
fraction_F = 0.515666224,
epsilon_1985 = 0.059346131 * 1.5,
epsilon_1992 = 0.053594832 * 1.5,
epsilon_2002 = 0.026936907 * 1.5,
epsilon_2013 = 0.026936907 * 1.5,
epsilon_2016 = 0.026936907 * 1.5,
# mu = c(0.02597403, 0.02597403, 0.02597403, 0.02597403, 0.02739726, 0.02739726, 0.02597403, 0.02739726, 0.02597403), # women 1/((27 + 50)/2) # men 1/((25 + 48)/2)
# c_comm = c(750, 52, 0, 0, 13.5, 0, 0, 0, 0),
# c_noncomm = c(0.38, 0.38, 0.88, 0.88, 4, 1.065, 0, 0, 0), # partner change rate lowlevel FSW same as pro, others are approximations from various surveys
#
muF = 0.02597403,
muM = 0.02739726,
# PARTNER CHANGE RATE
c_comm_1985 = c(1229.5, 52, 0, 0, 10.15873, 0, 0, 0, 0), # (1020 + 1439)/2
c_comm_1993 = c(1229.5, 52, 0, 0, 10.15873, 0, 0, 0, 0), # (1020 + 1439)/2
c_comm_1995 = c(1280, 52, 0, 0, 10.15873, 0, 0, 0, 0), # (1135 + 1425)/2
c_comm_1998 = c(881, 52, 0, 0, 10.15873, 0, 0, 0, 0), # (757 + 1005)/2
c_comm_2002 = c(598.5, 52, 0, 0, 11.08109, 0, 0, 0, 0), # (498 + 699)/2, (13.387-10.15873)/14 * 4 + 10.15873
c_comm_2005 = c(424, 52, 0, 0, 11.77286, 0, 0, 0, 0), # (366 + 482)/2, (13.387-10.15873)/14 * 7 + 10.15873
c_comm_2008 = c(371.5, 52, 0, 0, 12.46464, 0, 0, 0, 0), # (272 + 471)/2, (13.387-10.15873)/14 * 10 + 10.15873
c_comm_2012 = c(541, 52, 0, 0, 13.387, 0, 0, 0, 0), # (459 + 623)/2
c_comm_2015 = c(400, 52, 0, 0, 17.15294, 0, 0, 0, 0), # (309 + 491)/2
c_comm_2016 = c(400, 52, 0, 0, 17.15294, 0, 0, 0, 0), # (309 + 491)/2
c_noncomm_1985 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0), # (0.4682779 + 0.3886719 + 0.2729358)/3
c_noncomm_1993 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_1995 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_1998 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_2002 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_2005 = c(0.3766285, 0.3766285, 0.9610526, 0.9610526, 2.028986, 1.337444, 0, 0, 0),
c_noncomm_2008 = c(0.3766285, 0.3766285, 0.7943578, 0.7943578, 2.028986, 0.7878543, 0, 0, 0),
c_noncomm_2012 = c(0.3766285, 0.3766285, 0.7943578, 0.7943578, 8.086957, 0.7878543, 0, 0, 0),
c_noncomm_2015 = c(0.3766285, 0.3766285, 0.7943578, 0.7943578, 6.258258, 0.7878543, 0, 0, 0),
c_noncomm_2016 = c(0.3766285, 0.3766285, 0.7943578, 0.7943578, 6.258258, 0.7878543, 0, 0, 0),
#think about transforming to matrix
betaMtoF_comm = 0.00051, # RR circumcision = 0.44
betaFtoM_comm = 0.02442*0.44,
betaMtoF_noncomm = 0.003,
betaFtoM_noncomm = 0.0038*0.44,
infect_acute = 9, # RR for acute phase
infect_AIDS = 2, #7.27, # RR for AIDS phase
infect_ART = c(0, rep_len(0, 8)),
ec = rep_len(0.8, 9), # from kate's paper on nigeria SD couples
eP0 = c(0, rep_len(0, 8)), # assumptions!
eP1a = c(0.9, rep_len(0, 8)),
eP1b = c(0.45, rep_len(0, 8)),
eP1c = c(0, rep_len(0, 8)),
eP1d = c(0, rep_len(0, 8)),
dur_primary_phase = 0.4166667, # years
SC_to_death = 10,
dur_200_349 = 4.45, # years
kappaa = rep(0.2, 9),
kappab = rep(0.2, 9),
kappac = rep(0.2, 9),
kappa1 = rep(0.2, 9),
alpha01 = rep_len(0, 9),
alpha02 = rep_len(0, 9),
alpha03 = 0.03,
alpha04 = 0.07,
dur_below_200 = rep_len(0.27, 9), #1/2.9
alpha11 = rep_len(0, 9),
alpha22 = rep_len(0, 9),
alpha23 = rep_len(0.05, 9),
alpha24 = rep_len(0.08, 9),
alpha25 = rep_len(0.27, 9),
alpha32 = rep_len(0, 9),
alpha33 = rep_len(0.05, 9),
alpha34 = rep_len(0.08, 9),
alpha35 = rep_len(0.27, 9),
alpha42 = rep_len(0, 9),
alpha43 = rep_len(0.05, 9),
alpha44 = rep_len(0.08, 9),
alpha45 = rep_len(0.27, 9),
#PREP
zetaa_t = c(1985, 2013, 2015, 2016),
zetaa_y = matrix(c(rep(0, 9), 0, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
zetab_t = c(1985, 2013, 2015, 2016),
zetab_y = matrix(c(rep(0, 9), 0, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
zetac_t = c(1985, 2013, 2015, 2016),
zetac_y = matrix(c(rep(0, 9), 0, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
# zetac_y = matrix(c(rep(0, 9), 0.0075, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
psia = rep_len(0.1,9),
psib = rep_len(0.1,9),
#TESTING
test_rate_prep = c(4, 0, 0, 0, 0, 0, 0, 0, 0),
sigma = c(0.85, 0, 0, 0, 0, 0, 0, 0, 0),
prep_intervention_t = c(1985, 2013, 2015, 2016),
prep_intervention_y = matrix(c(rep(0, 9), 1, rep(0, 9-1), rep(0, 9), rep(0, 9)), ncol = 9, byrow = T),
testing_prob_t = c(1985, 2001, 2005, 2006, 2008, 2012, 2013, 2015, 2016),
# testing_prob_y = matrix(c(0, 0, 0, 0, 0, 0, 0, 0, 0, # 1985 columns are the risk groups
# 0, 0, 0, 0, 0, 0, 0, 0, 0, # 2001
# 0, 0, 0, 0, 0, 0, 0, 0, 0, # 2005
# 0.142, 0.142, 0.142, 0.142, 0.142, 0.142, 0, 0, 0, # 2006 0.653/8 slope
# 0.21, 0.21, 0.21, 0.21, 0.21, 0.21, 0, 0, 0, # 2008 3*0.653/8
# 0.331, 0.331, 0.331, 0.331, 0.331, 0.331, 0, 0, 0, # 2012 7*0.653/8
# 0.331, 0.331, 0.331, 0.331, 0.331, 0.331, 0, 0, 0, # 2013
# 0.331, 0.331, 0.331, 0.331, 0.331, 0.331, 0, 0, 0, # 2015
# 0.331, 0.331, 0.331, 0.331, 0.331, 0.331, 0, 0, 0), # 2016
# nrow = 9, ncol = 9, byrow = T),
testing_prob_y = matrix(c(0, 0, 0, 0, 0, 0, 0, 0, 0, # 1985 columns are the risk groups
0, 0, 0, 0, 0, 0, 0, 0, 0, # 2001
0, 0, 0, 0, 0, 0, 0, 0, 0, # 2005
0.081625, 0.142, 0.142, 0.142, 0.0975, 0.0975, 0, 0, 0, # 2006 0.653/8 slope
0.244875, 0.21, 0.21, 0.21, 0.1, 0.1, 0, 0, 0, # 2008 3*0.653/8
0.571375, 0.331, 0.331, 0.331, 0.0582, 0.0582, 0, 0, 0, # 2012 7*0.653/8
0.653, 0.331, 0.331, 0.331, 0.0582, 0.0582, 0, 0, 0, # 2013
0.68, 0.331, 0.331, 0.331, 0.0582, 0.0582, 0, 0, 0, # 2015
0.68, 0.331, 0.331, 0.331, 0.0582, 0.0582, 0, 0, 0), # 2016
nrow = 9, ncol = 9, byrow = T),
#ART
ART_prob_t = c(1985, 2002, 2005, 2016),
# ART_prob_y = matrix(c(0, 0, 0, 0, 0, 0, 0, 0, 0, # 1985
# 0, 0, 0, 0, 0, 0, 0, 0, 0, # 2002
# 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0, 0, 0, # 2005 0.676/14 * 3
# 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0),
# nrow = 4, ncol = 9, byrow = T), # 2016 GP: (0.8+0.552)/2
ART_prob_y = matrix(c(0, 0, 0, 0, 0, 0, 0, 0, 0, # 1985
0, 0, 0, 0, 0, 0, 0, 0, 0, # 2002
0, 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0.1448571, 0, 0, 0, # 2005 0.676/14 * 3
0.6739, 0.676, 0.676, 0.676, 0.676, 0.676, 0, 0, 0),
nrow = 4, ncol = 9, byrow = T), # 2016 GP: (0.8+0.552)/2
RR_ART_CD4200 = 5.39,
phi2 = c(0.105360516, rep_len(0.025,8)), # former sex workers drop out rate??!
phi3 = c(0.105360516, rep_len(0.025,8)),
phi4 = c(0.105360516, rep_len(0.025,8)),
phi5 = c(0.105360516, rep_len(0.025,8)),
ART_RR_prog = 10,
# ART_RR_mort = (1.3+3.45)/2,
#CONDOM
fc_y_comm_1985 = matrix(
c(0, 0, 0, 0, 0.145524, 0, 0, 0, 0, # 0.145524 is using John's FSW condom 1989 as prop of 1993, * our measure of 1993
0, 0, 0, 0, 0.145524, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.145524, 0.145524, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_1993 = matrix(
c(0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.536, 0.536, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_1995 = matrix(
c(0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.536, 0.536, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_1998 = matrix(
c(0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0.536, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.536, 0.536, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2002 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2005 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2008 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2012 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2015 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_comm_2015 = matrix(
c(0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0.8, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0.8, 0.8, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_1985 = matrix(
c(0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_1993 = matrix(
c(0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
# 1998
# (0.33 + 0.2705314)/ 2 # average FSW client
# (0.0326087 + 0.2705314)/ 2 # average client GPF
# (0.0326087 + 0.04989035) / 2 # average gpm gpf
fc_y_noncomm_1998 = matrix(
c(0, 0, 0, 0, 0.3002657, 0, 0, 0, 0,
0, 0, 0, 0, 0.3002657, 0, 0, 0, 0,
0, 0, 0, 0, 0.15157, 0.04124952, 0, 0, 0,
0, 0, 0, 0, 0.15157, 0.04124952, 0, 0, 0,
0.3002657, 0.3002657, 0.15157, 0.15157, 0, 0, 0, 0, 0,
0, 0, 0.04124952, 0.04124952, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
# 2008
# (0.33 + 0.4)/ 2 # average FSW client (both approx)
# ((0.05042017+0.241404781)/2 + 0.4)/ 2 # average client GPF (gpf averaged from 2 estimtes)
# ((0.05042017+0.241404781)/2 + (0.07103825+0.34838295)/2) / 2 # average gpm gpf
fc_y_noncomm_2002 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_2008 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_2011 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_2015 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_y_noncomm_2016 = matrix(
c(0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.365, 0, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0, 0, 0, 0, 0.2729562, 0.1778115, 0, 0, 0,
0.365, 0.365, 0.2729562, 0.2729562, 0, 0, 0, 0, 0,
0, 0, 0.1778115, 0.1778115, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), nrow = 9),
fc_t_comm = c(1985, 1993, 1995, 1998, 2002, 2005, 2008, 2012, 2015, 2016),
fc_t_noncomm = c(1985, 1993, 1998, 2002, 2008, 2011, 2015, 2016),
n_y_comm_1985 = matrix(
c(0.01), ncol=9, nrow = 9),
n_y_comm_2002 = matrix(
c(0.01), ncol=9, nrow = 9),
n_y_comm_2015 = matrix(
c(0.02), ncol=9, nrow = 9),
n_y_comm_2016 = matrix(
c(0.01), ncol=9, nrow = 9),
n_t_comm = c(1985, 2002, 2015, 2016),
n_y_noncomm_1985 = matrix(
c(0.01), ncol=9, nrow = 9),
n_y_noncomm_2002 = matrix(
c(0.02), ncol=9, nrow = 9),
n_y_noncomm_2015 = matrix(
c(0.01), ncol=9, nrow = 9),
n_y_noncomm_2016 = matrix(
c(0.01), ncol=9, nrow = 9),
n_t_noncomm = c(1985, 1998, 2002, 2011, 2015, 2016),
rate_leave_pro_FSW = 0.2,
FSW_leave_Cotonou_fraction = 0.1,
rate_leave_low_FSW = 0.1,
rate_leave_client = 0.05,
dropout_rate_not_FSW = 0.025,
dropout_rate_FSW = 0.025,
replaceDeaths = 0,
movement = 1,
ART_recruit_rate_rest = 0.25,
ART_recruit_rate_FSW = 0.25,
ART_reinit_rate_FSW = 0.2,
ART_reinit_rate_rest = 0.2
)
par_seq_default = c("c_comm", "c_noncomm")
condom_seq_default = c("fc_y_comm", "fc_y_noncomm")
groups_seq_default = c("ProFSW", "LowFSW", "GPF", "FormerFSW", "Client", "GPM", "VirginF", "VirginM", "FormerFSWoutside")
years_seq_default = seq(1985, 2016)
time_default <- seq(1986, 2020, length.out = 35)
# ranges_default ----------------------------------------------------------
ranges_default = rbind(
# MISC
init_clientN_from_PCR = c(0,0),
who_believe_comm = c(0, 1),
# DEMOGRAPHIC
fraction_F = c(0.512, 0.52), # fraction of population born female
frac_women_ProFSW = c(0.0024, 0.0143), # fraction of women that are professional FSW
frac_men_client = c(0.151, 0.4), # fraction of men that are clients
frac_women_virgin = c(0.079, 0.2), # fraction of women that are virgins
frac_men_virgin = c(0.070, 0.17), # fraction of men that are virgins
prev_init_FSW = c(0.0132, 0.0659), # initial prevalence of FSW
prev_init_rest = c(0.000313, 0.00294), # initial prevalence of the other groups
# growth rates
epsilon_1985 = c(0.08, 0.08),
epsilon_1992 = c(0.08, 0.08),
epsilon_2002 = c(0.06, 0.07),
epsilon_2013 = c(0.04, 0.06),
epsilon_2016 = c(0.04, 0.06),
muF = c(0.01851852, 0.025), # female mortality
muM = c(0.01851852, 0.025), # male mortality
rate_leave_pro_FSW = c(0, 1), # rate of exit of professional sex work
rate_leave_low_FSW = c(0, 1), # rate of exit of low level sex work
fraction_FSW_foreign = c(0.5, 0.9),
rate_leave_client = c(0, 0.189), # rate of exit of clients
rate_enter_sexual_pop_F = c(1/(20-15), 1/(17-15)), # rate of entering sexual population women
rate_enter_sexual_pop_M = c(1/(20-15), 1/(17-15)), # rate of entering sexual population men
fraction_sexually_active_15_F = c(0.119, 0.17), # fraction of 15 year old women sexually active
fraction_sexually_active_15_M = c(0.18, 0.35), # fraction of 15 year old men sexually active
# BEHAVIOURAL
# commercial partnerships
c_comm_1993_ProFSW = c(192, 1277),
c_comm_2005_ProFSW = c(81, 562),
# c_comm_2015_ProFSW = c(71, 501),
c_comm_1998_Client = c(8.39, 11.9),
c_comm_2012_Client = c(11.8, 15),
c_comm_2015_Client = c(14.5, 19.8),
#non commercial partnerships
c_non_comm_1985_ProFSW = c(0.31, 0.86),
c_non_comm_1985_LowFSW = c(0.41, 1.04),
c_non_comm_1985_Client= c(1.6, 7.9),
c_noncomm_1998_GPF = c(0.93, 0.99),
c_noncomm_2008_GPF = c(0.77, 0.82),
c_noncomm_1998_GPM = c(1.24, 1.43),
c_noncomm_2008_GPM = c(0.73, 0.84),
# sex acts per partnership comm
n_y_comm_1985_ProFSW_Client = c(1, 10.23),
n_y_comm_1985_Client_ProFSW = c(1.45, 11.45),
n_y_comm_1985_LowFSW_Client = c(1, 1),
n_y_comm_1985_Client_LowFSW = c(1, 1),
# sex acts per partnership noncomm
n_y_noncomm_2002_ProFSW_Client = c(13, 20),
n_y_noncomm_2015_ProFSW_Client = c(38.2, 60),
n_y_noncomm_1985_GPF_GPM = c(29, 43.7),
n_y_noncomm_1985_GPM_GPF = c(19.4, 46.7),
#BETA
betaMtoF_baseline = c(0.0006, 0.00109), # baseline male to female transmission rate
RR_beta_FtM = c(0.53, 2), # RR for transmission female to male
RR_beta_HSV2_comm = c(1.4, 2.1), # RR for commercial sex acts where the susceptible individual is infected HSV2
RR_beta_HSV2_noncomm = c(2.2, 3.4), # RR for non commercial sex acts where the susceptible individual is infected HSV2
prev_HSV2_FSW = c(0.8687271, 0.9403027), # prevalence HSV2 in FSW
prev_HSV2_Client = c(0.14, 0.8687271), # prevalence HSV2 in clients
prev_HSV2_GPF = c(0.2666742, 0.3236852), # prevalence of HSV2 in GPF
prev_HSV2_GPM = c(0.09843545, 0.14108970), # prevalence of HSV2 in GPM
RR_beta_circum = c(0.34, 0.72), # RR for transmission if susceptible individual is circumcised
# Progression parameters
infect_acute = c(4.47, 18.81), # RR for transmission rate if infected is acute stage
infect_AIDS = c(4.45, 11.88), # RR for transmission rate if infected is in AIDS stage
eff_ART = c(0.96, 1), # infectiousness RR when on ART (efficacy ART assuimed 90% * % undetectable which is 52.3%)
ec = c(0.58, 0.95), # condom efficacy
eP1a = c(0.9, 0.9), # prep efficacy perfect adherence
eP1b = c(0, 0.9), # prep efficacy intermediate adherence
eP1c = c(0, 0), # prep efficacy poor adherence
SC_to_death = c(8.7, 12.3),
dur_200_349 = c(3.9, 5),
alpha03 = c(0.03, 0.07),
alpha04 = c(0.05, 0.12),
dur_below_200 = c(0.23, 0.33),
ART_RR_prog = c(8.8, 12.1),
# ART_RR_mort = c(1.3, 3.45),
dropout_rate_not_FSW = c(0.0233, 0.274),
dropout_rate_FSW = c(0.0233, 0.274),
# condoms
fc_y_comm_1985_ProFSW_Client = c(0, 0),
fc_y_comm_1993_ProFSW_Client = c(0.535, 0.687),
fc_y_comm_2002_ProFSW_Client = c(0.536, 0.992),
fc_y_noncomm_1985_ProFSW_Client = c(0, 0),
fc_y_noncomm_2002_ProFSW_Client = c(0.19, 0.62),
fc_y_noncomm_1985_GPF_GPM = 0,
fc_y_noncomm_1998_GPF_GPM = c(0.0326087, 0.05042017),
fc_y_noncomm_2011_GPF_GPM = c(0.161, 0.255),
viral_supp_y_2015_ProFSW = c(0.91, 0.92),
viral_supp_y_1986_rest = c(0.1, 0.2),
ART_eff = c(0.96, 1),
ART_recruit_rate_FSW = c(0.5, 1.5),
ART_recruit_rate_rest = c(0.5, 1.5),
ART_reinit_rate_FSW = c(0.25, 1.5),
ART_reinit_rate_rest = c(0.25, 1.5),
PrEPOnOff = 1
)
outputs_default = c("prev", "frac_N", "Ntot", "epsilon", "rate_leave_client", "alphaItot", "prev_FSW", "prev_LowFSW", "prev_client", "prev_men", "prev_women", "c_comm_balanced", "c_noncomm_balanced", "who_believe_comm")
parameter_names = names(lhs_parameters(1, par_seq = par_seq_default, condom_seq = condom_seq_default, groups_seq = groups_seq_default, years_seq = years_seq_default, set_pars = best_set_default, ranges = ranges_default, time = time_default)[[1]])
all_lambda_pars = c("c_comm", "p_comm", "N", "beta_comm", "R", "fc_comm",
"fP_comm", "n_comm", "eP0", "eP1a", "eP1b", "eP1c", "eP1d", "ec", "fc_noncomm", "fP_noncomm",
"n_noncomm", "c_noncomm", "p_noncomm", "infect_ART",
"infect_acute", "infect_AIDS", "beta_noncomm")
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