'survey' and 'sweep' outputs erroneously return 0 values for incidence and EIR

[IzzyRou]

Code to reproduce bug (using develop branch)

`
library(tidyverse)
library(devtools)

Set working directory to location of SIMPLEGEN and load

setwd("~/GitHub/SIMPLEGEN")
devtools::load_all()
check_SIMPLEGEN_loaded()

Define model parameters

set.seed(1)
n_demes <- 1
s <- simplegen_project() %>%
define_epi_model_parameters(
H = 1e3,
M = 1e4,
seed_infections = 10,
mig_mat = diag(1, 1),
prob_infection = 0.3,
prob_acute = seq(1, 0.0000000000, l = 30),
prob_AC = 1.0,
duration_acute = dgeom(1:250, 1 / 100),
duration_chronic = dgeom(1:250, 1 / 400),
detectability_microscopy_acute = 0.9,
detectability_microscopy_chronic = 0.45,
treatment_seeking_mean = 0,
infectivity_acute = 0.9,
infectivity_chronic = 0.45
)

Define sampling strategy

daily_dataframe <- rbind(data.frame(name = "acute_prev", deme = 1, state = "A", measure = "prevalence", diagnostic = c("microscopy", "PCR"), age_min = 2, age_max = 10),
data.frame(name = "chronic_prev", deme = 1, state = "C", measure = "prevalence", diagnostic = c("microscopy", "PCR"), age_min = 2, age_max = 10),
data.frame(name = "acute_inc", deme = 1, state = "A", measure = "incidence", diagnostic = "microscopy", age_min = 0, age_max = 5),
data.frame(name = "EIR", deme = 1, state = "H", measure = "EIR", diagnostic = NA, age_min = 0, age_max = 110),
make.row.names = FALSE)

sweep_dataframe <- rbind(data.frame(name = "prev_acute", time = 365, deme = 1, measure = "prevalence", state = "A", diagnostic = "PCR", age_min = seq(0, 100, 5), age_max = seq(0, 100, 5) + 4),
data.frame(name = "inc_acute", time = 365, deme = 1, measure = "incidence", state = "A", diagnostic = "microscopy", age_min = seq(0, 100, 5), age_max = seq(0, 100, 5) + 4),
data.frame(name = "EIR",time = 365, deme = 1, state = "H", measure = "EIR", diagnostic = NA, age_min = 0, age_max = 110),
make.row.names = FALSE)

df_survey<-data.frame(
t_start = 365,
t_end= 365+29,
reporting_interval = 30,
deme = 1 ,
measure = c("prevalence", "prevalence", "incidence","prevalence", "prevalence", "incidence"),
diagnostic = c("PCR","microscopy","microscopy","PCR","microscopy","microscopy") ,
sampling = c(NA,NA,"PCD",NA,NA,"PCD"),
age_min = c(0,0,0,2,2,0),
age_max = c(110,110,110,10,10,5),
sample_size = 1000

)

s <-
define_epi_sampling_parameters(project = s, surveys = df_survey, daily = daily_dataframe, sweep = sweep_dataframe)

Simulate from transmission model

s <- sim_epi(
s,
max_time = 2 * 365,
save_transmission_record = FALSE,
transmission_record_location = "ignore/trans_record.txt",
overwrite_transmission_record = TRUE
)

Note that EIR is listed as 0 when sampled at time = 365 days

s$epi_output$sweeps %>%
dplyr::filter(measure == "EIR")

Note that incidence in 0-5 and 0-110 years over the 30 day period beginning on time = 365 is listed as zero

s$epi_output$surveys %>%
dplyr::filter(measure == "incidence")

Yet at time = 365 the daily output lists EIR as 110.6 and incidence in 0 to 5 as 0.33

s$epi_output$daily %>%
dplyr::filter((measure == "incidence" |
measure == "EIR") & time == unique(s$epi_output$sweeps$time))

`