Simple immunity model for vaccination and infection events

This immunity model should only be used with vaccines and infection. The probability of successful exposure for vaccination events depends on the number of vaccines an individual has received prior to time t and their current age. If the individual is under the maximum vaccinations allotted and is of an age eligible for vaccination then the probability of a successful exposure event is 1. The probability of a successful infection event is dependent on the total number of infections that individual has experienced thus far. If the individual is under the maximum number of infections allotted then the probability of a successful exposure event is 1.

immunity_model_vacc_ifxn_simple(
  i,
  t,
  x,
  immune_histories,
  biomarker_states,
  demography,
  biomarker_map,
  model_pars,
  max_events = rep(Inf, dim(immune_histories)[3]),
  vacc_exposures = rep(Inf, dim(immune_histories)[3]),
  vacc_age,
  ...
)

Arguments

i

integer for the individual ID

t

integer for the time period

x

integer for the exposure ID

immune_histories

a 3D array of immune histories for all individuals, time steps and exposure IDs

biomarker_states

an 3D array of biomarker states (biomarker quantities) for all individuals, time steps and biomarker IDs

demography

a tibble of demographic information for each individual in the simulation

biomarker_map

a table specifying the relationship between exposure IDs and biomarker IDs

model_pars

a tibble of parameters needed for the immunity model

max_events

a vector of the maximum number of successful exposure events possible for each exposure ID

vacc_exposures

a vector of exposure IDs (x)

vacc_age

a vector of the minimum age at which an individual is eligible for vaccination for each exposure event; If an exposure event is not a vaccination event then input NA

...

Additional arguments

Value

A probability of successful exposure is returned

Examples

tmp_immune_history <- array(0, dim=c(1, 10, 2))
## Toy example: individual has 3 early exposures with exposure ID 1
tmp_immune_history[1,1:3,1] <- 1
tmp_demography <- dplyr::tibble(i=1, birth=1)
## Probability of successful exposure ID 1 at time 8 is 0, as all 3 allowable 
## exposure events have occurred
immunity_model_vacc_ifxn_simple(1,8,1,tmp_immune_history,NULL, tmp_demography,
NULL, NULL,max_events=c(3,5),vacc_exposures=c(1,2),vacc_age=c(1,1))
#> [1] 0
## Probability of successful exposure ID 2 at time 8 is 1, as <5 of the 
## allowable exposure events have occurred
immunity_model_vacc_ifxn_simple(1,8,2,tmp_immune_history,NULL, tmp_demography,
NULL, NULL,max_events=c(3,5),vacc_exposures=c(1,2),vacc_age=c(1,1))
#> [1] 1