sim_reference: Simulate an ideal population

In khvorov45/impactflu: Quantification of Population-Level Impact of Vaccination

Description

Simulates an ideal population using the reference model from Tokars (2018).

Usage

sim_reference(init_pop_size, vaccinations, infections_novac, ve, lag)

Arguments

init_pop_size	Integer initial population size
vaccinations	Integer vector number of vaccinations at every timepoint
infections_novac	Integer vector number of infections at every timepoint
ve	Vaccine effectiveness (proportion)
lag	Integer lag period measured in timepoints

Value

A tibble with the following columns:

timepoint	Index of timepoint
vaccinations	Expected number of vaccinations
infections_novac	Expected number of infections in absence of vaccination
ve	Expected vaccine effectiveness
pflu	Flu incidence
infections	Actual number of infections
popn	Non-cases in absence of vaccination
pvac	Proportion of starting population vaccinated
b	Number vaccinated at that time who didn't get infected later
b_og	Number vaccinated at that time
A	Non-vaccinated non-cases
C	Vaccinated susceptible
D	Vaccinated immune
E	Non-vaccinated infections cumulative total
F	Vaccinated infections cumulative total

References

Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331–7337. doi:10.1016/j.vaccine.2018.10.026

Examples

# Population from Tokars (2018)
nsam <- 1e6L
ndays <- 304L
pop_tok <- sim_reference(
  init_pop_size = nsam,
  vaccinations = generate_counts(nsam, ndays, 0.55, mean = 100, sd = 50),
  infections_novac = generate_counts(nsam, ndays, 0.12, mean = 190, sd = 35),
  ve = 0.48,
  lag = 14
)
head(pop_tok)
sum(pop_tok$avert)

khvorov45/impactflu documentation built on July 22, 2021, 10:36 p.m.