Apply vaccination effects to next generation contact matrices
apply_vaccination.Rd
Applies the effect of vaccination on the next generation of infections, to understand and describe the reduction of acquisition and transmission in each age group.
Arguments
- ngm
next generation matrices. See
generate_ngm()
for creating next generation matrices of a state or a local government area for specific age groups- data
data frame with location specific information on vaccine coverage, efficacy of acquisition/susceptibility and efficacy of transmission/infectiousness for the ordered age groups from lowest to highest of the next generation matrix
- coverage_col
bare variable name for the column with information on vaccine coverage by age groups
- acquisition_col
bare variable name for the column with information on efficacy of acquisition
- transmission_col
bare variable name for the column with information on efficacy of transmission
Value
list of contact matrices, one for each setting with reduction in transmission matching the next generation matrices
Details
Vaccination improves a person's immunity from a disease. When a sizable section of the population receives vaccinations or when vaccine coverage is sufficient enough, the likelihood that the unvaccinated population will contract the disease is decreased. This helps to slow infectious disease spread as well as lessen its severity. For this reason, it is important to understand how much of a reduction in probability of acquisition (the likelihood that an individual will contract the disease), and probability of transmission (the likelihood that an individual will spread the disease after contracting it), has occurred as an the effect of vaccination, in other words the effect of vaccination on the next generation of infections.
apply_vaccination
returns the percentage reduction in acquisition and
transmission in each age group. It does this by taking the outer product
of these reductions in acquisition and transmission by age group, creating
a transmission reduction matrix. The next generation matrices with the
vaccination effects applied are then produced using the obtained
transmission reduction matrix and the next generation matrices passed to
the function as an argument.
Examples
# examples take 20 second to run so skipping
if (FALSE) {
# example data frame with vaccine coverage, acquisition and transmission
# efficacy of different age groups
vaccination_effect_example_data
# Generate next generation matrices
# The number of age breaks must match the vaccination effect data
ngm_nsw <- generate_ngm(
state_name = "NSW",
age_breaks = c(seq(0, 80, by = 5), Inf),
R_target = 1.5
)
# Apply vaccination effect to next generation matrices
ngm_nsw_vacc <- apply_vaccination(
ngm = ngm_nsw,
data = vaccination_effect_example_data,
coverage_col = coverage,
acquisition_col = acquisition,
transmission_col = transmission
)
}