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Model_Run

Model_Run.Rd

Run SEIRV model for single region (Model_Run_Multi_Input can be used to run multiple regions in parallel)

Usage

Model_Run(
  FOI_spillover = 0,
  R0 = 1,
  vacc_data = list(),
  pop_data = list(),
  years_data = c(1940:1941),
  start_SEIRV = list(),
  output_type = "full",
  year0 = 1940,
  mode_start = 0,
  vaccine_efficacy = 1,
  dt = 1,
  n_particles = 1,
  n_threads = 1,
  deterministic = FALSE
)

Arguments

FOI_spillover

Force of infection due to spillover from sylvatic reservoir

R0

Basic reproduction number for urban spread of infection

vacc_data

Projected vaccination-based immunity (assuming vaccine_efficacy = 1) by age group and year

pop_data

Population by age group and year

years_data

Incremental vector of years denoting years for which to save data

start_SEIRV

SEIRV data from end of a previous run to use as input

output_type

Type of data to output: "full" = SEIRVC + FOI for all steps and ages "case" = annual total new infections (C) summed across all ages "sero" = annual SEIRV "case+sero" = annual SEIRVC, cases summed across all ages "case_alt" = annual total new infections not combined by age "case_alt2" = total new infections combined by age for all steps

year0

First year in population/vaccination data

mode_start

Flag indicating how to set initial population immunity level in addition to vaccination If mode_start = 0, only vaccinated individuals If mode_start = 1, shift some non-vaccinated individuals into recovered to give herd immunity (uniform by age, R0 based only) If mode_start = 2, use SEIRV input in list from previous run(s) If mode_start = 3, shift some non-vaccinated individuals into recovered to give herd immunity (stratified by age)

vaccine_efficacy

Proportional vaccine efficacy

dt

Time increment in days to use in model (should be 1.0, 2.5 or 5.0 days)

n_particles

number of particles to use

n_threads

number of threads to use

deterministic

TRUE/FALSE - set model to run in deterministic mode if TRUE '

Details

Accepts epidemiological + population parameters and model settings; runs SEIRV model for one region over a specified time period for a number of particles/threads and outputs time-dependent SEIRV values, infection numbers and/or total force of infection values.