Model_Run_Reactive

Runs reactive version of SEIRV model

Usage

Model_Run_Reactive(
  FOI_spillover = 0,
  R0 = 1,
  vacc_data1 = list(),
  vacc_data2 = list(),
  pop_data = list(),
  years_data = c(1940:1941),
  start_SEIRV = list(),
  year0 = 1940,
  mode_start = 0,
  vaccine_efficacy = 1,
  dt = 1,
  n_particles = 1,
  n_threads = 1,
  deterministic = FALSE,
  p_rep = 1,
  outbreak_threshold1 = 1,
  cluster_threshold1 = 1
)

Arguments

FOI_spillover

Force of infection due to spillover from sylvatic reservoir

R0

Basic reproduction number for urban spread of infection

vacc_data1

[TBA]

vacc_data2

[TBA]

pop_data

Population in each age group by 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

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 If mode_start=2, use SEIRV input in list from previous run(s)

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

p_rep

Probabilities of an infection being reported as a case under different conditions (TBA)

outbreak_threshold1

Threshold total no. reported cases to trigger outbreak flag 1

cluster_threshold1

Threshold current infectious fraction to trigger cluster flag 1 '

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 total force of infection values. Alternate version incorporating case reporting and reactive surveillance/control measures based on case numbers