Extract key epidemic metrics from ODE simulation output

This function computes core epidemiological summary statistics from deterministic compartmental epidemic models (e.g., SIR, SIS, SEIR).

Usage

epi_metrics(data, beta, gamma, N = NULL)

Arguments

data: A data frame returned by model_*() functions. Must contain a column time, and at least S and I. Additional compartments such as E or R are allowed.
beta: Transmission rate (numeric).
gamma: Recovery / removal rate (numeric).
N: Total population (numeric). If NULL (default), it is computed as the sum of all compartment values at the first time point.

Value

A named list with:

R0: Basic reproduction number.
peak_infection: Maximum number of infectious individuals.
peak_time: Time at which infectious peak occurs.
attack_rate: Proportion of population that transitioned out of S; defined only for models containing an R compartment (e.g., SIR/SEIR).

Details

The input data frame is expected to be the output of model_*() functions, containing a time column and one or more compartment columns (e.g., S, I, R, E). All compartment values are assumed to be in absolute population counts, and the total population is assumed to be conserved unless otherwise specified.

Examples

sir = model_sir(
  init   = c(S = 990, I = 10),
  params = c(beta = 0.002, gamma = 0.1),
  times  = seq(0, 50, by = 0.1)
)
epi_metrics(sir, beta = 0.002, gamma = 0.1)
#> $R0
#> [1] 0.02
#> 
#> $peak_infection
#> [1] 10
#> 
#> $peak_time
#> [1] 0
#> 
#> $attack_rate
#> [1] 0.0002004762
#>