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hestia

{hestia} fits Bayesian compartmental infection models — such as susceptible-infected-recovered (SIR) and multi-compartment hidden Markov variants — from individual-level outcome data. Models are composed from infection-process and observation-process components and fit using Stan via {rstan}.

Installation

remotes::install_github("ACCIDDA/hestia", build = TRUE)

Requires R >= 4.1.0 and a C++ toolchain (for Stan model compilation).

Usage

Compose an infection-process model from transmit() (transmission between compartments) and progress() (within-host progression) steps:

library(hestia)

# A basic SIR model: S -> I transmission, I -> R recovery (rate fit from data)
inf_process <- make_infection_model(
  transmit(from = "S", to = "I"),
  progress(from = "I", to = "R", gamma = NA)
)

Pair the infection process with an observation model (make_observation_model()) and fit it with run_model(). See the vignettes for full worked examples, including a multi-compartment (symptomatic/asymptomatic) model.

Part of ACCIDDA

{hestia} is developed by the Atlantic Coast Center for Infectious Disease Dynamics and Analytics (ACCIDDA).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.