Estimating transmission parameters from stochastic epidemic models using survival analysis techniques

Statistical Methods in Medical Research, vol. 35, pp. 1727–1745

Abstract

Compartmental models based on ordinary differential equations quantifying the interactions between susceptible, infectious and recovered individuals within a population have played an important role in infectious disease modelling. The aim of the present paper is to explain the link between stochastic epidemic models based on the susceptible-infectious-recovered (SIR) model and methods from survival analysis. We illustrate how standard software for survival analysis in the statistical language R can be used to estimate pivotal parameters in the stochastic SIR model in the very much idealized situation where the epidemic is completely observed. Extensions incorporating interventions, age structure and heterogeneity are explored and illustrated.

Authors 3

1. Hein Putter corresponding Aachen Department of Mathematics, Leiden University

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Department of Mathematics, Leiden University, Leiden, The Netherlands

   Leiden University Medical Center

2. Chengyuan Lu Aachen

   Leiden University Medical Center

   Affiliation as printed

   Leiden University Medical Center

3. Jacco Wallinga Aachen

   Leiden University Medical Center · National Institute for Public Health and the Environment

   Affiliation as printed

   Leiden University Medical Center

   National Institute for Public Health and the Environment, Bilthoven, The Netherlands