Parameter estimation in the SIR model from early infections

TL;DR

This paper presents a straightforward algorithm for estimating SIR epidemic model parameters using early infection data, with performance guarantees on locally tree-like graphs, aiding understanding of disease spread.

Contribution

Introduces a simple, effective parameter estimation algorithm for the SIR model based on early infection times, with theoretical guarantees on certain graph structures.

Findings

Algorithm accurately estimates parameters from early infection data.

Performance guarantees established for locally tree-like graphs.

Potential applications in epidemic monitoring and control.

Abstract

A standard model for epidemics is the SIR model on a graph. We introduce a simple algorithm that uses the early infection times from a sample path of the SIR model to estimate the parameters this model, and we provide a performance guarantee in the setting of locally tree-like graphs.