Reproducibility of COVID-era infectious disease models

Abstract

AbstractInfectious disease modelling has been prominent throughout the COVID-19 pandemic, helping to understand the virus’ transmission dynamics and inform response policies. Given their potential importance and translational impact, we evaluated the computational reproducibility of infectious disease modelling articles from the COVID era. We found that only four out of 100 randomly sampled studies released between January 2020 and August 2022 could be computationally reproduced using the resources provided (e.g., code, data, instructions). For the 100 most highly cited articles from the same period we found that only 11 were reproducible. Reflecting on our experience, we discuss common issues affecting computational reproducibility and how these might be addressed.