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Estimating the basic reproduction number at the beginning of an outbreak

Author

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  • Sawitree Boonpatcharanon
  • Jane M Heffernan
  • Hanna Jankowski

Abstract

We compare several popular methods of estimating the basic reproduction number, R0, focusing on the early stages of an epidemic, and assuming weekly reports of new infecteds. We study the situation when data is generated by one of three standard epidemiological compartmental models: SIR, SEIR, and SEAIR; and examine the sensitivity of the estimators to the model structure. As some methods are developed assuming specific epidemiological models, our work adds a study of their performance in both a well-specified (data generating model and method model are the same) and miss-specified (data generating model and method model differ) settings. We also study R0 estimation using Canadian COVID-19 case report data. In this study we focus on examples of influenza and COVID-19, though the general approach is easily extendable to other scenarios. Our simulation study reveals that some estimation methods tend to work better than others, however, no singular best method was clearly detected. In the discussion, we provide recommendations for practitioners based on our results.

Suggested Citation

  • Sawitree Boonpatcharanon & Jane M Heffernan & Hanna Jankowski, 2022. "Estimating the basic reproduction number at the beginning of an outbreak," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-24, June.
    • Handle: RePEc:plo:pone00:0269306
    DOI: 10.1371/journal.pone.0269306
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    References listed on IDEAS

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    1. King, Aaron A. & Nguyen, Dao & Ionides, Edward L., 2016. "Statistical Inference for Partially Observed Markov Processes via the R Package pomp," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 69(i12).
    2. P. D. O’Neill & G. O. Roberts, 1999. "Bayesian inference for partially observed stochastic epidemics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(1), pages 121-129.
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    Cited by:

    1. Kim, Suhyeon & Park, Junpyo, 2025. "A double-edged aspect of basin entropy for predicting biodiversity in spatial rock–paper–scissors games," Chaos, Solitons & Fractals, Elsevier, vol. 197(C).

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