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Extreme value modelling of SARS-CoV-2 community transmission using discrete Generalised Pareto distributions

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  • Daouia, Abdelaati
  • Stupfler, Gilles
  • Usseglio-Carleve, Antoine

Abstract

Superspreading has been suggested to be a major driver of overall transmission in the case of SARS-CoV-2. It is therefore important to statistically investigate the tail features of superspreading events (SSEs) to better understand virus propagation and control. Our extreme value analysis of different sources of secondary case data indicates that case numbers of SSEs associated with SARS-CoV-2 may be fat-tailed, although substantially less so than predicted recently in the literature, but also less important relative to SSEs associated with SARS-CoV. The results caution against pooling data from both coronaviruses. This could provide policy- and decision-makers with a more reliable assessment of the tail exposure to SARS-CoV-2 contamination. Going further, we consider the broader problem of large community transmission. We study the tail behaviour of SARS-CoV-2 cluster cases documented both in official reports and in the media. Our results suggest that the observed cluster sizes have been fat-tailed in the vast majority of surveyed countries. We also give estimates and confidence intervals of the extreme potential risk for those countries. A key component of our methodology is up-to-date discrete Generalised Pareto models which allow for maximum-likelihood based inference of data with a high degree of discreteness.

Suggested Citation

  • Daouia, Abdelaati & Stupfler, Gilles & Usseglio-Carleve, Antoine, 2022. "Extreme value modelling of SARS-CoV-2 community transmission using discrete Generalised Pareto distributions," TSE Working Papers 22-1323, Toulouse School of Economics (TSE), revised 09 Mar 2023.
    • Handle: RePEc:tse:wpaper:126784
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    References listed on IDEAS

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    1. J. O. Lloyd-Smith & S. J. Schreiber & P. E. Kopp & W. M. Getz, 2005. "Superspreading and the effect of individual variation on disease emergence," Nature, Nature, vol. 438(7066), pages 355-359, November.
    2. Alison P. Galvani & Robert M. May, 2005. "Dimensions of superspreading," Nature, Nature, vol. 438(7066), pages 293-295, November.
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    Keywords

    COVID-19 ; Superspreading ; Cluster size; Secondary cases ; Extreme value theory ; Discrete extermes;
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