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Inference under Superspreading: Determinants of SARS-CoV-2 Transmission in Germany

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  • Patrick W. Schmidt

Abstract

Superspreading complicates the study of SARS-CoV-2 transmission. I propose a model for aggregated case data that accounts for superspreading and improves statistical inference. In a Bayesian framework, the model is estimated on German data featuring over 60,000 cases with date of symptom onset and age group. Several factors were associated with a strong reduction in transmission: public awareness rising, testing and tracing, information on local incidence, and high temperature. Immunity after infection, school and restaurant closures, stay-at-home orders, and mandatory face covering were associated with a smaller reduction in transmission. The data suggests that public distancing rules increased transmission in young adults. Information on local incidence was associated with a reduction in transmission of up to 44% (95%-CI: [40%, 48%]), which suggests a prominent role of behavioral adaptations to local risk of infection. Testing and tracing reduced transmission by 15% (95%-CI: [9%,20%]), where the effect was strongest among the elderly. Extrapolating weather effects, I estimate that transmission increases by 53% (95%-CI: [43%, 64%]) in colder seasons.

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  • Patrick W. Schmidt, 2020. "Inference under Superspreading: Determinants of SARS-CoV-2 Transmission in Germany," Papers 2011.04002, arXiv.org.
    • Handle: RePEc:arx:papers:2011.04002
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    1. B. F. Finkenstädt & B. T. Grenfell, 2000. "Time series modelling of childhood diseases: a dynamical systems approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(2), pages 187-205.
    2. S. Davis & P. Trapman & H. Leirs & M. Begon & J. A. P. Heesterbeek, 2008. "The abundance threshold for plague as a critical percolation phenomenon," Nature, Nature, vol. 454(7204), pages 634-637, July.
    3. Furman, Edward, 2007. "On the convolution of the negative binomial random variables," Statistics & Probability Letters, Elsevier, vol. 77(2), pages 169-172, January.
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    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health

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