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

Patrick W. Schmidt

arXiv 8 Nov 2020 · Statistics — Applications · publishedStatistics in Medicine (2024) · 1 citations (OpenAlex)

arXiv:2011.04002 · PDF · DOI · OpenAlex · Extracted main text

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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31
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Victor Chernozhukov, Hiroyuki Kasahara, and Paul Schrimpf (2020) Causal impact of masks, policies, behavior on early covid-19 pandemic in the u.s0.69371100%
2Seth Flaxman, Swapnil Mishra, Axel Gandy, H Juliette T Unwin, Thomas… (2020) Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe0.69351100%
3Colin J Carlson, Ana CR Gomez, Shweta Bansal, and Sadie J Ryan (2020) Misconceptions about weather and seasonality must not misguide COVID-19 response0.58531100%
4Solomon Hsiang, Daniel Allen, Sébastien Annan-Phan, Kendon Bell, Ian… (2020) The effect of large-scale anti-contagion policies on the covid-19 pandemic0.58531100%
5Andrew T Levin, Kensington B Cochran, and Seamus P Walsh (2020) Assessing the age specificity of infection fatality rates for Covid-19: Meta-analysis & public policy implications0.58531100%
6James O Lloyd-Smith, Sebastian J Schreiber, P Ekkehard Kopp, and Way… (2005) Superspreading and the effect of individual variation on disease emergence0.58531100%
7Henrik Salje, Cécile Tran Kiem, Noémie Lefrancq, Noémie Courtejoie,… (2020) Estimating the burden of SARS-CoV-2 in France0.58531100%
8Rachel E Baker, Wenchang Yang, Gabriel A Vecchi, C Jessica E Metcalf… (2020) Susceptible supply limits the role of climate in the early SARS-CoV-2 pandemic0.51121100%
9Jonas Dehning, Johannes Zierenberg, F Paul Spitzner, Michael Wibral,… (2020) Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions0.51121100%
10Shiv T Sehra, Justin D Salciccioli, Douglas J Wiebe, Shelby Fundin,… (2020) Maximum daily temperature, precipitation, ultra-violet light and rates of transmission of SARS-Cov-2 in the United States0.51121100%

Showing the top 10 of 31 scored citations.