Kremer, Cécile; Torneri, Andrea; Boesmans, Sien; Meuwissen, Hanne; Verdonschot, Selina; Vanden Driessche, Koen; Althaus, Christian L.; Faes, Christel; Hens, Niel (2021). Quantifying superspreading for COVID-19 using Poisson mixture distributions. Scientific reports, 11(1), p. 14107. Springer Nature 10.1038/s41598-021-93578-x
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The number of secondary cases, i.e. the number of new infections generated by an infectious individual, is an important parameter for the control of infectious diseases. When individual variation in disease transmission is present, like for COVID-19, the distribution of the number of secondary cases is skewed and often modeled using a negative binomial distribution. However, this may not always be the best distribution to describe the underlying transmission process. We propose the use of three other offspring distributions to quantify heterogeneity in transmission, and we assess the possible bias in estimates of the mean and variance of this distribution when the data generating distribution is different from the one used for inference. We also analyze COVID-19 data from Hong Kong, India, and Rwanda, and quantify the proportion of cases responsible for 80% of transmission, [Formula: see text], while acknowledging the variation arising from the assumed offspring distribution. In a simulation study, we find that variance estimates may be biased when there is a substantial amount of heterogeneity, and that selection of the most accurate distribution from a set of distributions is important. In addition we find that the number of secondary cases for two of the three COVID-19 datasets is better described by a Poisson-lognormal distribution.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM) |
UniBE Contributor: |
Althaus, Christian |
Subjects: |
600 Technology > 610 Medicine & health 300 Social sciences, sociology & anthropology > 360 Social problems & social services |
ISSN: |
2045-2322 |
Publisher: |
Springer Nature |
Language: |
English |
Submitter: |
Andrea Flükiger-Flückiger |
Date Deposited: |
27 Jul 2021 15:12 |
Last Modified: |
21 Jun 2023 15:48 |
Publisher DOI: |
10.1038/s41598-021-93578-x |
PubMed ID: |
34238978 |
BORIS DOI: |
10.48350/157533 |
URI: |
https://boris.unibe.ch/id/eprint/157533 |
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