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Superspreading quantified from bursty epidemic trajectories

AbstractThe quantification of spreading heterogeneity in the COVID-19 epidemic is crucial as it affects the choice of efficient mitigating strategies irrespective of whether its origin is biological or social. We present a method to deduce temporal and individual variations in the basic reproduction number directly from epidemic trajectories at a community level. Using epidemic data from the 98 districts in Denmark we estimate an overdispersion factor k for COVID-19 to be about 0.11 (95% confidence interval 0.08–0.18), implying that 10 % of the infected cause between 70 % and 87 % of all infections.
- KOBENHAVNS UNIVERSITET Denmark
- University of Copenhagen Denmark
Multidisciplinary, Population dynamics, Geography, SARS-CoV-2, Science, Denmark, Q, Statistics, R, Basic Reproduction Number, COVID-19, Diseases, Models, Theoretical, Applied mathematics, DISEASE, Article, Computational biophysics, Medicine, Humans, Epidemics, Algorithms
Multidisciplinary, Population dynamics, Geography, SARS-CoV-2, Science, Denmark, Q, Statistics, R, Basic Reproduction Number, COVID-19, Diseases, Models, Theoretical, Applied mathematics, DISEASE, Article, Computational biophysics, Medicine, Humans, Epidemics, Algorithms
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average Powered byBIP!

- Funder: European Commission (EC)
- Project Code: 740704
- Funding stream: H2020 | ERC | ERC-ADG
AbstractThe quantification of spreading heterogeneity in the COVID-19 epidemic is crucial as it affects the choice of efficient mitigating strategies irrespective of whether its origin is biological or social. We present a method to deduce temporal and individual variations in the basic reproduction number directly from epidemic trajectories at a community level. Using epidemic data from the 98 districts in Denmark we estimate an overdispersion factor k for COVID-19 to be about 0.11 (95% confidence interval 0.08–0.18), implying that 10 % of the infected cause between 70 % and 87 % of all infections.