The 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.
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【저자키워드】 Diseases, Applied mathematics, Statistics, Population dynamics, Computational biophysics, 【초록키워드】 COVID-19, Variation, heterogeneity, Epidemic, infections, Community, basic reproduction number, trajectory, Denmark, quantification, COVID-19 epidemic, 95% confidence interval, Affect, mitigating strategy, overdispersion factor, 【제목키워드】 Epidemic, trajectory, quantified,
【저자키워드】 Diseases, Applied mathematics, Statistics, Population dynamics, Computational biophysics, 【초록키워드】 COVID-19, Variation, heterogeneity, Epidemic, infections, Community, basic reproduction number, trajectory, Denmark, quantification, COVID-19 epidemic, 95% confidence interval, Affect, mitigating strategy, overdispersion factor, 【제목키워드】 Epidemic, trajectory, quantified,