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Variability of Individual Infectiousness Derived from Aggregate Statistics of COVID-19

Kirkegaard, J. B.; Sneppen, K.

2021-01-15 epidemiology
10.1101/2021.01.15.21249870 medRxiv
Show abstract

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 R 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 % to 87 % of all infections.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.