Estimation of the Distribution of the Individual Reproduction Number: The Case of the COVID-19 Pandemic
Alexander Braumann, Jonas Krampe, Jens-Peter Kreiss, Efstathios, Paparoditis

TL;DR
This paper develops methods to estimate the distribution of individual reproduction numbers during COVID-19, accounting for under-reporting and variability, using German regional data to inform policy decisions.
Contribution
It introduces a novel estimation approach for the negative binomial distribution parameters of reproduction numbers, incorporating under-reporting and regional data analysis.
Findings
Strong overdispersion of individual reproduction numbers in Germany
Estimates of mean and variance inform understanding of pandemic dynamics
Methodology enables construction of confidence intervals for reproduction number parameters
Abstract
We investigate the problem of estimating the distribution of the individual reproduction number governing the COVID-19 pandemic. Under the assumption that this random variable follows a Negative Binomial distribution, we focus on constructing estimators of the parameters of this distribution using reported infection data and taking into account issues like under-reporting or the time behavior of the infection and of the reporting processes. To this end, we extract information from regionally dissaggregated data reported by German health authorities, in order to estimate not only the mean but also the variance of the distribution of the individual reproduction number. In contrast to the mean, the latter parameter also depends on the unknown under-reporting rate of the pandemic. The estimates obtained allow not only for a better understanding of the time-varying behavior of the expected…
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Taxonomy
TopicsCOVID-19 epidemiological studies · COVID-19 Pandemic Impacts · Vaccine Coverage and Hesitancy
