Disease momentum: Estimating the reproduction number inthe presence of superspreading

Kory Johnson, Mathias Beiglböck, Manuel Eder, Annemarie Grass, Joachim Hermisson, Gudmund Pammer, Jitka Polechova, Daniel Toneian, Benjamin Wölfl

Publication: Scientific journalJournal articlepeer-review

9 Downloads (Pure)


A primary quantity of interest in the study of infectious diseases is the average number ofnew infections that an infected person produces. This so-called reproduction number has significant implications for the disease progression. There has been increasing literature suggesting that superspreading, the significant variability in number of new infections caused by individuals, plays an important role in the spread of SARS-CoV-2. In this paper, we consider the effect that such superspreading has on the estimation of the reproduction number and subsequent estimates of future cases. Accordingly, we employ a simpleextension to models currently used in the literature to estimate the reproduction number and present a case-study of the progression of COVID-19 in Austria. Our models demonstrate that the estimation uncertainty of the reproduction number increases with superspreading and that this improves the performance of prediction intervals. Of independent interest is the derivation of a transparent formula that connects the extent of superspreading to the width of credible intervals for the reproduction number. This serves as a valuable heuristic for understanding the uncertainty surrounding diseases with superspreading.
Original languageEnglish
Pages (from-to)706-728
JournalInfectious Disease Modelling
Publication statusPublished - 2021

Cite this