Disease momentum: Estimating the reproduction number in the presence of superspreading
A primary quantity of interest in the study of infectious diseases is the average number of new 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 superspreadin...
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doaj-334414154176459cab1725d2486b92222021-04-26T05:57:24ZengKeAi Communications Co., Ltd.Infectious Disease Modelling2468-04272021-01-016706728Disease momentum: Estimating the reproduction number in the presence of superspreadingKory D. Johnson0Mathias Beiglböck1Manuel Eder2Annemarie Grass3Joachim Hermisson4Gudmund Pammer5Jitka Polechová6Daniel Toneian7Benjamin Wölfl8Vienna University of Economics and Business, Welthandelsplatz 1, Vienna, 1020, Austria; Corresponding author.University of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, AustriaUniversity of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, AustriaUniversity of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, AustriaUniversity of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, AustriaUniversity of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, AustriaUniversity of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, AustriaUniversity of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, AustriaUniversity of Vienna, Oskar-Morgenstern-Platz 1, Vienna, 1090, AustriaA primary quantity of interest in the study of infectious diseases is the average number of new 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 simple extension 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.http://www.sciencedirect.com/science/article/pii/S2468042721000270COVID-19Reproduction numberOverdispersionSuperspreading |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kory D. Johnson Mathias Beiglböck Manuel Eder Annemarie Grass Joachim Hermisson Gudmund Pammer Jitka Polechová Daniel Toneian Benjamin Wölfl |
spellingShingle |
Kory D. Johnson Mathias Beiglböck Manuel Eder Annemarie Grass Joachim Hermisson Gudmund Pammer Jitka Polechová Daniel Toneian Benjamin Wölfl Disease momentum: Estimating the reproduction number in the presence of superspreading Infectious Disease Modelling COVID-19 Reproduction number Overdispersion Superspreading |
author_facet |
Kory D. Johnson Mathias Beiglböck Manuel Eder Annemarie Grass Joachim Hermisson Gudmund Pammer Jitka Polechová Daniel Toneian Benjamin Wölfl |
author_sort |
Kory D. Johnson |
title |
Disease momentum: Estimating the reproduction number in the presence of superspreading |
title_short |
Disease momentum: Estimating the reproduction number in the presence of superspreading |
title_full |
Disease momentum: Estimating the reproduction number in the presence of superspreading |
title_fullStr |
Disease momentum: Estimating the reproduction number in the presence of superspreading |
title_full_unstemmed |
Disease momentum: Estimating the reproduction number in the presence of superspreading |
title_sort |
disease momentum: estimating the reproduction number in the presence of superspreading |
publisher |
KeAi Communications Co., Ltd. |
series |
Infectious Disease Modelling |
issn |
2468-0427 |
publishDate |
2021-01-01 |
description |
A primary quantity of interest in the study of infectious diseases is the average number of new 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 simple extension 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. |
topic |
COVID-19 Reproduction number Overdispersion Superspreading |
url |
http://www.sciencedirect.com/science/article/pii/S2468042721000270 |
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