ArticleInfectious Disease Modelling2021
Disease momentum: Estimating the reproduction number in the presence of superspreading.
Article in Infectious Disease Modelling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Unjustified Poisson assumptions lead to overconfident estimates of the effective reproductive number.Epidemiology and infection · 2026Article
- Simulation-based inference of the time-dependent reproduction number from temporally aggregated and under-reported disease incidence time series data.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Effects of meteorological factors on influenza transmissibility by virus type/subtype.BMC public health · 2024Article
- Time-varying overdispersion of SARS-CoV-2 transmission during the periods when different variants of concern were circulating in Japan.Scientific reports · 2023Article
- Assessing the heterogeneity in the transmission of infectious diseases from time series of epidemiological data.PloS one · 2023Article
- Monitoring real-time transmission heterogeneity from incidence data.PLoS computational biology · 2022Article
- Assessing epidemic curves for evidence of superspreading.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2022Article
- Real-time estimation of the epidemic reproduction number: Scoping review of the applications and challenges.PLOS digital health · 2022Article
- SARS-CoV-2 rapid antigen tests provide benefits for epidemic control - observations from Austrian schools.Journal of clinical epidemiology · 2022Article
- Robust models of disease heterogeneity and control, with application to the SARS-CoV-2 epidemic.PLOS global public health · 2022Article
- Estimation of the Serial Interval and the Effective Reproductive Number of COVID-19 Outbreak Using Contact Data in Burkina Faso, a Sub-Saharan African Country.Computational and mathematical methods in medicine · 2022Article
- Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity.BMC medical research methodology · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.