ArticlePloS one2015
The basic reproduction number as a predictor for epidemic outbreaks in temporal networks.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Integrating mathematical modelling and artificial intelligence to combat emerging viral syndemics: A systematic review.New microbes and new infections · 2026Review
- Understanding Nash epidemics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Static graph approximations of dynamic contact networks for epidemic forecasting.Scientific reports · 2024Article
- Structural network characteristics affect epidemic severity and prediction in social contact networks.Infectious Disease Modelling · 2024Article
- Understanding the progress of COVID-19 transmission in a rural district: a social network approach.PeerJ · 2024Article
- Rational social distancing policy during epidemics with limited healthcare capacity.PLoS computational biology · 2023Article
- Impact of insecticide resistance on malaria vector competence: a literature review.Malaria journal · 2023Review
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- Temperature impacts the environmental suitability for malaria transmission by Anopheles gambiae and Anopheles stephensi.Ecology · 2022Article
- What Is the Impact of Early and Subsequent Epidemic Characteristics on the Pre-delta COVID-19 Epidemic Size in the United States?Pathogens (Basel, Switzerland) · 2022Article
- Concurrency measures in the era of temporal network epidemiology: a review.Journal of the Royal Society, Interface · 2021Review
- Article
- Cost effective reproduction number based strategies for reducing deaths from COVID-19.Journal of mathematics in industry · 2021Article
- Mass screening vs lockdown vs combination of both to control COVID-19: A systematic review.Journal of public health research · 2020Article
- Prediction of CoVid-19 infection, transmission and recovery rates: A new analysis and global societal comparisons.Safety science · 2020Article
- Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020Article
- Article
- Meta-analysis of several epidemic characteristics of COVID-19.Journal of data science : JDS · 2020Article
- Meta-analysis of several epidemic characteristics of COVID-19.medRxiv : the preprint server for health sciences · 2020Article
- Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The basic reproduction number R0--the number of individuals directly infected by an infectious person in an otherwise susceptible population--is arguably the most widely used estimator of how severe an epidemic outbreak can be. This severity can be more directly measured as the fraction of people infected once the outbreak is over, Ω. In traditional mathematical epidemiology and common formulations of static network epidemiology, there is a deterministic relationship between R0 and Ω. However, if one considers disease spreading on a temporal contact network--where one knows when contacts happen, not only between whom--then larger R0 does not necessarily imply larger Ω. In this paper, we numerically investigate the relationship between R0 and Ω for a set of empirical temporal networks of human contacts. Among 31 explanatory descriptors of temporal network structure, we identify those that make R0 an imperfect predictor of Ω. We find that descriptors related to both temporal and topological aspects affect the relationship between R0 and Ω, but in different ways.
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