ArticleProceedings of the National Academy of Sciences of the United States of America2018
Measurability of the epidemic reproduction number in data-driven contact networks.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers.
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116 citing papers in PubMed.
- Integrating mathematical modelling and artificial intelligence to combat emerging viral syndemics: A systematic review.New microbes and new infections · 2026Review
- A systematic comparison of methodologies for the estimation of the serial interval.Infectious Disease Modelling · 2026Article
- Redefining and estimating the early-phase reproduction ratio for epidemic outbreaks in spatially structured populations.PLoS computational biology · 2026Article
- Network structure induced bias in estimates of intrinsic generation times.PLoS computational biology · 2026Article
- Sex- and age-specific transmission pathways of mumps: a mechanistic SEPIAR modeling study in Chengdu, China (2008-2019).BMC public health · 2026Article
- VIBES: A multiscale modeling approach integrating within-host and between-hosts dynamics in epidemics.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Surveillance of infectious diseases spreading on time-varying multiplex networks.Infectious Disease Modelling · 2026Article
- From data to decisions: a modular platform for modelling and simulation of infectious disease diffusion in networks.BMC medical informatics and decision making · 2026Article
- Prediction of influenza-like illness incidence using meteorological factors in Kunming : deep learning model study.BMC public health · 2025Article
- Social contact patterns and their impact on the transmission of respiratory pathogens in rural China.Infectious Disease Modelling · 2025Article
- Duration of transients in outbreaks: when can infectiousness be estimated?Journal of mathematical biology · 2024Article
- Estimating the time-varying effective reproduction number via Cycle Threshold-based Transformer.PLoS computational biology · 2024Article
- Epidemicity indices and reproduction numbers from infectious disease data in connected human populations.Infectious Disease Modelling · 2024Article
- Inferring enterovirus D68 transmission dynamics from the genomic data of two 2022 North American outbreaks.Npj viruses · 2024Article
- Emergence of the reproduction matrix in epidemic forecasting.Journal of the Royal Society, Interface · 2024Article
- Assessing the impact of interventions on the major Omicron BA.2 outbreak in spring 2022 in Shanghai.Infectious Disease Modelling · 2024Article
- Static graph approximations of dynamic contact networks for epidemic forecasting.Scientific reports · 2024Article
- Evaluating Seasonal Variations in Human Contact Patterns and Their Impact on the Transmission of Respiratory Infectious Diseases.Influenza and other respiratory viruses · 2024Article
- Structural network characteristics affect epidemic severity and prediction in social contact networks.Infectious Disease Modelling · 2024Article
- Assessing the impact of different contact patterns on disease transmission: Taking COVID-19 as a case.PloS one · 2024Article
56 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
The basic reproduction number is one of the conceptual cornerstones of mathematical epidemiology. Its classical definition as the number of secondary cases generated by a typical infected individual in a fully susceptible population finds a clear analytical expression in homogeneous and stratified mixing models. Along with the generation time (the interval between primary and secondary cases), the reproduction number allows for the characterization of the dynamics of an epidemic. A clear-cut theoretical picture, however, is hardly found in real data. Here, we infer from highly detailed sociodemographic data two multiplex contact networks representative of a subset of the Italian and Dutch populations. We then simulate an infection transmission process on these networks accounting for the natural history of influenza and calibrated on empirical epidemiological data. We explicitly measure the reproduction number and generation time, recording all individual-level transmission events. We find that the classical concept of the basic reproduction number is untenable in realistic populations, and it does not provide any conceptual understanding of the epidemic evolution. This departure from the classical theoretical picture is not due to behavioral changes and other exogenous epidemiological determinants. Rather, it can be simply explained by the (clustered) contact structure of the population. Finally, we provide evidence that methodologies aimed at estimating the instantaneous reproduction number can operationally be used to characterize the correct epidemic dynamics from incidence data.
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