ReviewJournal of the Royal Society, Interface2021
The stochastic dynamics of early epidemics: probability of establishment, initial growth rate, and infection cluster size at first detection.
Review in Journal of the Royal Society, Interface, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 0 citations in OpenAlex.
- Dengue transmission risk in California under climate and land-use change: a semi-mechanistic modelling study.Lancet regional health. Americas · 2026Article
- Understanding patterns of variant emergence and spread in an ongoing epidemic.medRxiv : the preprint server for health sciences · 2026Article
- A multi-host mechanistic model of African swine fever emergence and control in Romania.Nature communications · 2026Article
- Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha.Nature communications · 2024Article
- Using early detection data to estimate the date of emergence of an epidemic outbreak.PLoS computational biology · 2024Article
- A stochastic analysis of the interplay between antibiotic dose, mode of action, and bacterial competition in the evolution of antibiotic resistance.PLoS computational biology · 2023Article
- The stochastic dynamics of early epidemics: probability of establishment, initial growth rate, and infection cluster size at first detection.Journal of the Royal Society, Interface · 2021Review
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Authors and funding
4 authors at 2 institutions in 3 countries.
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Abstract
Emerging epidemics and local infection clusters are initially prone to stochastic effects that can substantially impact the early epidemic trajectory. While numerous studies are devoted to the deterministic regime of an established epidemic, mathematical descriptions of the initial phase of epidemic growth are comparatively rarer. Here, we review existing mathematical results on the size of the epidemic over time, and derive new results to elucidate the early dynamics of an infection cluster started by a single infected individual. We show that the initial growth of epidemics that eventually take off is accelerated by stochasticity. As an application, we compute the distribution of the first detection time of an infected individual in an infection cluster depending on testing effort, and estimate that the SARS-CoV-2 variant of concern Alpha detected in September 2020 first appeared in the UK early August 2020. We also compute a minimal testing frequency to detect clusters before they exceed a given threshold size. These results improve our theoretical understanding of early epidemics and will be useful for the study and control of local infectious disease clusters.
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