ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2022
Behavioural response to heterogeneous severity of COVID-19 explains temporal variation of cases among different age groups.
Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2022. 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.
- Breakthrough COVID-19 infections among healthcare workers at a tertiary care hospital in Beirut: Prevalence and determinants.IJID regions · 2026Article
- Estimating the effect of self-protection on transmission dynamics of SARS-CoV-2 in Germany in 2021: a modelling study.BMC public health · 2026Article
- Inferring COVID-19 testing and vaccination behavior from New Jersey testing data.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Heterogeneous risk tolerance, in-groups, and epidemic waves.Frontiers in applied mathematics and statistics · 2024Article
- Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models.Nature communications · 2023Article
- A model of behavioural response to risk accurately predicts the statistical distribution of COVID-19 infection and reproduction numbers.Scientific reports · 2023Article
- Social divisions and risk perception drive divergent epidemics and large later waves.Evolutionary human sciences · 2023Article
- Exploration of the COVID-19 pandemic at the neighborhood level in an intra-urban setting.Frontiers in public health · 2023Article
- Comparison of Clinical Features, Complete Blood Count Parameters, and Outcomes between Two Distinct Waves of COVID-19: A Monocentric Report from Italy.Healthcare (Basel, Switzerland) · 2022Article
- A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior.Scientific reports · 2022Article
- Emergence of protective behaviour under different risk perceptions to disease spreading.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Article
- Data science approaches to infectious disease surveillance.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Review
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5 authors.
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Abstract
Together with seasonal effects inducing outdoor or indoor activities, the gradual easing of prophylaxis caused second and third waves of SARS-CoV-2 to emerge in various countries. Interestingly, data indicate that the proportion of infections belonging to the elderly is particularly small during periods of low prevalence and continuously increases as case numbers increase. This effect leads to additional stress on the health care system during periods of high prevalence. Furthermore, infections peak with a slight delay of about a week among the elderly compared to the younger age groups. Here, we provide a mechanistic explanation for this phenomenology attributable to a heterogeneous prophylaxis induced by the age-specific severity of the disease. We model the dynamical adoption of prophylaxis through a two-strategy game and couple it with an SIR spreading model. Our results also indicate that the mixing of contacts among the age groups strongly determines the delay between their peaks in prevalence and the temporal variation in the distribution of cases. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.
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