ArticleJournal of the Royal Society, Interface2020
A theoretical framework for transitioning from patient-level to population-scale epidemiological dynamics: influenza A as a case study.
Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 32 citations in OpenAlex.
- Should public health policy exempt cases with low viral load from isolation during an epidemic?: a modelling study.Infectious Disease Modelling · 2025Article
- Within- and between-host evolutionary effects on viral oncogenicity.Virus evolution · 2025Article
- Linking within- and between-host scales for understanding the evolutionary dynamics of quantitative antimicrobial resistance.Journal of mathematical biology · 2023Article
- Analysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 as a case study.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Contact-number-driven virus evolution: A multi-level modeling framework for the evolution of acute or persistent RNA virus infection.PLoS computational biology · 2023Article
- Correlation of viral loads in disease transmission could affect early estimates of the reproduction number.Journal of the Royal Society, Interface · 2023Article
- Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models.Journal of theoretical biology · 2023Article
- Generation time of the alpha and delta SARS-CoV-2 variants: an epidemiological analysis.The Lancet. Infectious diseases · 2022Article
- Challenges for modelling interventions for future pandemics.Epidemics · 2022Article
- The impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants.Frontiers in immunology · 2022Article
- Article
- Data-driven methods for present and future pandemics: Monitoring, modelling and managing.Annual reviews in control · 2021Review
- Will an outbreak exceed available resources for control? Estimating the risk from invading pathogens using practical definitions of a severe epidemic.Journal of the Royal Society, Interface · 2020Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multi-scale epidemic forecasting models have been used to inform population-scale predictions with within-host models and/or infection data collected in longitudinal cohort studies. However, most multi-scale models are complex and require significant modelling expertise to run. We formulate an alternative multi-scale modelling framework using a compartmental model with multiple infected stages. In the large-compartment limit, our easy-to-use framework generates identical results compared to previous more complicated approaches. We apply our framework to the case study of influenza A in humans. By using a viral dynamics model to generate synthetic patient-level data, we explore the effects of limited and inaccurate patient data on the accuracy of population-scale forecasts. If infection data are collected daily, we find that a cohort of at least 40 patients is required for a mean population-scale forecasting error below 10%. Forecasting errors may be reduced by including more patients in future cohort studies or by increasing the frequency of observations for each patient. Our work, therefore, provides not only an accessible epidemiological modelling framework but also an insight into the data required for accurate forecasting using multi-scale models.
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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 OpenQuestion graph.