Within-host immunology to age-of-infection epidemiology via a virtual cohort
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866909051945746432 |
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| author | Arino, Julien Craig, Morgan Djuikem, Clotilde Liao, Kang-Ling Portet, Stéphanie |
| author_facet | Arino, Julien Craig, Morgan Djuikem, Clotilde Liao, Kang-Ling Portet, Stéphanie |
| contents | We present a methodology providing a one-directional link from within-host individual heterogeneity to population-level disease transmission dynamics. The methodology works in several steps. A within-host model is investigated numerically to determine pathogen and immunological parameters leading to the largest variation of model responses. These key parameters are used to generate a synthetic population of individuals whose temporal immunological response profiles are recorded. These responses are ranked in terms of the severity of experienced outcomes, from mild infections to death, as a function of time since infection. This is used to parametrise an age-of-infection structured epidemiological model to study the transmission dynamics of the disease at the population level. The approach is illustrated using a within-host model describing SARS-CoV-2 infection and an SIR population-level model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_17129 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Within-host immunology to age-of-infection epidemiology via a virtual cohort Arino, Julien Craig, Morgan Djuikem, Clotilde Liao, Kang-Ling Portet, Stéphanie Populations and Evolution Quantitative Methods 92D30, 92C45, 35Q92 We present a methodology providing a one-directional link from within-host individual heterogeneity to population-level disease transmission dynamics. The methodology works in several steps. A within-host model is investigated numerically to determine pathogen and immunological parameters leading to the largest variation of model responses. These key parameters are used to generate a synthetic population of individuals whose temporal immunological response profiles are recorded. These responses are ranked in terms of the severity of experienced outcomes, from mild infections to death, as a function of time since infection. This is used to parametrise an age-of-infection structured epidemiological model to study the transmission dynamics of the disease at the population level. The approach is illustrated using a within-host model describing SARS-CoV-2 infection and an SIR population-level model. |
| title | Within-host immunology to age-of-infection epidemiology via a virtual cohort |
| topic | Populations and Evolution Quantitative Methods 92D30, 92C45, 35Q92 |
| url | https://arxiv.org/abs/2605.17129 |