Multi-scale phylodynamic modelling of rapid punctuated pathogen evolution
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866918108955934720 |
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| author | Nguyen, Quang Dang Chang, Sheryl L. Suster, Carl J. E. Rockett, Rebecca J. Sintchenko, Vitali Sorrell, Tania C. Prokopenko, Mikhail |
| author_facet | Nguyen, Quang Dang Chang, Sheryl L. Suster, Carl J. E. Rockett, Rebecca J. Sintchenko, Vitali Sorrell, Tania C. Prokopenko, Mikhail |
| contents | Computational multi-scale pandemic modelling remains a major and timely challenge. Here we identify specific requirements for a new class of models simulating pandemics across three scales: (1) pathogen evolution, often punctuated by the rapid emergence of new variants, (2) human interactions within a heterogeneous population, and (3) public health responses which constrain individual actions to control the disease transmission. We then present a pandemic modelling framework satisfying these requirements and capable of simulating feedback loops between dynamics unfolding at these different scales. The developed framework comprises a stochastic agent-based model of pandemic spread, coupled with a phylodynamic model that incorporates within-host pathogen evolution. It is validated with a case study, modelling the punctuated evolution of SARS-CoV-2, based on global and contemporary genomic surveillance data, which captures a large heterogeneous population. We demonstrate that the model replicates the essential features of the COVID-19 pandemic and virus evolution, while retaining computational tractability and scalability. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_03896 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multi-scale phylodynamic modelling of rapid punctuated pathogen evolution Nguyen, Quang Dang Chang, Sheryl L. Suster, Carl J. E. Rockett, Rebecca J. Sintchenko, Vitali Sorrell, Tania C. Prokopenko, Mikhail Populations and Evolution Computational multi-scale pandemic modelling remains a major and timely challenge. Here we identify specific requirements for a new class of models simulating pandemics across three scales: (1) pathogen evolution, often punctuated by the rapid emergence of new variants, (2) human interactions within a heterogeneous population, and (3) public health responses which constrain individual actions to control the disease transmission. We then present a pandemic modelling framework satisfying these requirements and capable of simulating feedback loops between dynamics unfolding at these different scales. The developed framework comprises a stochastic agent-based model of pandemic spread, coupled with a phylodynamic model that incorporates within-host pathogen evolution. It is validated with a case study, modelling the punctuated evolution of SARS-CoV-2, based on global and contemporary genomic surveillance data, which captures a large heterogeneous population. We demonstrate that the model replicates the essential features of the COVID-19 pandemic and virus evolution, while retaining computational tractability and scalability. |
| title | Multi-scale phylodynamic modelling of rapid punctuated pathogen evolution |
| topic | Populations and Evolution |
| url | https://arxiv.org/abs/2412.03896 |