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Supporting Mathematica Notebook from Reservoir population ecology, viral evolution and the risk of emerging infectious disease

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DataCite Commons2022-08-26 更新2024-08-18 收录
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https://rs.figshare.com/articles/dataset/Supporting_Mathematica_Notebook_from_Reservoir_population_ecology_viral_evolution_and_the_risk_of_emerging_infectious_disease/20660522
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资源简介:
The ecology and life history of wild animals influences their potential to harbour infectious disease. This observation has motivated studies identifying empirical relationships between traits of wild animals and historical patterns of spillover and emergence into humans. Although these studies have identified compelling broad-scale patterns, they are generally agnostic with respect to underlying mechanisms. Here, we develop mathematical models that couple reservoir population ecology with viral epidemiology and evolution to clarify existing verbal arguments and pinpoint the conditions that favour spillover and emergence. Our results support the idea that average lifespan influences the likelihood of an animal serving as a reservoir for human infectious disease. At the same time, however, our results show that the magnitude of this effect is sensitive to the rate of viral mutation. Our results also demonstrate that viral pathogens causing persistent infections or a transient immune response within the reservoir are more likely to fuel emergence. Genetically explicit stochastic simulations enrich these mathematical results by identifying relationships between the genetic basis of transmission and the risk of spillover and emergence. Together, our results clarify the scope of applicability for existing hypotheses and refine our understanding of emergence risk.
提供机构:
The Royal Society
创建时间:
2022-08-26
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