five

A conceptual disease cycle model to link the size of past and future epidemics

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NIAID Data Ecosystem2026-05-10 收录
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.p8cz8wb2g
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Populations of humans, animals, and plants face ongoing threats from infectious disease epidemics. While host–parasite coevolution plays a central role in shaping these dynamics, epidemics are often studied in isolation. I propose a simple ‘Disease Cycle’ model that connects past and future epidemic sizes within the context of environmental change and evolutionary feedbacks. Drawing on recent evo-epidemiological research, I highlight three key themes: (i) how epidemics influence the strength and direction of natural selection, (ii) how host and parasite diversity shift through evolving resistance and infectivity, and (iii) how genetic diversity in either population may affect future epidemic severity. Although gaps remain, current evidence supports this integrative model. Future research should explore how the Disease Cycle applies to non-model organisms with low coevolutionary potential. This framework encourages a more holistic view of epidemics as dynamic outcomes of host–parasite coevolution.
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2025-09-30
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