Infected host competence overshadows heterogeneity in susceptibility in shaping experimental epizootics
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| Publicado en: | bioRxiv (Jan 20, 2025) |
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| Autor principal: | |
| Otros Autores: | , , , , , |
| Publicado: |
Cold Spring Harbor Laboratory Press
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full text outside of ProQuest |
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| Resumen: | The accelerated rate of disease emergence in recent decades underscores the need to understand conditions that promote or dampen epidemics. Theoretical models consistently show that epidemics are smaller in populations with higher among-individual heterogeneity in susceptibility. Experimental tests of these predictions are rare but critical for understanding how heterogeneity in susceptibility shapes epidemics in natural systems. We directly link data-parameterized models from previous dose response experiments in the house finch – Mycoplasma gallisepticum system to experimental epidemics in replicated aviary mesocosm flocks. We manipulated flock-level heterogeneity in susceptibility by seeding epidemics in flocks composed of either pathogen-naïve or previously exposed birds, which prior work showed have higher heterogeneity in susceptibility relative to pathogen-naïve populations. We tracked epidemics for over two months, combining empirical data and stochastic compartmental models to address how heterogeneity in susceptibility changes epidemic severity. Consistent with previous work, heterogeneity in susceptibility was higher in flocks given prior pathogen exposure. However, even pathogen-naïve flocks, which had relatively homogeneous susceptibility in previous experiments, were best described by heterogeneous, rather than homogenous, models of susceptibility. This suggests flock-level epidemics captured sources of heterogeneity absent in controlled experiments, such as transmission heterogeneity leading to variable host competence. Finally, although prior exposure conferred protection from disease at the individual level, prior exposure and its associated flock-level heterogeneity did not dampen epidemics as predicted by deterministic models. Further, our stochastic simulations generated a range of outcomes for small epidemics over the timescales examined, underscoring the challenges of measuring transmission dynamics in naturalistic settings.Competing Interest StatementThe authors have declared no competing interest. |
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| ISSN: | 2692-8205 |
| DOI: | 10.1101/2025.01.15.632224 |
| Fuente: | Biological Science Database |