Linking Bioenergetics and Parasite Transmission Models Suggests Mismatch Between Snail Host Density and Production of Human Schistosomes
| Autor: | Matthew Malishev, David J. Civitello |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0106 biological sciences
0301 basic medicine media_common.quotation_subject Ecology (disciplines) Dynamic energy budget Parasitism Plant Science 010603 evolutionary biology 01 natural sciences Competition (biology) Host-Parasite Interactions 03 medical and health sciences Animals Humans Parasite hosting media_common Population Density Biomphalaria biology Ecology Intermediate host Schistosoma mansoni biology.organism_classification 030104 developmental biology Human parasite Animal Science and Zoology Energy Metabolism |
| Zdroj: | Integrative and Comparative Biology. 59:1243-1252 |
| ISSN: | 1557-7023 1540-7063 |
| DOI: | 10.1093/icb/icz058 |
| Popis: | The consequences of parasite infection for individual hosts depend on key features of host–parasite ecology underpinning parasite growth and immune defense, such as age, sex, resource supply, and environmental stressors. Scaling these features and their underlying mechanisms from the individual host is challenging but necessary, as they shape parasite transmission at the population level. Translating individual-level mechanisms across scales could inherently improve the way we think about feedbacks among parasitism, the mechanisms driving transmission, and the consequences of human impact and disease control efforts. Here, we use individual-based models (IBMs) based on general metabolic theory, Dynamic Energy Budget (DEB) theory, to scale explicit life-history features of individual hosts, such as growth, reproduction, parasite production, and death, to parasite transmission at the population level over a range of resource supplies focusing on the major human parasite, Schistosoma mansoni, and its intermediate host snail, Biomphalaria glabrata. At the individual level, infected hosts produce fewer parasites at lower resources as competition increases. At the population level, our DEB–IBM predicts brief, but intense parasite peaks early during the host growth season when resources are abundant and infected hosts are few. The timing of these peaks challenges the status quo that high densities of infected hosts produce the highest parasite densities. As expected, high resource supply boosts parasite output, but parasite output also peaks at modest to high host background mortality rates, which parallels overcompensation in stage-structured models. Our combined results reveal the crucial role of individual-level physiology in identifying how environmental conditions, time of the year, and key feedbacks within host–parasite ecology interact to define periods of elevated risk. The testable forecasts from this physiologically-explicit epidemiological model can inform disease management to reduce human risk of schistosome infection. |
| Databáze: | OpenAIRE |
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