Collaborative Research: Community Ecology of Disease: Control of Epidemics by Species Interactions

新的疾病继续出现在动物种群中。 这一令人不安的趋势引发了关于疾病的挑战性问题，例如，为什么有些人受到感染，而另一些人没有？ 最近，生态学家怀疑其他物种，例如那些为宿主提供食物，与宿主竞争食物，捕食生病宿主的物种，可以抑制或促进疾病传播。 因此，与其他物种的相互作用可能会影响野生动物疾病的分布。 然而，这种可能性的探索需要整合流行病学与社区生态学。 很少有疾病系统提供这种整合的机会，但霍尔和卡塞雷斯的目标是利用水生寄生虫（真菌）-宿主（水蚤）系统开发一种实验上易于处理的系统。 他们将利用几十年来对水蚤的研究，将水蚤作为藻类的食草动物，作为藻类的其他浮游动物的竞争者，以及作为鱼类和无脊椎动物的猎物。 这些相互作用中的每一种都可能影响疾病在水蚤宿主中的传播。 例如，食物资源的数量和质量会影响寄生虫感染形式的产生。 然而，因为它们消耗但不产生这些感染形式，其他的益生菌竞争者可能会减少疾病。 最后，捕食者可以通过吃受感染的宿主来抑制疾病。 这些机制是复杂的，因此将通过构建数学模型，使用实验改进这些模型，并通过流行病的观察来测试模型预测来解决。 在这项研究中检查的过程和建模工作应该适用于许多其他疾病系统。 最终，这项工作将产生可以指导理解和控制野生动物种群疾病的理论。

New diseases continue to appear in animal populations. This disturbing trend prompts challenging questions about disease, such as, why do some populations become infected and not others? Recently, ecologists have suspected that other species, such as those that provide food for hosts, compete with hosts for food, and prey on sick hosts, can inhibit or facilitate disease spread. Therefore, interactions with other species may influence the distribution of wildlife disease. However, an exploration of this possibility requires an integration of epidemiology with community ecology. Few disease systems offer opportunities for such integration, but Hall and Caceres aim to exploit an experimentally tractable one using an aquatic parasite (fungus)-host (water flea, Daphnia) system. They will harness decades of study of Daphnia as grazers of algae, as competitors with other zooplankton for that algae, and as prey for fishes and invertebrates. Each of these interactions likely influences disease spread among the Daphnia hosts. For instance, quantity and quality of food resources influence the production of infective forms of the parasite. However, because they consume but do not produce these infective forms, other planktonic competitors may reduce disease. Finally, predators may inhibit disease by eating infected hosts. These mechanisms are complex and will thus be addressed by constructing mathematical models, refining those models using experiments, and testing model predictions with observations of epidemics. The processes examined in this study and the modeling work should apply to many other disease systems. Ultimately, this work will produce theories that can guide efforts to understand and control disease in wildlife populations.