Abstract Incorporating host behavioral variation into epidemiological models is important for predicting host-pathogen dynamics. Animals living at high densities or with many strong social connections are predicted to have greater risk of acquiring pathogens. Using social network analysis, we tested the hypothesis that variation in the strength of social connections would influence simulated elk ( Cervus canadensis ) pathogen dynamics. We quantified fine-scale social connections for captive elk at three experimentally manipulated densities and wild elk at two natural densities. We applied susceptible-infected epidemiological models to networks to infer the relationship between fine-scale host sociality and simulated pathogen dynamics. Networks were filtered based on four association thresholds to determine how variation in the strength of social connections influenced pathogen dynamics. Our simulations suggest that social behavior interacts with population density to predict pathogen dynamics, but this effect was sex-specific. For both males and females at higher density, elk had strong social connections, resulting in higher number of infected individuals. We observed differences in social connections across density, and these results translated to our simulations, which predicted density-dependent pathogen dynamics for captive and wild elk networks. Our results highlight host social behavior as a potential mechanism driving variation in the relationship between population density and pathogen dynamics. Elk are reservoir hosts for numerous emerging infectious diseases, and our models suggest that density-dependent host social behavior could influence pathogen dynamics in elk social networks. Significance statement Animal population density can influence transmission of parasites and pathogens, but variation in social connections at different densities could impact this relationship. Using social network analysis and epidemiological simulations, we tested the hypothesis that density-dependent variation in social connections would influence pathogen dynamics using captive and free-ranging populations of elk ( Cervus elaphus ). For all elk groups, simulated number of infected individuals increased with social connectedness. In addition, our simulations suggest that social connectedness interacts with population density to predict number of infected individuals, but this effect was sex-specific. For males and females at high density, elk had strong social connections, resulting in more infected individuals; this relationship was linear for males and non-linear for females. Taken together, our results suggest fine-scale measures of social behavior vary with population density, a result which could have implications for pathogen dynamics.

中文翻译：

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社交网络连接的异质性取决于密度：对群居有蹄类动物疾病动态的影响

摘要 将宿主行为变异纳入流行病学模型对于预测宿主-病原体动态非常重要。预计生活在高密度或具有许多强大社会关系的动物感染病原体的风险更大。使用社交网络分析，我们测试了社会联系强度的变化会影响模拟麋鹿（Cervus canadensis）病原体动态的假设。我们量化了三种实验操作密度下圈养麋鹿和两种自然密度下野生麋鹿的精细社会关系。我们将易感感染的流行病学模型应用于网络，以推断精细宿主社会性与模拟病原体动态之间的关系。根据四个关联阈值过滤网络，以确定社会联系强度的变化如何影响病原体动态。我们的模拟表明，社会行为与人口密度相互作用以预测病原体动态，但这种影响是性别特异性的。对于密度较高的雄性和雌性，麋鹿具有很强的社会联系，导致感染人数更多。我们观察到不同密度的社会联系的差异，并将这些结果转化为我们的模拟，该模拟预测了圈养和野生麋鹿网络的密度依赖性病原体动态。我们的结果强调宿主社会行为是驱动人口密度和病原体动态之间关系变化的潜在机制。麋鹿是许多新发传染病的宿主，我们的模型表明，密度依赖的宿主社会行为可能会影响麋鹿社交网络中的病原体动态。意义声明 动物种群密度会影响寄生虫和病原体的传播，但不同密度的社会联系的变化可能会影响这种关系。使用社交网络分析和流行病学模拟，我们使用圈养和自由放养的麋鹿种群 (Cervus elaphus) 检验了社会联系的密度依赖性变化会影响病原体动态的假设。对于所有麋鹿群体，模拟的感染个体数量随着社会联系的增加而增加。此外，我们的模拟表明，社会联系与人口密度相互作用以预测受感染个体的数量，但这种影响具有性别特异性。对于高密度的雄性和雌性，麋鹿有很强的社会联系，导致更多的个体被感染；这种关系对男性来说是线性的，而对女性来说是非线性的。综上所述，我们的结果表明，社会行为的精细尺度测量因人口密度而异，这一结果可能对病原体动态产生影响。