Data from: Contact and contagion: bighorn sheep demographic states vary in probability of transmission given contact

1. Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because probability of transmission given contact is notoriously difficult to measure. Here we present a first step toward empirically investigating probability of transmission given contact in free-ranging wildlife. 2. We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae, an agent responsible for bighorn sheep pneumonia. 3. We built covariates using contact network metrics, demographic information, and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but we also built covariates that broke the network metrics into particular categories that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections. 4. Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between lambs. 5. Although yearlings and non-reproductive bighorn ewes regularly carried Mycoplasma ovipneumoniae, our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals who carry pathogens but rarely transmit. 6. This analysis demonstrates a simple logistic regression approach for testing a priori hypotheses about variation in odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology.1. 同时掌握接触行为与接触后传播概率，是管控野生动物疾病的核心要点。然而，野生动物疾病研究往往侧重于接触异质性（contact heterogeneity），部分原因在于接触后传播概率的测量难度极高。本研究针对自由活动野生动物（free-ranging wildlife）的接触后传播概率展开实证探索，为该领域的研究迈出了第一步。 2. 本研究利用实测接触网络（contact network），检验大角羊的种群统计特征是否在传染性与对绵羊肺炎支原体（Mycoplasma ovipneumoniae）的易感性上存在系统性差异——该病原体是引发大角羊肺炎的致病菌。 3. 我们基于接触网络指标、种群统计信息与感染状态构建协变量（covariate），并通过逻辑回归（logistic regression）将这些协变量与羔羊存活率进行关联分析。协变量集包含描述节点中心性的经典网络指标——度（degree）；同时还构建了按特定类别拆分网络指标的协变量，以区分与一岁龄羊、带羔母羊、无羔母羊，以及存在/不存在活动性感染个体的接触差异。 4. 一岁龄羊、带羔母羊与无羔母羊展现出相似的群体归属模式，但羔羊与繁殖母羊间的直接肢体接触发生率，较任意成年个体类群间或成年个体与一岁龄羊间的接触率高出两个数量级，较羔羊间的直接接触率高出一个数量级。 5. 尽管一岁龄羊与非繁殖大角羊母羊常携带绵羊肺炎支原体（Mycoplasma ovipneumoniae），但我们的模型结果显示，与感染繁殖母羊的一次接触，其引发羔羊死亡事件的优势比约为与感染空怀母羊或一岁龄羊进行同等接触的5倍。据此，针对感染个体的管理措施可能会不必要地移除那些携带病原体但极少发生传播的年轻个体。 6. 本分析提出了一种简便的逻辑回归分析框架，可用于检验关于自由活动野生动物宿主接触后传播优势比变异的先验假设，且该方法可广泛应用于野生动物疾病生态学研究领域。