Impacts of phenology on disease transmission dynamics

拟议的项目是一项全面的努力，以严格调查物候学的贡献- 或季节性活动-使用3种广泛传播的人畜共患病病原体传播动力学 被黑腿的扁虱。季节性活动模式和生活史事件的变化，这是很好的 记录在居住在温带地区的物种中，可以导致显著的种群动态，包括 人口灭绝或爆炸。物候在时间和地理上的变化也改变了 物种间相互作用的频率和强度以及病原体传播的机会， 这可能对病原体传播动力学和人类疾病风险产生深远影响。尽管 对公众健康的可能重要性，物候变化对疾病传播的影响 在许多复杂的人畜共患病系统中，动力学研究仍然明显不足。由扁虱传播的 北美疾病系统提供了理想的系统来确定物候对 病原体传播动力学，无论是理论上还是经验上。我们将构建和评估可解决方案 分析模型、计算模型和高级统计模型，所有这些都明确 结合扁虱的季节性活动，并用来自自然野外的经验数据验证这些模型。 拟议的项目将(1)确定不同物候情景对 3种人类病原体的传播动力学以及由此产生的疾病风险，(2)经验评估模型 预测，以及(3)确定导致不同 病原菌种间传播动态结果。我们将开发3个建模框架来 调查物候对传播动态的影响，识别和量化物候和 3种重要人类病原体传播动力学的环境驱动因素，并进行了经验验证 理论模型和统计模型的结果。两种物候驱动因素的经验验证 而模型预测不仅对公共卫生管理至关重要，而且对识别机械性 驱动这些模式的过程。这项拟议的研究提供了理论和实证两方面的支持。 研究物候对多种疾病传播动力学影响的框架 涉及多种寄主物种或生命阶段的系统--从病媒植物病原体到病原体 具有多主机生命周期。

The proposed projects are a comprehensive effort to rigorously investigate the contribution of phenology - or seasonal activity - to pathogen transmission dynamics using 3 widespread zoonotic pathogens carried by black-legged ticks. Variation in seasonal activity patterns and life-history events, which are well documented in species inhabiting temperate regions, can result in dramatic population dynamics including population extinctions or explosions. Phenological variation across time and geography also alters the frequency and strength of inter-species interactions and thus opportunities for pathogen transmission, which likely has profound impacts on pathogen transmission dynamics and human disease risk. Despite the likely importance to public health, the consequences of phenological variation on disease transmission dynamics remain notably under-studied in many complex zoonotic disease systems. The tick-borne disease system in North America provides the ideal system to determine the impact of phenology on pathogen transmission dynamics both theoretically and empirically. We will build and evaluate solvable analytical models, computational models, and advanced statistical models, all of which explicitly incorporate tick seasonal activity, and validate these models with empirical data from natural field sites. The proposed projects will (1) determine the quantitative impact of different phenological scenarios on the transmission dynamics of, and thus disease risk from, 3 human pathogens, (2) empirically evaluate model predictions, and (3) identify specific phenological and environmental features that result in different transmission dynamic outcomes among pathogen species. We will develop 3 modeling frameworks to investigate the impact of phenology on transmission dynamics, identify and quantify phenological and environmental drivers of transmission dynamics in 3 important human pathogens, and empirically validate the outcomes of the theoretical and statistical models. Empirical validation of both the phenological drivers and model predictions is essential not only for public health management but also to identify mechanistic processes driving these patterns. The proposed research provides both theoretical and empirical frameworks to investigate the impact of phenology on transmission dynamics in the multitude of disease systems involving multiple host species or life-stages from insect-vectored plant pathogens to pathogens with multi-host life-cycles.