eMB: Enhancing Mathematical Models to Investigate the Influences of Climate Change on Zoonotic Spillover

大多数传染病的爆发都涉及从动物到人类的传播，称为人畜共患病溢出。一些研究提供证据表明，气候变化可影响人畜共患病外溢的频率和发生。尽管如此，目前的数学模型在很大程度上忽略了气候变化对人畜共患病溢出的影响。通过加强建模方法，这个多学科项目的研究人员试图了解人畜共患病病原体必须克服哪些挑战才能从野生动物宿主传播给人类或其他动物，气候变化如何减少这些挑战，并使人畜共患病病原体更有可能生活在新物种内部和之间，从气候变化的角度看，什么样的环境更有可能发生人畜共患病的外溢。该研究小组将利用数十年的天气、野生动物种群和人畜共患病数据来确定可以纳入模型的重要变量，并准确估计溢出的流行病学预测因素（例如，疾病传播的力量、速度和方向以及基本繁殖数）作为重要天气和环境因素的函数。 校准模型的数值模拟将有助于研究人员阐明人畜共患病生态学的潜在机制，并预测气候变化可能产生的影响。 此外，本研究建立在现有的病原体和人口扩散的波动理论，以推进行波和驻波的理论知识，包括它们的存在性，唯一性，稳定性和渐近行为。用于增强建模和模拟人畜共患病溢出的分析和计算工具、模板代码和教程将在专门用于该项目的GitHub页面上发布。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Most infectious disease outbreaks involve transmission from animals to humans, known as zoonotic spillover. Several studies provide evidence that climate change can influence the frequency and occurrence of zoonotic spillover. Nonetheless, current mathematical models have largely overlooked the effects of climate change on zoonotic spillover. By enhancing the modeling approaches, the researchers of this multidisciplinary project seek to understand what challenges zoonotic pathogens must overcome to transmit from wild animal hosts to humans or other animals, how climate change can reduce these challenges and make it more plausible for zoonotic pathogens to live within and between new species, and what kinds of environments have a higher likelihood of zoonotic spillover in the view of climate change. The research team will use decades of weather, wildlife population, and zoonotic disease data to identify significant variables that can be incorporated into the models and to accurately estimate epidemiological predictors of spillover (e.g., the force, speed, and direction of disease spread and the basic reproduction number) as functions of significant weather and environmental factors. The numerical simulations of the calibrated models will help the researchers elucidate the underlying mechanisms governing the ecology of zoonotic disease and predict possible influences of climate change. Furthermore, this study builds on the existing wave theory of pathogen and population dispersal to advance the theoretical knowledge of traveling and stationary waves, including their existence, uniqueness, stability, and asymptotic behaviors. The analytical and computational tools, template codes, and tutorials for enhanced modeling and simulating zoonotic spillover will be released on a GitHub page dedicated to this project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.