Collaborative Research: IHBEM: Three-way coupling of water, behavior, and disease in the dynamics of mosquito-borne disease systems

在COVID-19大流行期间，对来自公共卫生官员、社交媒体和其他地方的信息的复杂行为反应暴露了流行病学模型传统上对人类行为做出的简单假设的局限性。该项目的研究人员假设，人类行为也可能在伊蚊传播的疾病（如登革热和寨卡病毒）如此难以控制的原因中发挥关键作用。伊蚊在家庭储水容器中产卵，这意味着与储水、用水和储水容器管理有关的行为会影响蚊子种群，从而影响这些蚊子传播的疾病。该项目的中心目标是了解人类如何对伊蚊传播疾病的预防行动作出决定，以及这些行动如何反过来影响疾病动态和随后的个人一级决策。该项目将重点放在哥伦比亚的伊巴格瓦伊市，那里的公共卫生官员长期以来一直使用行为方法来干预伊蚊传播的疾病。实证社会科学研究将调查个体对这些干预措施的反应，并描述个体之间反应的差异。数学模型研究将在人口水平上估计这些干预措施的有效性。在整个项目期间，将培养与社区成员和当地公共卫生官员的密切联系，以确保有效地转化项目成果。培训和能力建设活动将把项目的影响扩大到巴拉圭以外的地区。该项目旨在从机制上理解行为在传染病动力学中的作用，以及能够解释这些机制的数学建模工具，其最终目标是能够更有效地利用公共卫生干预措施。该项目将以伊巴格瓦伊的实证社会科学研究为基础。伊巴格瓦伊是哥伦比亚城市化率和伊蚊传播率最高的城市之一。将采用观察和实验相结合的方法来表征在家中和周围采取蚊虫预防行为的异质性，并了解推动采取或忽视这些行为的线索。这些实证研究结果将被用于开发一个数学模型，该模型围绕使用蚊子预防行为来响应个人层面的行为倾向，这些行为倾向随着时间的推移随着线索的出现和消退而变化。然后，该决策模型将被纳入基于主体的伊蚊传播模型，该模型将用于推断公共卫生官员用于控制伊蚊传播疾病的行为干预措施的有效性。最后，将开发一套更简单的宏观模型，并评估其捕捉行为干预对基于主体的模型模拟的流行病学动态的影响的能力。该项目的最终成果将是开发和验证能够预测流行病学动态对行为干预的反应的最小复杂度数学模型。该项目由数学和物理科学局（MPS）的数学科学部（DMS）、刺激竞争研究的既定计划（EPSCoR）以及社会、行为和经济科学局（SBE）的社会和经济科学部（SES）共同资助。该奖项反映了美国国家科学基金会的法定使命，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。

Complex behavioral responses to information from public health officials, social media, and elsewhere during the COVID-19 pandemic laid bare the limitations of the simplistic assumptions that epidemiological models have traditionally made about human behavior. The investigators of this project hypothesize that human behavior may also play a key role in why diseases transmitted by Aedes mosquitoes, such as dengue and Zika, have been so difficult to control. Aedes mosquitoes lay eggs in household water storage containers, meaning that behaviors related to water storage, water consumption, and water container management impact mosquito populations and, thereby, diseases transmitted by these mosquitoes. The central objective of this project is to understand how humans make decisions about preventive actions against Aedes-borne diseases and how those actions in turn affect disease dynamics and subsequent individual-level decision-making. The project will focus on the city of Ibagué, Colombia, where public health officials have long used behavioral approaches to intervene against Aedes-borne diseases. Empirical social science research will investigate how individuals respond to these interventions and characterize differences among individuals in their responses. Mathematical modeling research will estimate the effectiveness of these interventions at the population level. Throughout the project, a close connection with community members and local public health officials will be cultivated to ensure the effective translation of project outcomes. Training and capacity building activities will extend the impacts of the project to settings beyond Ibagué.This project aims to develop a mechanistic understanding of the role of behavior in infectious disease dynamics and mathematical modeling tools that are capable of accounting for those mechanisms, with the ultimate goal of enabling more effective use of public health interventions. The project will be grounded in empirical social science research in Ibagué, a city in Colombia with one of the highest urbanization rates and Aedes-borne disease transmission rates in the country. A combination of observational and experimental approaches will be used to characterize heterogeneity in the adoption of mosquito prevention behaviors in and around the home and to understand the cues that drive the adoption, or neglect, of those behaviors. These empirical findings will be used to develop a mathematical model of individual decision-making around the use of mosquito prevention behaviors in response to individual-level behavioral dispositions that change over time as cues arise and subside. This decision-making model will then be incorporated into an agent-based model of Aedes-borne disease transmission that will be used to infer the effectiveness of behavioral interventions that public health officials use to control Aedes-borne diseases in Ibagué. Finally, a suite of simpler macroscopic models will be developed and assessed with respect to their ability to capture effects of behavioral interventions on epidemiological dynamics simulated with the agent-based model. The ultimate outcome of the project will be the development and validation of minimally complex mathematical models that are capable of predicting responses of epidemiological dynamics to behavioral interventions.This project is jointly funded by the Division of Mathematical Sciences (DMS) in the Directorate of Mathematical and Physical Sciences (MPS), the Established Program to Stimulate Competitive Research (EPSCoR), and the Division of Social and Economic Sciences (SES) in the Directorate of Social, Behavioral and Economic Sciences (SBE).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.