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

在新冠肺炎大流行期间，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化假设的局限性。该项目的研究人员假设，人类行为可能也是导致登革热和寨卡病毒等伊蚊传播的疾病如此难以控制的关键原因。伊蚊在家庭储水容器中产卵，这意味着与储水、用水和水容器管理相关的行为会影响蚊子的数量，从而影响由这些蚊子传播的疾病。该项目的中心目标是了解人类如何就预防伊蚊传播疾病的行动作出决定，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。该项目将把重点放在哥伦比亚的伊巴圭，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。经验性的社会科学研究将调查个人如何对这些干预措施做出反应，并确定不同个体在反应中的差异。数学模型研究将在人口层面评估这些干预措施的有效性。在整个项目中，将培养与社区成员和当地公共卫生官员的密切联系，以确保项目成果的有效转化。培训和能力建设活动将把该项目的影响扩大到伊巴圭以外的环境。该项目旨在从机械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，最终目标是能够更有效地利用公共卫生干预措施。该项目将以伊巴格́的实证社会科学研究为基础，伊巴格是哥伦比亚城市化速度和伊蚊传播疾病传播率最高的城市之一。将使用观察和实验相结合的方法来表征在家庭内部和周围采用防蚊行为的异质性，并了解驱动采用或忽视这些行为的线索。这些经验性的发现将被用来开发一个个人决策的数学模型，该模型围绕着个人层面的行为倾向的蚊子预防行为的使用，随着线索的出现和消失而改变。然后，这一决策模型将被纳入伊蚊传播疾病的基于代理人的模型，该模型将被用于推断公共卫生官员在伊巴格́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，并评估它们捕捉行为干预对流行病学动力学的影响的能力，这些影响是用基于代理的模型模拟的。该项目的最终结果将是开发和验证能够预测流行病动力学对行为干预的反应的最小复杂数学模型。该项目由数学和物理科学局(MPS)的数学科学部(DMS)、既定的激励竞争研究计划(EPSCoR)和社会、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NSF的法定使命，并通过使用基金会的智力优势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.