Land Use Change, Transmission Potential Networks and Disease Spread in Madagascar

马达加斯加的土地利用变化、传播潜力网络和疾病传播

• 批准号: 10609831
• 负责人: Charles Nunn
• 金额: $ 23.1万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-17 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10609831
• 关键词: Agriculture; Animals; Antibodies; Area; Astrovirus; Babesia; Bacteria; Characteristics; Communicable Diseases; Communities; Competence; Coupled; Data; Databases; Dimensions; Disease; Disease Pathway; Domestic Animals; Education; Farm; Goals; Habitats; Health; Helminths; Host-Parasite Relations; Household; Human; Human Activities; Individual; Infection; Infectious Agent; Laboratories; Lead; Leptospira; Location; Madagascar; Mammals; Mathematics; Methods; Modeling; Molecular; Organism; Ownership; Parasites; Pathway interactions; Pattern; Persons; Population; Positioning Attribute; Prevalence; Primates; Protozoa; Public Health; Research; Research Personnel; Rice; Rickettsia; Rural; Sampling; Sampling Biases; Sampling Studies; Scientist; Serology; Shapes; Site; Social Network; Socioeconomic Factors; Structure; Surveys; System; Testing; Ungulate; Variant; Vector-transmitted infectious disease; Virus; Yersinia; Yersinia pestis; Zoonoses; agricultural activity; analytical method; anthropogenesis; comparative; data integration; disease transmission; experimental study; forest; gastrointestinal; human subject; innovation; land use; low income country; multiple data sources; novel strategies; parasitism; pathogen; predictive modeling; screening; simulation; social; social contact; social relationships; socioeconomics; transmission process

Anthropogenic land use alters ecological communities, leading to the question: How do these changes alter infectious disease transmission, including to humans? This question is especially important in low-income countries such as Madagascar, where zoonotic diseases remain major threats to public health. The proposed research aims to model the ecological and socioeconomic factors that influence disease spread and predict how infectious agents spread from small mammals and domesticated animals to people. This goal will be pursued through innovative and interdisciplinary field, laboratory, and analytical approaches. The team of ecologists, social scientists, and a mathematician will integrate and model ecological and socioeconomic data from the field site in rural Madagascar, which includes a protected area surrounded by native forest fragments, agricultural fields, and villages of subsistence agriculturalists. Around four villages and in the park, the team will investigate multiple hypotheses concerning how human land use activities shape zoonotic disease transmission. To extend the findings globally, the researchers will use the Global Mammal Parasite Database to investigate how human land use and network connectivity impact host-parasite relationships and prevalence. The interdisciplinary team is uniquely positioned to investigate infectious disease transmission in this system. By integrating multiple data sources into unified mathematical representations, the team will investigate specific hypotheses for how diseases spread using multilayer transmission potential networks (TPNs). Significantly, they will test how TPNs and disease transmission change with human activities and identify the socioeconomic factors that lead some people to be more connected into transmission networks. Specifically, the team will: (i) identify pathways of disease transmission using cutting-edge field and analytical methods, coupled with infectious disease data representing multiple transmission modes; (ii) investigate socioeconomic characteristics of individual humans that most strongly connect them into TPNs of wildlife and domesticated animals; (iii) characterize how human activities generate entry points of infectious disease. Comparative analyses will extend the findings beyond the Malagasy study system. TPNs will be based on trapping data for small mammals, GPS data for people and domesticated animals, and social network surveys for people. The team will test whether these networks predict infection with multiple pathogens, including Leptospira, Yersinia, Babesia, Rickettsia, and gastrointestinal helminths. The research team has all necessary permits, extensive on-the-ground logistical support, and substantial pilot data on human and animal populations at the site.

人为土地使用改变了生态群落，导致了一个问题：这些变化如何改变传染病的传播，包括人类？这个问题在马达加斯加等低收入国家中尤为重要，那里的人畜共患病仍然对公共卫生造成了主要威胁。拟议的研究旨在模拟影响疾病传播的生态和社会经济因素，并预测传染性药物如何从小型哺乳动物和驯养动物传播到人们。该目标将通过创新和跨学科的领域，实验室和分析方法来实现。生态学家，社会科学家和数学家团队将从马达加斯加乡村的田间现场整合并模拟生态和社会经济数据，其中包括一个被本地森林碎片，农业田地和自给自足农业家村庄所包围的保护区。在四个村庄和公园中，团队将调查有关人类使用活动如何塑造人畜共患病传播的多个假设。为了扩展全球的发现，研究人员将使用全球哺乳动物寄生虫数据库来研究人类土地使用和网络连通性如何影响宿主 - 寄生虫的关系和流行。跨学科团队在该系统中的传染病传播方面具有独特的位置。通过将多个数据源集成到统一的数学表示中，该团队将研究使用多层传输潜力网络（TPN）如何传播疾病的特定假设。值得注意的是，他们将测试TPN和疾病传播如何随着人类活动的变化，并确定导致某些人更加联系到传输网络的社会经济因素。具体而言，团队将：（i）使用尖端领域和分析方法确定疾病传播的途径，再加上代表多种传播模式的传染病数据； （ii）调查各个人类的社会经济特征，这些特征最强烈地将它们连接到野生动物和驯养动物的TPN中； （iii）表征人类活动如何产生传染病的入口点。比较分析将把发现扩展到马达加斯加研究系统之外。 TPN将基于捕获小型哺乳动物的数据，人和家养动物的GPS数据以及对人的社交网络调查。该团队将测试这些网络是否预测了多种病原体的感染，包括钩端螺旋体，耶尔森氏菌，巴贝西亚，立克赛和胃肠道舵。研究团队拥有所有必要的许可证，广泛的现场后勤支持以及对现场人类和动物种群的大量试点数据。