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.

人为的土地利用改变了生态群落，导致了这样一个问题：这些变化如何改变传染病的传播，包括对人类的传播？这个问题在马达加斯加等低收入国家尤其重要，因为人畜共患疾病仍然是公共卫生的主要威胁。该研究旨在模拟影响疾病传播的生态和社会经济因素，并预测传染病如何从小型哺乳动物和家养动物传播给人类。这一目标将通过创新和跨学科领域、实验室和分析方法来实现。这个由生态学家、社会科学家和一名数学家组成的团队将对来自马达加斯加农村实地的生态和社会经济数据进行整合和建模，其中包括一个被原始森林碎片、农田和自给自足的农民村庄包围的保护区。在四个村庄和公园内，研究小组将调查关于人类土地利用活动如何影响人畜共患疾病传播的多种假设。为了在全球范围内扩展这些发现，研究人员将使用全球哺乳动物寄生虫数据库来调查人类土地利用和网络连接如何影响宿主-寄生虫关系和流行。该跨学科团队在研究该系统中的传染病传播方面具有独特的优势。通过将多个数据源整合到统一的数学表示中，该团队将研究疾病如何使用多层传播电位网络（TPNs）传播的具体假设。重要的是，他们将测试tpn和疾病传播如何随着人类活动而变化，并确定导致一些人更多地与传播网络联系在一起的社会经济因素。具体而言，该小组将：(i)利用前沿领域和分析方法，结合代表多种传播模式的传染病数据，确定疾病传播途径；（ii）调查人类个体的社会经济特征，这些特征与野生动物和驯养动物的TPNs最密切相关；描述人类活动如何产生传染病的进入点。比较分析将把研究结果扩展到马达加斯加研究系统之外。tpn将基于小型哺乳动物的诱捕数据，人类和家养动物的GPS数据，以及人类的社会网络调查。该团队将测试这些网络是否能预测多种病原体的感染，包括钩端螺旋体、耶尔森氏菌、巴贝斯虫、立克次体和胃肠道蠕虫。研究小组获得了所有必要的许可，广泛的实地后勤支持，以及关于该地点人类和动物种群的大量试点数据。