Models for improving surveillance of environmentally-mediated infectious diseases

改善环境介导的传染病监测的模型

基本信息

批准号：
8415962
负责人：
Justin V Remais
金额：
$ 12.85万
依托单位：
EMORY UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-02-01 至 2016-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8415962
关键词：
Accounting China Communicable Diseases Coupled Coupling Data Data Set Decision Making Dimensions Disease Disease Outbreaks Disease Outcome Distant Environment Environmental Risk Factor Epidemiology Foundations Graph Heterogeneity Human Infection Knowledge Lead Life Measures Mediating Methods Metric Modeling Organism Outcome Parasites Process Province Public Health Research Research Activity Research Personnel Risk Schistosoma Schistosoma japonicum Schistosomiasis Sentinel Series Services Site Staging Statistical Methods Surveys System Techniques Temperature Testing Theoretical model Time Training Tropical Disease Work base career development disease transmission environmental change epidemiological model improved innovation longitudinal database mathematical model neglect network models novel prevent research and development skills theories transmission process vector

项目摘要

DESCRIPTION (provided by applicant): Schistosomiasis, like many other neglected tropical diseases, has strong associations with dynamic climactic, ecological, hydrological and other environmental phenomena, raising an important opportunity for public health decision-making. Because disease persistence and establishment are highly dependent on environmental phenomena, spatial and temporal environmental datasets have the potential to inform public health actions, such as where and when to focus surveillance efforts. This application provides multiple modes of training to the applicant in advanced numerical and statistical methods, applied to the optimization of schistosomiasis surveillance in the presence of environmental heterogeneity in Sichuan Province, China. Surveillance for Schistosoma parasites in China is currently guided by analytical models with key limitations, including simplistic, isotropic spatial functions that perform poorly for environmentally-mediated organisms, and crude phenomenological representations of environmental processes. The specific aims of this proposal are: 1) to assemble a world-class Schistosoma japonicum epidemiological dataset, combining surveillance and research data into a cohesive, longitudinal database; 2) to quantitatively attribute the effects of multiple environmental drivers at varying scales on dynamic Schistosoma outcomes using novel statistical and mathematical approaches, including spatially explicit, graph-theoretic models and time-series approaches allowing for transient coupling; and 3) to optimize Schistosoma surveillance campaigns in Sichuan using models developed in Aim 2, evaluating predictions using historical and contemporary data. The career development and research activities proposed in this application will lead to a more rigorous quantification of environmental drivers of schistosomiasis, more accurate modeling of the spatial and temporal dimensions of risk, and improved selection of surveillance sites and survey timing. The resulting techniques will be generalized for use in other systems where they can be applied to decision-making support in the face of environmental change. The research builds on the candidate's foundation of skills, leveraging existing data and knowledge to support his transition to a productive independent investigator. PUBLIC HEALTH RELEVENCE: Human parasites like schistosomes are known to be highly sensitive to environmental factors. Understanding how these parasites respond to changes in temperature, rainfall and vegetation can be used to inform public health decision-making, such as where and when to focus surveillance for disease outbreaks. The proposed study will be the first to investigate how environmental information can be used to improve public health activities to prevent new parasite infections.

描述（由申请人提供）：血吸虫病与许多其他被忽视的热带病一样，与动态气候、生态、水文和其他环境现象密切相关，为公共卫生决策提供了重要机会。由于疾病的持续存在和建立高度依赖于环境现象，空间和时间环境数据集有可能为公共卫生行动提供信息，例如在何时何地集中监测工作。该应用程序为申请人提供了先进数值和统计方法的多种培训模式，应用于中国四川省存在环境异质性的情况下优化血吸虫病监测。中国血吸虫寄生虫的监测目前以分析模型为指导，但存在主要局限性，包括对环境介导的生物体表现不佳的简单化、各向同性的空间函数，以及环境过程的粗略现象学表征。该提案的具体目标是：1）建立世界级的日本血吸虫流行病学数据集，将监测和研究数据结合成一个有凝聚力的纵向数据库； 2) 使用新颖的统计和数学方法，包括空间明确的图论模型和允许瞬态耦合的时间序列方法，定量归因不同规模的多个环境驱动因素对动态血吸虫结果的影响； 3) 使用目标 2 中开发的模型优化四川血吸虫监测活动，并使用历史和当代数据评估预测。本申请中提出的职业发展和研究活动将导致对血吸虫病的环境驱动因素进行更严格的量化，对风险的空间和时间维度进行更准确的建模，并改进监测地点和调查时间的选择。由此产生的技术将被推广用于其他系统，在面对环境变化时它们可以应用于决策支持。该研究建立在候选人的技能基础上，利用现有的数据和知识来支持他向富有成效的独立调查员的转变。公共卫生相关性：众所周知，血吸虫等人类寄生虫对环境因素高度敏感。了解这些寄生虫如何应对温度、降雨和植被的变化，可以为公共卫生决策提供信息，例如在何时何地集中监测疾病爆发。拟议的研究将首次调查如何利用环境信息来改善公共卫生活动，以预防新的寄生虫感染。