The Planetary Child Health Observatory: an interdisciplinary research initiative and web-based dashboard for mapping enteric infectious diseases and their risk factors and interventions in LMICs

行星儿童健康观察站：一项跨学科研究计划和基于网络的仪表板，用于绘制中低收入国家肠道传染病及其危险因素和干预措施

• 批准号: 10591991
• 负责人: Josh M Colston
• 金额: $ 13.04万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-20 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10591991
• 关键词: Adult; Age; Area; Bacteria; Big Data; Biological Process; Biometry; COVID-19; Campylobacter; Cessation of life; Child; Child Health; Childhood; Cholera; Climate; Communicable Diseases; Communities; Country; Cryptosporidium; Data; Data Set; Databases; Development; Development Plans; Diagnosis; Diagnostic; Differential Diagnosis; Disease; Disease Outcome; Enteral; Epidemiologist; Etiology; Exclusion; Funding; Geographic Distribution; Geography; Goals; HIV; Health; Health Information System; Household; Interdisciplinary Study; International; Intervention; Lower Respiratory Tract Infection; Malaria; Maps; Marketing; Mentors; Mentorship; Methodology; Methods; Modeling; Modernization; Molecular; Monitor; National Institute of Allergy and Infectious Disease; Norovirus; Online Systems; Outcome; Perception; Personal Satisfaction; Planet Earth; Population; Population Intervention; Populations at Risk; Prevalence; Process; Public Health; Publications; Reporting; Research; Research Activity; Research Personnel; Resolution; Resources; Risk; Risk Factors; Sampling Studies; Secure; Shigella; Source; Standardization; Surveys; Target Populations; Testing; Time; Training; United States National Aeronautics and Space Administration; Universities; Update; Vaccines; Variant; Viral; age group; burden of illness; career development; central database; climate change; comparative; dashboard; diagnostic technologies; disability-adjusted life years; economic outcome; enteric pathogen; evidence base; improved; inter-institutional; large datasets; low and middle-income countries; molecular diagnostics; novel; novel vaccines; pathogen; peer; peer learning; priority pathogen; public repository; remote sensing; skills; sociodemographic factors; sociodemographics; spatiotemporal; stool sample; success; surveillance study; tool; transmission process; trend; vaccine candidate; web page; web portal; years of life lost

PROJECT SUMMARY/ABSTRACT Mapping spatiotemporal variation in the burden of infectious diseases is critical for targeting interventions like vaccines and prioritizing at-risk populations, particularly in Low- and Middle-Income Countries (LMICs), where such diseases are most prevalent. While many priority pathogens have been mapped over entire endemic regions, enteric infectious diseases (EIDs) have not, due to a perception that the necessary spatially referenced data on their prevalence and environmental determinants are not available. However, improvements in differential diagnosis of EIDs, geostatistical methods, and accessibility and accuracy of environmental data mean that it is now possible to carry out such a mapping. The long-term goal of this proposal is to provide the research and stakeholder community with an evidence base for the geographical targeting of enteropathogen-specific child health interventions such as novel vaccines. The overall objective is to apply a big data approach to the modeling of EIDs in combination with advanced geostatistical analyses and global earth observation (EO)- derived datasets, resulting in generalizable estimates of the geographical distribution of these outcomes and of their associations with environmental drivers disseminated via an interactive web-based dashboard. The central hypothesis is that the prevalence of many enteropathogens varies spatiotemporally as a function of climatic, environmental, and socio-demographic factors in a way that can be modelled using global EO datasets and similar products. The rationale underlying the proposed research is that it will enable the identification of target populations for interventions. Specifically, building on existing partnerships between epidemiologists, climatologists, and hydrologists as well as investigators in numerous LMICs, Dr. Colston will: 1) compile and maintain a large database of georeferenced results from studies that diagnosed EIDs in children in LMICs; 2) Apply geostatistical models to EID outcome data (aim 1) and spatiotemporally matched, high resolution environmental covariates to a). draw inferences about underlying biological processes and b). generate prediction maps to identify geographical foci of transmission risk. 3) Establish a Planetary Child Health Observatory (PCHO), an interinstitutional initiative consisting of a). an interactive web-based dashboard and b). an international consortium of investigators. In addition to these research activities, Dr. Colston proposes a career development plan that includes mentorship, experiential and peer-to-peer learning, coursework, publications, and presentations with the objectives of: 1) gaining skills and formal training in geostatistical inference, biostatistics, and large datasets; 2) expanding expertise in applications of environmental and remote sensing-derived datasets in health research; 3) transitioning to research independence by securing follow-on R01 funding. His proposal will be supervised by an outstanding, interdisciplinary mentoring team with complementary methodological and substantive skills. The project will have a positive impact on public health by providing data inputs urgently needed for targeting EID interventions to priority populations in LMICs.

项目概要/摘要 绘制传染病负担的时空变化对于制定干预措施至关重要，例如 疫苗并优先考虑高危人群，特别是在低收入和中等收入国家 (LMIC)，其中 此类疾病最为普遍。虽然许多优先病原体已在整个地方病中被绘制出来 地区，肠道传染病（EID）还没有，因为人们认为必要的空间参考 没有关于其流行率和环境决定因素的数据。然而，改进 EID 的鉴别诊断、地统计方法以及环境数据平均值的可获取性和准确性 现在可以进行这样的映射。该提案的长期目标是提供研究 和利益相关者社区，具有针对特定肠道病原体的地理目标的证据基础 儿童健康干预措施，例如新型疫苗。总体目标是将大数据方法应用于 结合先进的地统计分析和全球地球观测 (EO) 的 EID 建模 - 派生的数据集，从而对这些结果的地理分布和 他们与环境驱动因素的关联通过基于网络的交互式仪表板传播。中央 假设许多肠道病原体的流行随着气候的变化而时空变化， 环境和社会人口因素可以使用全球EO数据集进行建模 类似的产品。拟议研究的基本原理是它将能够识别目标 人群进行干预。具体而言，以流行病学家之间现有的伙伴关系为基础， Colston 博士将与许多中低收入国家的气候学家、水文学家以及研究人员一起：1) 编制和 维护一个大型数据库，其中包含诊断中低收入国家儿童 EID 的研究的地理参考结果； 2） 将地统计模型应用于 EID 结果数据（目标 1）和时空匹配的高分辨率 a) 的环境协变量。对潜在的生物过程做出推论，b).产生 预测地图以确定传播风险的地理焦点。 3) 建立全球儿童健康 观察站 (PCHO)，一项机构间倡议，包括 a)。基于网络的交互式仪表板和 b). 一个国际调查人员联盟。除了这些研究活动之外，科尔斯顿博士还提出了一项 职业发展计划，包括指导、体验式和同伴学习、课程作业、 出版物和演讲，其目的是：1) 获得地质统计方面的技能和正式培训 推理、生物统计学和大型数据集； 2）扩大环境和远程应用方面的专业知识 健康研究中的传感数据集； 3）通过确保后续研究过渡到研究独立性 R01 资金。他的提案将由杰出的跨学科指导团队监督 互补的方法和实质性技能。该项目将对公众健康产生积极影响 提供针对中低收入国家优先人群的 EID 干预措施急需的数据输入。