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

项目摘要/摘要 绘制传染病负担的时空变化图对于针对性干预至关重要，例如 疫苗和优先考虑高危人群，特别是在低收入和中等收入国家， 这类疾病最为普遍。虽然许多优先病原体已经被绘制成整个地方性疾病的地图 在各地区，肠道传染病(EID)还没有，因为人们认为有必要在空间上参考 没有关于它们的流行率和环境决定因素的数据。然而，改进了 EID的区别诊断、地统计学方法以及环境数据的可获得性和准确性 现在可以进行这样的测绘了。这项提议的长期目标是提供研究 和利益相关者社区，拥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，如新型疫苗。总体目标是将大数据方法应用于 结合先进的地质统计分析和全球地球观测(EO)的EID建模- 派生数据集，从而对这些结果的地理分布和 他们与环境驱动因素的联系通过基于网络的互动仪表板传播。中环 假设许多肠道病原体的流行在时空上随着气候的变化而变化， 环境和社会人口因素，可以使用全球EO数据集和 类似的产品。拟议研究的基本原理是，它将使识别目标成为可能 用于干预的人群。具体地说，在流行病学家之间现有的伙伴关系的基础上， 气候学家、水文学家以及众多LMIC的研究人员，科尔斯顿博士将：1)汇编和 维护一个大型数据库，其中包含诊断LMICs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、高分辨率 环境协变量到a)。得出关于潜在生物过程的推论和b)。生成 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 天文台(PCHO)，这是一项机构间倡议，由一个)。基于Web的交互式仪表板和b)。 一个由国际调查人员组成的联盟。除了这些研究活动，科尔斯顿博士还提出了一个 职业发展计划，包括指导、体验式和点对点学习、课程工作、 出版物和演示文稿，目的是：1)获得地质统计学方面的技能和正规培训 推论、生物统计学和大数据集；2)扩展环境和遥感应用方面的专业知识 健康研究中的传感衍生数据集；3)通过确保后续行动过渡到研究独立性 R01基金。他的建议将由一个杰出的跨学科指导团队监督，该团队将 方法和实质性技能相辅相成。该项目将通过以下方式对公共卫生产生积极影响 向低收入国家优先人群提供针对EID干预措施所急需的数据输入。

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.