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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

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:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-12-20 至 2027-11-30
关键词:
AdultAgeAreaBacteriaBig DataBiological ProcessBiometryCOVID-19CampylobacterCessation of lifeChildChild HealthChildhoodCholeraClimateCommunicable DiseasesCommunitiesCountryCryptosporidiumDataData SetDatabasesDevelopmentDevelopment PlansDiagnosisDiagnosticDifferential DiagnosisDiseaseDisease OutcomeEnteralEpidemiologistEtiologyExclusionFundingGeographic DistributionGeographyGoalsHIVHealthHealth Information SystemHouseholdInterdisciplinary StudyInternationalInterventionLower Respiratory Tract InfectionMalariaMapsMarketingMentorsMentorshipMethodologyMethodsModelingModernizationMolecularMonitorNational Institute of Allergy and Infectious DiseaseNorovirusOnline SystemsOutcomePerceptionPersonal SatisfactionPlanet EarthPopulationPopulation InterventionPopulations at RiskPrevalenceProcessPublic HealthPublicationsReportingResearchResearch ActivityResearch PersonnelResolutionResourcesRiskRisk FactorsSampling StudiesSecureShigellaSourceStandardizationSurveysTarget PopulationsTestingTimeTrainingUnited States National Aeronautics and Space AdministrationUniversitiesUpdateVaccinesVariantViralage groupburden of illnesscareer developmentcentral databaseclimate changecomparativedashboarddiagnostic technologiesdisability-adjusted life yearseconomic outcomeenteric pathogenevidence baseimprovedinter-institutionallarge datasetslow and middle-income countriesmolecular diagnosticsnovelnovel vaccinespathogenpeerpeer learningpriority pathogenpublic repositoryremote sensingskillssociodemographic factorssociodemographicsspatiotemporalstool samplesuccesssurveillance studytooltransmission processtrendvaccine candidateweb pageweb portalyears of life lost

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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.
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