Relationship Between Multiple Environmental Exposures and CVD Incidence and Survival: Vulnerability and Susceptibility
Relationship Between Multiple Environmental Exposures and CVD Incidence and Survival: Vulnerability and Susceptibility
批准号:
10163485
负责人:
Francesca Dominici
金额:
$24.67万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-18 至 2022-11-30
关键词:
AddressAdoptedAir PollutantsAir PollutionAlgorithmsCessation of lifeCodeCollaborationsCommunitiesComputer softwareDataData AggregationData ScienceData SetDependenceDevelopmentDockingDocumentationEnsureEnvironmental ExposureEnvironmental HealthEtiologyExposure toFutureGoalsHealthHospitalizationIncidenceLanguageLibrariesLicensingMedical RecordsMethodsOutcomeOutputPopulationPredispositionProceduresPublishingPythonsReadinessResearchResearch PersonnelSoftware EngineeringSourceSource CodeStandardizationStatistical MethodsStructureSubgroupTestingTimeUnited States National Institutes of HealthVulnerable PopulationsWeatherWorkbasecardiovascular disorder riskcloud platformcohortcomputing resourcesdata analysis pipelinedata formatdesignenvironmental agentflexibilityimprovedinnovationinterestlarge datasetslifestyle factorsmortalitynovelopen sourceparent grantportabilityrepositoryresponsesocioeconomicstool
中文摘要
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英文摘要
Project Summary
The specific aims of the parent grant (R01 ES028033) are to develop new methods to assess the association
between long-term exposure to multiple environmental agents (air pollution and weather) on several health
outcomes (e.g. risk of cardiovascular disease, mortality); and identify vulnerable populations. As part of the
work conducted in Aim 1 of the parent grant, we developed two scientific R packages that address two
common challenges in environmental health: 1) how to estimate flexibly the exposure-response curve under a
statistical approach that allows users to assess causality from analyses of observational data1 (GPSmatching);
and 2) how to identify subgroups of the population that are more or less vulnerable to adverse health effects of
environmental exposure2 (denovo). While most environmental health research traditionally relies on existing
well-established statistical approaches, there is increasing interest in the community to adopt new cutting-edge
statistical tools, such as GPSmatching and denovo. GPSmatching and denovo are valuable R packages and
offer innovative functionalities to researchers, however, they are not well designed in terms of software
engineering best practices to be accessible to a broader scientific community and are not optimized for larger
datasets and efficient utilization on the cloud.
With this administrative proposal, we plan to establish a sustainable collaboration with professional software
engineers to redeploy our packages and disseminate them to a wider research community. More specifically,
our aims include; refactoring and improving the source code of both the GPSmatching and denovo R packages
in order to meet the best software engineering practices and community open source development, improving
cloud readiness by optimizing and parallelizing the R packages, and porting the packages to Python.
The refactoring of the GPSmatching and denovo software packages will enable a very large user base of
researchers to efficiently utilize the tools, add capabilities to the codebase, and offer improvements to the
algorithms. This proposal will make these tools widely accessible to the community and will establish workflows
and procedures that will allow more easily for the future dissemination of other innovative statistical methods.
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