The Texas flood registry: a flexible tool for environmental and public health practitioners and researchers

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dc.citation.firstpage823en_US
dc.citation.issueNumber5en_US
dc.citation.journalTitleJournal of Exposure Science & Environmental Epidemiologyen_US
dc.citation.lastpage831en_US
dc.citation.volumeNumber31en_US
dc.contributor.authorMiranda, Marie Lynnen_US
dc.contributor.authorCallender, Rashidaen_US
dc.contributor.authorCanales, Joally M.en_US
dc.contributor.authorCraft, Elenaen_US
dc.contributor.authorEnsor, Katherine B.en_US
dc.contributor.authorGrossman, Maxen_US
dc.contributor.authorHopkins, Lorenen_US
dc.contributor.authorJohnston, Jocelynen_US
dc.contributor.authorShah, Umairen_US
dc.contributor.authorTootoo, Joshuaen_US
dc.date.accessioned2021-09-30T17:34:48Zen_US
dc.date.available2021-09-30T17:34:48Zen_US
dc.date.issued2021en_US
dc.description.abstractBackground: Making landfall in Rockport, Texas in August 2017, Hurricane Harvey resulted in unprecedented flooding, displacing tens of thousands of people, and creating environmental hazards and exposures for many more. Objective: We describe a collaborative project to establish the Texas Flood Registry to track the health and housing impacts of major flooding events. Methods: Those who enroll in the registry answer retrospective questions regarding the impact of storms on their health and housing status. We recruit both those who did and did not flood during storm events to enable key comparisons. We leverage partnerships with multiple local health departments, community groups, and media outlets to recruit broadly. We performed a preliminary analysis using multivariable logistic regression and a binomial Bayesian conditional autoregressive (CAR) spatial model. Results: We find that those whose homes flooded, or who came into direct skin contact with flood water, are more likely to experience a series of self-reported health effects. Median household income is inversely related to adverse health effects, and spatial analysis provides important insights within the modeling approach. Significance: Global climate change is likely to increase the number and intensity of rainfall events, resulting in additional health burdens. Population-level data on the health and housing impacts of major flooding events is imperative in preparing for our planet’s future.en_US
dc.identifier.citationMiranda, Marie Lynn, Callender, Rashida, Canales, Joally M., et al.. "The Texas flood registry: a flexible tool for environmental and public health practitioners and researchers." <i>Journal of Exposure Science & Environmental Epidemiology,</i> 31, no. 5 (2021) Springer Nature: 823-831. https://doi.org/10.1038/s41370-021-00347-z.en_US
dc.identifier.digitals41370-021-00347-zen_US
dc.identifier.doihttps://doi.org/10.1038/s41370-021-00347-zen_US
dc.identifier.urihttps://hdl.handle.net/1911/111415en_US
dc.language.isoengen_US
dc.publisherSpringer Natureen_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleThe Texas flood registry: a flexible tool for environmental and public health practitioners and researchersen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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