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Estimating Importation Risk of COVID-19 in Hurricane Evacuations: A Prediction Framework Applied to Hurricane Laura in Texas

Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

In August 2020 as Texas was coming down from a summer COVID-19 surge, forecasts suggested that Hurricane Laura was tracking towards 6M residents along the East Texas coastline threatening to spread COVID-19 across the state. To assist local authorities facing the dual threat, we developed a framework that integrates evacuation dynamics and local pandemic conditions to quantify COVID-19 importations due to hurricane evacuations. For Hurricane Laura, we estimate that 499,500 [90% Credible Interval (CI): 347,500, 624,000] people evacuated the Texan counties, and that there were 2,900 [90% CI: 1,700, 5,800] importations of COVID-19 across the state. To demonstrate the transferability of the framework, we apply it to a scenario with characteristics matching those of Hurricane Rita, where a much feared direct hit towards the highly populated Houston/Galveston area was forecasted. For this scenario we estimate 1,054,500 evacuations [90% CI: 832,500, 1,162,000], and 6,850 COVID-19 importations [90% CI: 4,100, 13,670]. Overall, we present a flexible and transferable framework that captures spatial heterogeneity and incorporates geographic components for anticipating potential epidemiological risks resulting from evacuation movement due to hurricane events.

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  • DOI: 10.1007/978-3-030-98096-2_12
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Acknowledgements

We thank Dr. Kelly Gaither and Dr. Gordon Wells of the University of Texas at Austin, as well as Mario Chapa from the Texas Division of Emergency Management, whose insights helped us better design and inform our models.

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Correspondence to Michelle Audirac .

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Audirac, M., Tec, M., García-Tejeda, E., Fox, S. (2022). Estimating Importation Risk of COVID-19 in Hurricane Evacuations: A Prediction Framework Applied to Hurricane Laura in Texas. In: Tapia-McClung, R., Sánchez-Siordia, O., González-Zuccolotto, K., Carlos-Martínez, H. (eds) Advances in Geospatial Data Science. iGISc 2021. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-030-98096-2_12

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