飓风疏散中的COVID-19输入风险估计：应用于德克萨斯州飓风劳拉的预测框架
Estimating Importation Risk of Covid-19 in Hurricane Evacuations: A Prediction Framework Applied to Hurricane Laura in Texas
摘要：
于二零二零年八月，当德克萨斯州从夏季COVID-19大幅飙升中走出来时，预测显示飓风劳拉正沿着德克萨斯州东部海岸线向600万居民逼近，威胁将COVID-19传播到全州并导致疫情复发。为协助地方当局应对双重威胁，我们将沿海居民的调查预期和观察到的飓风疏散率整合到一个统计框架中，并结合当地的流行情况，预测COVID-19在飓风中的传播情况。对于飓风劳拉，我们估计有499，500 [90%可信区间（CI）：347，500，624，000]人撤离德克萨斯州各县，没有一个县的飓风撤离人数超过2.5%，全州有2，900 [90% CI：1，700，5，800]人输出新冠肺炎。一般而言，接收估计数集中在人口密度较高的地区。尽管如此，预计在小地区的进口风险更高，在我们的案例研究中，每10，000名居民的最大进口数量为10。总的来说，我们提出了一个灵活的和可转移的框架，捕捉空间异质性，并结合地理成分预测人口流动的自然灾害。随着飓风的频率和强度不断增加，我们的框架可以部署在应对预期的飓风路径，以指导备灾和规划。
英文摘要：
In August 2020, as Texas was coming down from a large 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 and cause pandemic resurgences. To assist local authorities facing the dual-threat, we integrated survey expectations of coastal residents and observed hurricane evacuation rates in a statistical framework that combined with local pandemic conditions predicts how COVID-19 would spread in response to a hurricane. For Hurricane Laura, we estimate that 499,500 [90% Credible Interval (CI): 347,500, 624,000] people evacuated the Texan counties, that no single county accumulated more than 2.5% of hurricane evacuees, and that there were 2,900 [90% CI: 1,700, 5,800] exportations of Covid-19 across the state. In general, reception estimates were concentrated in regions with higher population densities. Nonetheless, higher importation risk is expected in small Districts, with a maximum number of importations of 10 per 10,000 residents in our case study. Overall, we present a flexible and transferable framework that captures spatial heterogeneity and incorporates geographic components for predicting population movement in the wake of a natural disaster. As hurricanes continue to increase in both frequency and strength, our framework can be deployed in response to anticipated hurricane paths to guide disaster preparedness and planning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
