Surveillance of the first cases of COVID-19 in Sergipe using a prospective spatiotemporal analysis: the spatial dispersion and its public health implications

Abstract INTRODUCTION: Coronavirus disease 2019 (COVID-19) has become a global public health emergency with lethality ranging from 1% to 5%. This study aimed to identify active high-risk transmission clusters of COVID-19 in Sergipe. METHODS: We performed a prospective space-time analysis using confirmed cases of COVID-19 during the first 7 weeks of the outbreak in Sergipe. RESULTS: The prospective space-time statistic detected "active" and emerging spatio-temporal clusters comprising six municipalities in the south-central region of the state. CONCLUSIONS: The Geographic Information System (GIS) associated with spatio-temporal scan statistics can provide timely support for surveillance and assist in decision-making.

引言：2019冠状病毒病（Coronavirus disease 2019，COVID-19）已演变为全球性公共卫生紧急事件，其致死率介于1%至5%之间。本研究旨在识别塞尔希培州（Sergipe）境内新冠病毒的活跃高风险传播簇。
研究方法：针对塞尔希培州疫情暴发最初7周内的确诊新冠病例，本研究开展了前瞻性时空分析。
研究结果：前瞻性时空统计方法检测到该州中南部地区6个市镇组成的“活跃”且处于发展中的时空聚集性传播簇。
研究结论：结合时空扫描统计量的地理信息系统（Geographic Information System，GIS）能够为疫情监测提供及时支撑，并辅助决策制定。