利用前瞻性时空分析监测塞尔希培州的首批 COVID-19 病例：空间分布及其公共卫生意义。
Surveillance of the first cases of COVID-19 in Sergipe using a prospective spatiotemporal analysis: the spatial dispersion and its public health implications.
机构信息
Programa de Pós-Graduação em Enfermagem, Universidade Federal de Sergipe, Aracaju, SE, Brasil.
Programa de Pós-Graduação em Biologia Parasitária, Universidade Federal de Sergipe, Aracaju, SE, Brasil.
出版信息
Rev Soc Bras Med Trop. 2020;53:e20200287. doi: 10.1590/0037-8682-0287-2020. Epub 2020 Jun 1.
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.
简介
2019 年冠状病毒病（COVID-19）已成为全球公共卫生紧急事件，其致死率在 1%至 5%之间。本研究旨在确定塞尔希培州 COVID-19 的活跃高危传播集群。
方法
我们对塞尔希培州疫情爆发的前 7 周内确诊的 COVID-19 病例进行了前瞻性时空分析。
结果
前瞻性时空统计检测到由该州中南部六个城市组成的“活跃”和新兴时空集群。
结论
地理信息系统（GIS）与时空扫描统计相结合，可以为监测提供及时支持，并有助于决策。
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