Author: Andrade, Lucas Almeida; Gomes, Dharliton Soares; Góes, Marco Aurélio de Oliveira; de Souza, Mércia Simone Feitosa; Teixeira, Daniela Cabral Pizzi; Ribeiro, CaÃque Jordan Nunes; Alves, José Antônio Barreto; de Araújo, Karina Conceição Gomes Machado; dos Santos, Allan Dantas
Title: Surveillance of the first cases of COVID-19 in Sergipe using a prospective spatiotemporal analysis: the spatial dispersion and its public health implications Cord-id: 5ju39ptd Document date: 2020_6_1
ID: 5ju39ptd
Snippet: 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 i
Document: 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.
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