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

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 case...

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Detalles Bibliográficos
Autores principales: Andrade, Lucas Almeida, Gomes, Dharliton Soares, Góes, Marco Aurélio de Oliveira, de Souza, Mércia Simone Feitosa, Teixeira, Daniela Cabral Pizzi, Ribeiro, Caíque Jordan Nunes, Alves, José Antônio Barreto, de Araújo, Karina Conceição Gomes Machado, dos Santos, Allan Dantas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sociedade Brasileira de Medicina Tropical - SBMT 2020
Materias:
Short Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269533/
https://www.ncbi.nlm.nih.gov/pubmed/32491098
http://dx.doi.org/10.1590/0037-8682-0287-2020
Descripción
Sumario: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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