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

Lucas Almeida Andrade, Dharliton Soares Gomes, Marco Aurélio de Oliveira Góes, Mércia Simone Feitosa de Souza, Daniela Cabral Pizzi Teixeira, Caíque Jordan Nunes Ribeiro, José Antônio Barreto Alves, Karina Conceição Gomes Machado de Araújo, Allan Dantas dos Santos

2020Revista da Sociedade Brasileira de Medicina Tropical42 citationsDOI Open Access PDF

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.

Topics & Concepts

Scan statisticCoronavirus disease 2019 (COVID-19)OutbreakStatisticPublic healthSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Geography2019-20 coronavirus outbreakLocation dataProspective cohort studyTransmission (telecommunications)Mass gatheringCartographyEnvironmental healthMedicineDiseaseStatisticsComputer scienceVirologyInfectious disease (medical specialty)PathologyReal-time computingTelecommunicationsMathematicsCOVID-19 epidemiological studiesData-Driven Disease SurveillanceCOVID-19 impact on air quality