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

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Author(s): 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

Publication date (Print and electronic): 2020

Journal: Revista da Sociedade Brasileira de Medicina Tropical

Publisher: Sociedade Brasileira de Medicina Tropical - SBMT

Keywords: COVID-19, Spatial analysis, Space-time clusters, Pandemic, Disease surveillance

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Abstract

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.

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Most cited references 9

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The Socio-Economic Implications of the Coronavirus and COVID-19 Pandemic: A Review

Maria R.C. Nicola, Zaid Alsafi, Catrin Sohrabi … (2020)

The COVID-19 pandemic has resulted in over 1.4 million confirmed cases and over 83,000 deaths globally. It has also sparked fears of an impending economic crisis and recession. Social distancing, self-isolation and travel restrictions forced a decrease in the workforce across all economic sectors and caused many jobs to be lost. Schools have closed down, and the need of commodities and manufactured products has decreased. In contrast, the need for medical supplies has significantly increased. The food sector has also seen a great demand due to panic-buying and stockpiling of food products. In response to this global outbreak, we summarise the socio-economic effects of COVID-19 on individual aspects of the world economy.

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COVID-19: Challenges to GIS with Big Data

Chenghu Zhou, Fenzhen Su, Tao Pei … (2020)

Highlights • GIS with big data provides geospatial information to fight COVID-19. • Big data showed power on epidemic transmission analysis and prevention decision making support. • Challenges still continue in data aggregation, knowledge discovery, and dynamic expression.

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Prospective time periodic geographical disease surveillance using a scan statistic

Martin Kulldorff (2001)

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Author and article information

Journal

Journal ID (publisher-id): rsbmt

Title: Revista da Sociedade Brasileira de Medicina Tropical

Abbreviated Title: Rev. Soc. Bras. Med. Trop.

Publisher: Sociedade Brasileira de Medicina Tropical - SBMT (Uberaba, MG, Brazil )

ISSN (Print): 0037-8682

ISSN (Electronic): 1678-9849

Publication date (Print and electronic): 2020

Volume: 53

Electronic Location Identifier: e20200287

Affiliations

[2] Aracaju Sergipe orgnameUniversidade Federal de Sergipe orgdiv1Programa de Pós-Graduação em Biologia Parasitária Brazil

[4] Aracaju SE orgnameSecretaria Estadual de Saúde de Sergipe orgdiv1Diretoria de Vigilância em Saúde Brasil

[6] Aracaju Sergipe orgnameUniversidade Federal de Sergipe orgdiv1Programa de Pós-Graduação em Ciências da Saúde Brazil

[5] São Cristóvão SE orgnameInstituto Federal de Sergipe Brasil

[3] Aracaju Sergipe orgnameUniversidade Federal de Sergipe orgdiv1Departamento de Medicina Brazil

[1] Aracaju Sergipe orgnameUniversidade Federal de Sergipe orgdiv1Programa de Pós-Graduação em Enfermagem Brazil

Article

Publisher ID: S0037-86822020000100641 Publisher ID: S0037-8682(20)05300000641

DOI: 10.1590/0037-8682-0287-2020

SO-VID: 2dea580e-eb13-4634-a382-9c4000d3a064

License:

This work is licensed under a Creative Commons Attribution 4.0 International License.

History

Date accepted : 14 May 2020

Date received : 07 May 2020

Page count

Figures: 0, Tables: 0, Equations: 0, References: 15, Pages: 0

Product

SciELO Brazil

Self URI: Full text available only in PDF format (EN)

Categories

Subject: Short Communications

Keywords: COVID-19,Spatial analysis,Space-time clusters,Pandemic,Disease surveillance

Data availability:

Keywords: COVID-19, Spatial analysis, Space-time clusters, Pandemic, Disease surveillance

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