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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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          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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          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.
          Article 0 comments Cited 2036 times – based on 0 reviews     Review now
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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.
            Article 0 comments Cited 176 times – based on 0 reviews     Review now
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              Prospective time periodic geographical disease surveillance using a scan statistic

              Martin Kulldorff (2001)
              Article 0 comments Cited 167 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Rev Soc Bras Med Trop
                Journal ID (iso-abbrev): Rev. Soc. Bras. Med. Trop
                Journal ID (publisher-id): rsbmt
                Title: Revista da Sociedade Brasileira de Medicina Tropical
                Publisher: Sociedade Brasileira de Medicina Tropical - SBMT
                ISSN (Print): 0037-8682
                ISSN (Electronic): 1678-9849
                Publication date (Electronic, pub): 01 June 2020
                Publication date (Electronic, collection): 2020
                Volume: 53
                Electronic Location Identifier: e20200287
                Affiliations
                [1 ]Universidade Federal de Sergipe, Programa de Pós-Graduação em Enfermagem, Aracaju, SE, Brasil.
                [2 ]Universidade Federal de Sergipe, Programa de Pós-Graduação em Biologia Parasitária, Aracaju, SE, Brasil.
                [3 ]Universidade Federal de Sergipe, Departamento de Medicina, Aracaju, SE, Brasil.
                [4 ]Secretaria Estadual de Saúde de Sergipe, Diretoria de Vigilância em Saúde, Aracaju, SE, Brasil.
                [5 ]Instituto Federal de Sergipe, São Cristóvão, SE, Brasil.
                [6 ]Universidade Federal de Sergipe, Programa de Pós-Graduação em Ciências da Saúde, Aracaju, SE, Brasil.
                Author notes
                Corresponding author: Allan Dantas dos Santos, PhD. e-mail: allanufs@ 123456hotmail.com

                Authors’ Contributions: LAA: Conception and design of the study, analysis and interpretation of data; DSG: Conception and design of the study, analysis and interpretation of data; MAOG: Acquisition of data, conception and design of the study, final approval of the submitted manuscript; MFSF: Acquisition of data; DCPT: Acquisition of data; CJNR: Analysis and interpretation of data, drafting the manuscript; JABA: Analysis and interpretation of data; KGCMA: Conception and design of the study, analysis and interpretation of data; final approval of the submitted manuscript; ADS: Conception and design of the study, drafting the manuscript, analysis and interpretation of data, final approval of the submitted manuscript.

                Conflict of Interests: The authors declare no conflicts of interest.

                Author information
                http://orcid.org/0000-0002-6529-1887
                Article
                Other ID: 00641
                DOI: 10.1590/0037-8682-0287-2020
                PMC ID: 7269533
                PubMed ID: 32491098
                SO-VID: 2dea580e-eb13-4634-a382-9c4000d3a064
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License

                History
                Date received : 07 May 2020
                Date accepted : 14 May 2020
                Page count
                Figures: 2, Tables: 1, Equations: 1, References: 15
                Categories
                Subject: Short Communication

                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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