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Addressing the COVID-19 transmission in inner Brazil by a mathematical model.
Almeida, G B; Vilches, T N; Ferreira, C P; Fortaleza, C M C B.
  • Almeida GB; Medical School of Botucatu, São Paulo State University, Botucatu, 18618-687, Brazil. gb.almeida@unesp.br.
  • Vilches TN; Institute of Mathematics, Statistics, and Scientific Computing, University of Campinas, Campinas, 13083-859, Brazil.
  • Ferreira CP; Institute of Biosciences, São Paulo State University, Botucatu, 18618-689, Brazil.
  • Fortaleza CMCB; Medical School of Botucatu, São Paulo State University, Botucatu, 18618-687, Brazil.
Sci Rep ; 11(1): 10760, 2021 05 24.
Article in English | MEDLINE | ID: covidwho-1242044
ABSTRACT
In 2020, the world experienced its very first pandemic of the globalized era. A novel coronavirus, SARS-CoV-2, is the causative agent of severe pneumonia and has rapidly spread through many nations, crashing health systems and leading a large number of people to death. In Brazil, the emergence of local epidemics in major metropolitan areas has always been a concern. In a vast and heterogeneous country, with regional disparities and climate diversity, several factors can modulate the dynamics of COVID-19. What should be the scenario for inner Brazil, and what can we do to control infection transmission in each of these locations? Here, a mathematical model is proposed to simulate disease transmission among individuals in several scenarios, differing by abiotic factors, social-economic factors, and effectiveness of mitigation strategies. The disease control relies on keeping all individuals' social distancing and detecting, followed by isolating, infected ones. The model reinforces social distancing as the most efficient method to control disease transmission. Moreover, it also shows that improving the detection and isolation of infected individuals can loosen this mitigation strategy. Finally, the effectiveness of control may be different across the country, and understanding it can help set up public health strategies.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Models, Theoretical Type of study: Observational study Limits: Humans Country/Region as subject: South America / Brazil Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-90118-5

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Models, Theoretical Type of study: Observational study Limits: Humans Country/Region as subject: South America / Brazil Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-90118-5