About: Objective: This study investigates the regional differences in the occurrence of COVID-19 in Brazil and its relationship with climatic and demographic factors, for this, using data about identified cases of COVID-19 on Brazil from February 26 to April 04, 2020. Methods: A model using the Polynomial Regression with cubic adjustments of the number of days of contagion, demographic density, city population and climatic factors was designed to explain the spread of COVID-19 in Brazil. Main results: It was evidenced that temperature variation maintains a relationship with the reduction in the number of cases of COVID-19, but on a very small scale. With a simulation of 30 days of contagion, a variation of -0.9% was found for each increase of 1 C. Conclusion: Temperature, despite being an intervening factor in the variation in the number of COVID-19 cases, has a reduced magnitude effect. Cities with higher temperatures do not necessarily it is more protected from the SARS-CoV-2 than those with lower temperatures, however, strong statistical significance was found, this relationship deserves to be investigated in other tests with longer time series, wide and with especially non-linear data adjustments.   Goto Sponge  NotDistinct  Permalink

An Entity of Type : fabio:Abstract, within Data Space : covidontheweb.inria.fr associated with source document(s)

AttributesValues
type
value
  • Objective: This study investigates the regional differences in the occurrence of COVID-19 in Brazil and its relationship with climatic and demographic factors, for this, using data about identified cases of COVID-19 on Brazil from February 26 to April 04, 2020. Methods: A model using the Polynomial Regression with cubic adjustments of the number of days of contagion, demographic density, city population and climatic factors was designed to explain the spread of COVID-19 in Brazil. Main results: It was evidenced that temperature variation maintains a relationship with the reduction in the number of cases of COVID-19, but on a very small scale. With a simulation of 30 days of contagion, a variation of -0.9% was found for each increase of 1 C. Conclusion: Temperature, despite being an intervening factor in the variation in the number of COVID-19 cases, has a reduced magnitude effect. Cities with higher temperatures do not necessarily it is more protected from the SARS-CoV-2 than those with lower temperatures, however, strong statistical significance was found, this relationship deserves to be investigated in other tests with longer time series, wide and with especially non-linear data adjustments.
Subject
  • Brazil
  • Zoonoses
  • Viral respiratory tract infections
  • COVID-19
  • BRICS nations
  • Member states of Mercosur
  • Occupational safety and health
part of
is abstract of
is hasSource of
Faceted Search & Find service v1.13.91 as of Mar 24 2020


Alternative Linked Data Documents: Sponger | ODE     Content Formats:       RDF       ODATA       Microdata      About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data]
OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software