Assessing the potential impact of COVID-19 in Brazil: Mobility, Morbidity and the burden on the Health Care System
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Background
Brazil detected community transmission of COVID-19 on March 13, 2020. In this study we identify which areas in the country are most vulnerable for COVID-19, both in terms of the risk of arrival of COVID-19 cases and the risk of sustained transmission. The micro-regions with higher social vulnerability are also identified.
Methods
Probabilistic models were used to calculate the probability of COVID-19 spread from São Paulo and Rio de Janeiro, according to previous data available on human mobility in Brazil. We also perform a multivariate cluster analysis of socio-economic indices to identify areas with similar social vulnerability.
Results
The results consist of a series of maps of effective distance, outbreak probability, hospital capacity and social vulnerability. They show areas in the North and Northeast with high risk of COVID-19 outbreak that are also highly vulnerable.
Interpretation
The maps produced are useful for authorities in their efforts to prioritize actions such as resource allocation to mitigate the effects of the pandemic and may help other countries to use a similar approach to predict the virus route in their countries as well.
Funding
No funding
Article activity feed
-
SciScore for 10.1101/2020.03.19.20039131: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank…
SciScore for 10.1101/2020.03.19.20039131: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
-
-