Sars-Cov-2 in Argentina: Following Virus Spreading Using Granger Causality
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
There is a debate in Argentina on how COVID-19 outbreak in one district ends up infecting its neighbor districts. This contribution aims to use tools of time series analysis for understanding processes of contagious through regions. I use VAR and Granger causality for testing neighbor spreading via sequential rate of contagion. Results show that in the case of Argentina, contagion began in the capital city of Buenos Aires and then spread to its hinterland via specific districts. Once interior districts were infected a positive feedback dynamics emerge creating regions of high reproducibility of the virus where interventions may be focus in the very near future. This specific use of time series analysis may provide a tool for tracing infectiousness along regions that may help to anticipate infection and then for intervening for reducing the problems derived by the disease.
Article activity feed
-
SciScore for 10.1101/2020.10.06.20207993: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. 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 …
SciScore for 10.1101/2020.10.06.20207993: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. 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.
-