Multiscale dynamics of COVID-19 and model-based recommendations for 105 countries
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
We analyse the dynamics of COVID-19 using computational modelling at multiple scales. For large scale analysis, we propose a 2-scale lattice extension of the classical SIR-type compartmental model with spatial interactions called the Lattice-SIRQL model. Computational simulations show that global quantifiers are not completely representative of the actual dynamics of the disease especially when mitigation measures such as quarantine and lockdown are applied. Furthermore, using real data of confirmed COVID-19 cases, we calibrate the Lattice-SIRQL model for 105 countries. The calibrated model is used to make country specific recommendations for lockdown relaxation and lockdown continuation. Finally, using an agent-based model we analyse the influence of cluster level relaxation rate and lockdown duration on disease spreading.
Article activity feed
-
SciScore for 10.1101/2020.06.05.20123547: (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 10.1101/2020.06.05.20123547: (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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 8 and 7. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.
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.
-