Four-week forecasts of COVID-19 epidemic trajectories in South Africa, Chile, Peru and Brazil: a model evaluation
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Introduction
From the beginning of the COVID-19 pandemic, epidemiological models have been used in a number of ways to aid governments and organizations in efficient planning of resources and decision making. These models have elucidated important epidemiological transmission parameters, in addition to making short-term projections.
Methods
We constructed a compartmental mathematical model for the transmission, detection and prevention of SARS-CoV-2 infections for regions where Anglo American has mining operations. We fitted the model to publicly available data and used it to make short-term projections. Finally, we evaluated how the model performed by comparing short-term projections to actual confirmed cases, retrospectively.
Findings
The average forecast errors for four-week-ahead projections ranged between 1% and 8% in all the countries and regions considered in this study. All but one region had more than 75% of the true values falling within the range of four-week-ahead projections. The quality of the projections improved with time as expected due to increased historical data.
Conclusion
Our model produced four-week forecasts with a sufficiently high level of accuracy to guide operational and strategic planning for business continuity and COVID-19 responses in Anglo American mining sites.
Article activity feed
-
SciScore for 10.1101/2021.09.06.21263151: (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: Thank you for sharing your code and data.
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 …
SciScore for 10.1101/2021.09.06.21263151: (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: Thank you for sharing your code and data.
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.
Results from scite Reference Check: We found no unreliable references.
-