Mathematical Modelling Projections Versus the Actual Course of the COVID-19 Epidemic following the Nationwide Lockdown in Kyrgyzstan
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SciScore for 10.1101/2020.12.10.20247247: (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: We detected the following sentences addressing limitations in the study:However, there are some limitations of this model, associated with a number of uncertainties and assumptions about this novel disease and the effects of related interventions, that must be taken into account. One such …
SciScore for 10.1101/2020.12.10.20247247: (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: We detected the following sentences addressing limitations in the study:However, there are some limitations of this model, associated with a number of uncertainties and assumptions about this novel disease and the effects of related interventions, that must be taken into account. One such limitation is that the model reflected the medium-term projection of the epidemic, where seasonality was not considered due to the limited evidence for this at the beginning of the year. Moreover, contrary to the model’s predictions, Kyrgyzstan experienced a second wave of the epidemic during October and November, as a result of nationwide protests and mass gatherings against the results of parliamentary elections. There were also some methodological limitations. The model was visually fitted, as part of the simulation process, through a web-based application. The particle filtering method has only recently became available, which we plan to apply for further simulations of the epidemic in Kyrgyzstan. Accordingly, it remains unclear whether the visual fitting was appropriate for forecasting the epidemic. However, it is important to note that the primary function of the model was to support real-time decision-making, which urgently required evidence and tools to address the constantly changing situation with regards to the epidemic. Thus, in this use case, the model was fit for purpose, from a qualitative point of view, with its predictions matching the observed outcomes of the decision to release the lockdown in Kyrgyzstan.
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.
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