Risk Analysis and Prediction for COVID19 Demographics in Low Resource Settings using a Python Desktop App and Excel Models
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Abstract
While the novel covid19 disease caused by sar-cov-2 corona virus has proved a serious threat to mankind it being a pandemic, the rate at which technology in low resource income countries like Uganda has been used to predict the spread and impact of the disease in their economies has not been strongly employed. This paper presents a an excel model and desktop application software developed using open source python programming tools for carrying out risk analysis and prediction of demographics for covid19 disease. Prediction results for both models clearly stated using epidemiological curve, these results can vary based on the force of infection which varies based on government measures and actions. With a certain degree of certainty of the potential impact of the disease on low resource countries, it will foster proper planning and strategical methods to properly manage the pandemic.
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SciScore for 10.1101/2020.04.13.20063453: (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 10.1101/2020.04.13.20063453: (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.
- Thank you for including a protocol registration statement.
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