A Mathematical Model Approach for Prevention and Intervention Measures of the COVID-19 Pandemic in Uganda
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Abstract
The human{infecting corona virus disease (COVID-19) caused by the novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) was declared a global pandemic on March11th, 2020. Different countries adopted different interventions at different stages of the outbreak, with social distancing being the first option while lock down the preferred option for attening the curve at the peak of the pandemic. Lock down aimed at adherence to social distancing, preserve the health system and improve survival. We propose a Susceptible-Exposed- Infected-Expected recoveries (SEIR) mathematical model for the prevention and control of Covid-19 in Uganda. We analyze the model using available data to find the infection-free, endemic/infection steady states and the basic reproduction number. We computed the reproductive number and it worked out as R0 = 0:468. We note that R0 is less than unity, thus forecast that several strategies in combination (including travel restrictions, mass media awareness, community buy-in and medical health interventions) will eliminate the disease from the population. However, our model predicts a recurrence of the disease after one year and two months (430 days) thus the population has to be mindful and continuously practice the prevention and control measures. In addition, a sensitivity analysis done showed that the transmission rate and the rate at which persons acquire the virus, have a positive in uence on the basic reproduction number. On other hand the rate of evacuation by a rescue ambulance greatly reduces the reproduction number. The results have potential to inform the impact and effect of early strict interventions including lock down in resource limited settings and social distancing.
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SciScore for 10.1101/2020.05.08.20095067: (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: 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…
SciScore for 10.1101/2020.05.08.20095067: (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: 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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