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Modelling the Impact and Public Health Response to COVID-19 in Uganda

29 Pages Posted: 28 Aug 2020

See all articles by Ronald Galiwango

Ronald Galiwango

Uganda Christian University - Centre for Computational Biology

John Kitayimbwa

Centre for Computational Biology, Uganda Christian University

Agnes N. Kiragga

Infectious Diseases Institute, College of Health Sciences, Makerere University

Katherine E. Atkins

College of Medicine and Veterinary Medicine, University of Edinburgh

Andrew Leigh Brown

Institute of Evolutionary Biology, University of Edinburgh

Anthony K. Mbonye

School of Public Health, College of Health Sciences, Makerere University

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Abstract

Background: As of June 18, 2020, Uganda had registered 741 COVID-19 cases, and several intervention measures have been implemented to control the spread of the SARS-CoV2. With increasing risk of community transmission, it is important to forecast the extent on the COVID-19 epidemic in Uganda. This study aimed to design a predictive model to provide reliable estimates for COVID-19 in Uganda.

Methods: A stochastic model of a modified SEAIR (Susceptible, Exposed, Infected Asymptomatic, Infected Symptomatic and Removed) type, which made assumptions on the local SARS-CoV2 transmission, was used to forecast the impact of COVID-19 in relation to the varying levels of compliance to mitigation measures.

Results:  Our results predict between 2,000 to 4,000 cases within 100 days from lifting the lockdown if no or weak interventions are in place. However, if social distancing was implemented at 40% effectiveness, to prevent interaction between susceptible and infected populations with no use of face-masks, we would expect 200 to 400 cases. The number of infections decreases with increase in the level of effectiveness of social distancing measures and the curve flattens at ≥60% level of social distancing. Wearing face-masks at ≥40% consistency and social distancing at 50% reduces the number of infections and flattens the curve.

Interpretation: The prompt public health response in Uganda has so far limited COVID-19 to imported cases, comprising mainly of truck drivers. Although lifting the lockdown measures is feasible, social distancing strategies, as the most effective measure, should be maintained at high levels and supplemented with wearing face-masks.

Funding Statement: None to declare

Declaration of Interests: All authors have no reported conflicts of interest.

Ethics Approval Statement: Not required

Keywords: SARS-CoV2: COVID-19: Modeling: Africa: Uganda

Suggested Citation

Galiwango, Ronald and Kitayimbwa, John and Kiragga, Agnes N. and Atkins, Katherine E. and Brown, Andrew Leigh and Mbonye, Anthony K., Modelling the Impact and Public Health Response to COVID-19 in Uganda (6/18/2020). Available at SSRN: https://ssrn.com/abstract=3633199 or http://dx.doi.org/10.2139/ssrn.3633199

Ronald Galiwango (Contact Author)

Uganda Christian University - Centre for Computational Biology ( email )

Uganda

John Kitayimbwa

Centre for Computational Biology, Uganda Christian University

Agnes N. Kiragga

Infectious Diseases Institute, College of Health Sciences, Makerere University

Katherine E. Atkins

College of Medicine and Veterinary Medicine, University of Edinburgh

Andrew Leigh Brown

Institute of Evolutionary Biology, University of Edinburgh

Anthony K. Mbonye

School of Public Health, College of Health Sciences, Makerere University