The Ugandan Severe Acute Respiratory Syndrome -Coronavirus 2 (SARS-CoV-2) Model: A Data Driven Approach to Estimate Risk

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dc.contributor.authorNannyonga, Betty
dc.contributor.authorKyobe Bosa, Henry
dc.contributor.authorWoldermariam, Yonas T.
dc.contributor.authorKaleebu, Pontiano
dc.contributor.authorSsenkusu, John M.
dc.contributor.authorLutalo, Tom
dc.contributor.authorKirungi, Willford
dc.contributor.authorMakumbi, Fredrick E.
dc.contributor.authorSsembatya, Vincent A.
dc.contributor.authorMwebesa, Henry G.
dc.contributor.authorAtwine, Diana
dc.contributor.authorAceng, Jane R.
dc.contributor.authorWanyenze, Rhoda K.
dc.date.accessioned2021-12-14T12:49:42Z
dc.date.available2021-12-14T12:49:42Z
dc.date.issued2020
dc.description.abstractThe first case of Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) was identified on March 21, 2020, in Uganda. The number of cases increased to 8,287 by September 30, 2020. By May throughout June, most of the cases were predominantly imported cases of truck drivers from neighbouring countries. Uganda responded with various restrictions and interventions including lockdown, physical distancing, hand hygiene, and use of face masks in public, to control the growth rate of the outbreak. By end of September 2020, Uganda had transitioned into community transmissions and most of the reported cases were locals contacts and alerts. This study assessed risks associated with SARS-CoV-2 in Uganda, and presents estimates of the reproduction ratio in real time. An optimal control analysis was performed to determine how long the current mitigation measures such as controlling the exposure in communities, rapid detection, confirmation and contact tracing, partial lockdown of the vulnerable groups and control at the porous boarders, could be implemented and at what cost. Methods: The daily confirmed cases of SARS-CoV-2 in Uganda were extracted from publicly available sources. Using the data, relative risks for age, gender, and geographical location were determined. Four approaches were used to forecast SARS-CoV-2 in Uganda namely linear exponential, nonlinear exponential, logistic and a deterministic model.en_US
dc.identifier.citationNannyonga, B., Bosa, H. K., Woldermariam, Y. T., Kaleebu, P., Ssenkusu, J. M., Lutalo, T., ... & Wanyenze, R. K. (2021). The Ugandan Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) Model: A Data Driven Approach to Estimate Risk. medRxiv, 2020-12.doi: https://doi.org/10.1101/2020.12.28.20248922en_US
dc.identifier.uridoi: https://doi.org/10.1101/2020.12.28.20248922
dc.identifier.urihttps://nru.uncst.go.ug/xmlui/handle/123456789/502
dc.language.isoenen_US
dc.publishermedRxiven_US
dc.subjectCoronavirus 2en_US
dc.subjectAcute Respiratory Syndromen_US
dc.subjectRisken_US
dc.titleThe Ugandan Severe Acute Respiratory Syndrome -Coronavirus 2 (SARS-CoV-2) Model: A Data Driven Approach to Estimate Risken_US
dc.typeArticleen_US
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