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Age structured mixture model for early COVID-19 spread: a Zimbabwean risk factor analysis

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dc.contributor.author Zidana, Chipo
dc.contributor.author Gudoshava, Masilin
dc.contributor.author Showa, Sarudzai Portia
dc.date.accessioned 2021-08-29T11:23:52Z
dc.date.available 2021-08-29T11:23:52Z
dc.date.issued 2020-07-13
dc.identifier.citation Zidana, C., Gudoshava, M. and Showa, S. P. (2020). Age structured mixture model for early COVID-19 spread: a Zimbabwean risk factor analysis. Journal of Contemporary Studies in Epidemiology and Public Health, 1(1), ep20003. https://doi.org/10.30935/jconseph/8442 en_US
dc.identifier.issn 2634-8543
dc.identifier.uri http://repository.biust.ac.bw/handle/123456789/325
dc.description.abstract Unique severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2/COVID-19) prevention measures to distinct age, geographical and community groupings can only be effectively and efficiently implemented with a clear understanding on dynamics of the disease. Dynamics include disease spread, different risk factors and their level of influence and individual attributes that aid the spread. The paper aims at determining the major COVID-19 spread risk factors in Zimbabwe by identifying individual, age and community groupings, their risk levels given the complex heterogeneous population. COVID-19 data for 37 individuals as provided by the Ministry of Health and Child Care (MoHCC) for the period from 20 March - 14 May 2020 is used. Generalised Mixture Models were implemented to achieve the objectives. Results show that gender, age, mode of infection and history of travel were the main predictors of COVID-19 spread in Zimbabwe. However, their effects were distributed differently across two clusters. Children (0-14) years, females and those with imported infections were among high level risk spread groups. Whilst low risk groups consist non travelers, males and those infected by local transmission. We thus recommend that the Zimbabwean government need to prioritise children, females, and non-travelers when implementing prevention measures. en_US
dc.language.iso en en_US
dc.publisher Modestum Publishing LTD en_US
dc.subject COVID-19 spread en_US
dc.subject Age structured en_US
dc.subject Spread risk factors en_US
dc.subject Finite mixture models en_US
dc.subject COVID-19 prevention en_US
dc.title Age structured mixture model for early COVID-19 spread: a Zimbabwean risk factor analysis en_US
dc.description.level phd en_US
dc.description.accessibility unrestricted en_US
dc.description.department mss en_US


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