A Framework for COVID-19 Pandemic Intervention Modelling and Analysis for Policy Formation Support in Botswana

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Love Ekenberg
Tobias Fasth
Vasilis Koulolias
Aron Larsson
Aron Larsson
Mats Danielson
Nadejda Komendantova
Adriana Mihai


The purpose of this research was to develop a methodological framework that could be applied for policy formation in situations having a high level of uncertainty and heterogeneity of existing opinions among involved stakeholders about risk mitigation and management such as COVID-19 pandemic risk. In this paper, we present such a framework and its application for policy decision-making in Botswana for mitigating the COVID-19 pandemic. The purpose of the proposed model is twofold: firstly, to supply decision-makers with reliable and usable epidemiologic modelling since measures to contain the spread of the COVID-19 virus were initially to a large extent based on various epidemiologic risk assessments. Secondly, given that some sets of measures adopted in other parts of the world were progressively imposing high or even very high social and economic costs on the countries which adopted these measures, we provided a multi-criteria decision support model which could be used in order to weigh different policy approaches to combat the virus spread taking into consideration local impact assessments across a variety of societal areas. We describe how the formulation of a national COVID-19 strategy and policy in Botswana in 2020 was aided by using ICT decision support models as a vital information source. Then we present the virus spread simulation model and its results which are connected to a multi-criteria decision support model. Finally, we discuss how the framework can be further developed for the needs of Botswana to optimise hazard management options in the case of handling COVID-19 and other pandemic scenarios. The significant research contribution is on advancing the research frontier regarding a methodology of including the heterogeneity of views and identification of compromise solutions in policy-relevant discourses under a high degree of uncertainty.

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