3 research outputs found

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

    Get PDF
    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

    Chapter 10 The Adequacy of Artificial Intelligence Tools to Combat Misinformation

    No full text
    We discuss a computationally meaningful process for evaluating misinformation detection tools in the context of immigration in Austria, admitting for the wide variety of qualitative and quantitative data involved. The evaluation machinery is based on a library of tools to support the process in both the elicitation and evaluation phases, including automatized preference elicitation procedures, development of result robustness measures as well as algorithms for co-evaluating quantitative and qualitative data in various formats. The focus of our work is on the Austrian limited profit housing sector, which makes up 24% of the total housing stock and more than 30% of the total of new construction, with a high share of migrants as tenants. We describe the results from workshops analysing the existing misinformation on migration issues in Austria, where we also introduced a co-creation phase. To better understand the stakeholder ecosystem and the lifecycle of misinformation towards social conflicts, we applied a software for integrated multi-stakeholder-multi-attribute problems under risk subject to incomplete or imperfect information, based on the evaluation machinery. Perceived counter-measures of importance turned out to be institutional and regulatory measures in combination with the creation of info-points, measures to raise awareness and stimulate critical thinking, production of tools to deal with misinformation, provision of reliable sources of information, and creation of a culture of thinking
    corecore