Evidence-Based Methods for the Development of Computationally Supported Epidemic-Combating Policies

Danielson, M., Ekenberg, L. ORCID: https://orcid.org/0000-0002-0665-1889, Komendantova, N. ORCID: https://orcid.org/0000-0003-2568-6179, & Mihai, A. (2022). Evidence-Based Methods for the Development of Computationally Supported Epidemic-Combating Policies. In: New Trends in Intelligent Software Methodologies, Tools and Techniques. pp. 363-373 IOS Press. 10.3233/FAIA220266.

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Abstract

In this article, we suggest a group decision method within an integrated computational framework for decision policy. Based on a co-creation workflow, epidemiological estimates, and socioeconomic factors, decisions are considered in a multi-stakeholder, multi-criteria context to elicit attitudes, perceptions, and preferences of relevant stakeholder groups. The complete framework has been applied in Botswana, Romania, and Jordan to assess mitigation actions related to the Covid-19 pandemic in order to mobilize better response strategies for other relevant future scenarios, and potentially more serious pandemics and other hazardous events. The framework was recommended as best practice in the EU under the European Open Science Cloud EOSC, Covid-19 Fast Track Funding.

Item Type:	Book Section
Research Programs:	Advancing Systems Analysis (ASA) Advancing Systems Analysis (ASA) > Cooperation and Transformative Governance (CAT)
Depositing User:	Luke Kirwan
Date Deposited:	24 Oct 2022 06:29
Last Modified:	29 Apr 2024 12:38
URI:	https://pure.iiasa.ac.at/18320

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