Co-Modelling for Relief and Recovery from the Covid-19 Crisis in Zimbabwe

Ramos Mabugu, Hélène Maisonnave (), Martin Henseler (), Margaret Chitiga-Mabugu and Albert Makochekanwa
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Hélène Maisonnave: ULH - Université Le Havre Normandie - NU - Normandie Université
Martin Henseler: ULH - Université Le Havre Normandie - NU - Normandie Université
Margaret Chitiga-Mabugu: University of Pretoria [South Africa]
Albert Makochekanwa: UZ - University of Zimbabwe

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Abstract: This article presents lessons on transcendence, from research on the socioeconomic impacts of the Covid-19 pandemic to policy, using experiences from Zimbabwe. The case study parallels literature on knowledge translation that suggests that the challenge of evidence-informed policy is more a problem of evidence production than evidence translation. The positioning, influence, and leverage of the research team was predominantly built on a platform of personal relationship legacies, academic legitimacy, and networks. The data and model co-produced with state actors could influence policy decisions and behaviours because they were designed with and for policymakers to assist with policy decisions. The results had direct implications for Covid-19 response measures, informing policymakers on what the impact on different groups is likely to be and indicating what policy measures could do to address impacts. Knowledge co‑production also proved pivotal in reducing some of the concerns around the limitations of risk‑based modelling in a crisis.

Date: 2023-10-23
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Published in IDS Bulletin, 2023, 54 (2), ⟨10.19088/1968-2023.131⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05361701

DOI: 10.19088/1968-2023.131

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