Abstract
There is an emerging body of literature focusing on the COVID-19 livelihoods and environmental impacts, as well as the effects of the pandemics on evidence generation. However, little attention has been paid to how COVID-19 has—and is likely to continue to—affect monitoring, evaluation, and learning (MEL) systems, specifically in the context of large sustainability science research-to-policy project consortia. Here, we provide a conceptual framework of MEL responsiveness to COVID-19 effects and discuss the specific pathways to successful MEL transition. Using the UKRI GCRF TRADE Hub as a case study, we provide some examples of possible adjustments within the new context.
Highlights
The novel coronavirus disease (COVID-19) is a pathogenic viral infection, which was first reported in Wuhan, China in December 2019 [1,2]
While the development and potential application of a COVID-19 vaccine might affect this process, it is unlikely that MEL practices would see a return to business as usual (BAU) anytime soon
This article provides an overview of the key MEL-related changes, challenges and opportunities resulting from the COVID-19 pandemic focusing on large research-to-policy projects
Summary
The novel coronavirus disease (COVID-19) is a pathogenic viral infection, which was first reported in Wuhan, China in December 2019 [1,2]. In this continuously context, it is imperative to thoroughly shift the tradicommentary we provide aevolving brief discussion regarding the COVID-19 induced changes tional project management and MEL approaches to accommodate innovative techniques “from old to new” MEL strategies and offer a set of potential solution pathways to mitiandagainst ways oflikely working that ensure that anticipated results unaffected. It is imperative to thoroughly shift the tradicommentary we provide aevolving brief discussion regarding the COVID-19 induced changes tional project management and MEL approaches to accommodate innovative techniques “from old to new” MEL strategies and offer a set of potential solution pathways to mitiandagainst ways oflikely working that ensure that anticipated results unaffected The Responsiveness conceptual model for MEL responsiveness to COVID-19 effects (Figure 1) is
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