ArticleSustainability science2021
Risk management for pandemics: a novel approach: "Hindsight is 20/20" English proverb.
Article in Sustainability science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The impacts of the current COVID-19 pandemic illustrate the global-level sensitivity to such threats. As understanding of major hazards is generally based on past experience and there is a lack of good historical precedents, approaches and models currently employed to assess risks and guide responses generally lack transparency and are often associated with huge, unspecified uncertainties. Fundamental challenges arise from the strongly coupled nature of the impacts of a pandemic (i.e. not only on health, but also on the entire socio-economic infrastructure) and their long-term evolution with recovery likely to take many years or, potentially, decades. Here, we outline experience gained in risk assessment within the nuclear industry, which has experience facing similar challenges (assessing long-term impacts in a strongly coupled technical system subject to socio-economic constraints), and assess options for knowledge transfer that may help manage future pandemics and other high-impact threats.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.