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AuthorGrieve, Richard
AuthorYang, Youqi
AuthorAbbott, Sam
AuthorBabu, Giridhara R.
AuthorBhattacharyya, Malay
AuthorDean, Natalie
AuthorEvans, Stephen
AuthorJewell, Nicholas
AuthorLangan, Sinéad M.
AuthorLee, Woojoo
AuthorMolenberghs, Geert
AuthorSmeeth, Liam
AuthorWilliamson, Elizabeth
AuthorMukherjee, Bhramar
Available date2024-06-24T07:18:23Z
Publication Date2023-11-01
Publication NamePLOS Global Public Health
Identifierhttp://dx.doi.org/10.1371/journal.pgph.0002601
CitationGrieve R, Yang Y, Abbott S, Babu GR, Bhattacharyya M, Dean N, et al. (2023) The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic. PLOS Glob Public Health 3(11): e0002601. https://doi.org/10.1371/journal.pgph.0002601
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85195095387&origin=inward
URIhttp://hdl.handle.net/10576/56186
AbstractThe COVID-19 pandemic has brought about valuable insights regarding models, data, and experiments. In this narrative review, we summarised the existing literature on these three themes, exploring the challenges of providing forecasts, the requirement for real-time linkage of health-related datasets, and the role of ‘experimentation’ in evaluating interventions. This literature review encourages us to broaden our perspective for the future, acknowledging the significance of investing in models, data, and experimentation, but also to invest in areas that are conceptually more abstract: the value of ‘team science’, the need for public trust in science, and in establishing processes for using science in policy. Policy-makers rely on model forecasts early in a pandemic when there is little data, and it is vital to communicate the assumptions, limitations, and uncertainties (theme 1). Linked routine data can provide critical information, for example, in establishing risk factors for adverse outcomes but are often not available quickly enough to make a real-time impact. The interoperability of data resources internationally is required to facilitate sharing across jurisdictions (theme 2). Randomised controlled trials (RCTs) provided timely evidence on the efficacy and safety of vaccinations and pharmaceuticals but were largely conducted in higher income countries, restricting generalisability to low- and middle-income countries (LMIC). Trials for non-pharmaceutical interventions (NPIs) were almost non-existent which was a missed opportunity (theme 3). Building on these themes from the narrative review, we underscore the importance of three other areas that need investment for effective evidence-driven policy-making. The COVID-19 response relied on strong multidisciplinary research infrastructures, but funders and academic institutions need to do more to incentivise team science (4). To enhance public trust in the use of scientific evidence for policy, researchers and policy-makers must work together to clearly communicate uncertainties in current evidence and any need to change policy as evidence evolves (5). Timely policy decisions require an established two-way process between scientists and policy makers to make the best use of evidence (6). For effective preparedness against future pandemics, it is essential to establish models, data, and experiments as fundamental pillars, complemented by efforts in planning and investment towards team science, public trust, and evidence-based policy-making across international communities. The paper concludes with a ‘call to actions’ for both policy-makers and researchers.
Languageen
PublisherPublic Library of Science
SubjectCOVID-19
pandemic
TitleThe importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic
TypeArticle Review
Issue Number11
Volume Number3
ESSN2767-3375
dc.accessType Open Access


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