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1.
Soc Sci Med ; 348: 116783, 2024 May.
Artículo en Inglés | MEDLINE | ID: mdl-38574589

RESUMEN

BACKGROUND: While political polarization in policy opinions, preferences, and observance is well established, little is known about whether and how such divisions evolve, and possibly attenuate, over time. Using the COVID-19 pandemic in Brazil as the backdrop, we examine the longitudinal evolution of a highly relevant and polarizing policy: adherence to the COVID-19 vaccination. METHODS: Studies 1 (N = 3346) and 2 (N = 10,214) use nationwide surveys to document initial differences and subsequent changes in vaccination adherence between conservatives ("Bolsonaristas") and non-conservatives ("non-Bolsonaristas"). Study 3 (N = 742) uses an original dataset to investigate belief changes among conservatives and their association with asymmetric changes in vaccination adherence. RESULTS: Despite substantial differences at the early stages of rollout, the gap in vaccination adherence between conservatives and non-conservatives significantly decreased with the passage of time, driven essentially by a much faster uptake among the initially most skeptic-the conservatives. Study 3 demonstrates that the asymmetric changes in vaccination adherence were associated with meaningful belief changes among the conservatives, especially about the perceived effectiveness of the COVID-19 vaccines and the expected adherence of peers to the vaccination campaign. CONCLUSIONS: Together, these studies show that, in a context where the superiority of the promoted policy becomes clear over time and individuals have the opportunity to revisit prior beliefs, even intense political polarization can be attenuated.


Asunto(s)
Vacunas contra la COVID-19 , COVID-19 , Política , Humanos , Brasil , COVID-19/prevención & control , COVID-19/epidemiología , Vacunas contra la COVID-19/administración & dosificación , Estudios Longitudinales , Vacunación/estadística & datos numéricos , Vacunación/psicología , Política de Salud , SARS-CoV-2
2.
Wellcome Open Res ; 9: 156, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-39429630

RESUMEN

The COVID CIRCLE initiative Research Project Tracker by UKCDR and GloPID-R and associated living mapping review (LMR) showed the importance of sharing and analysing data on research at the point of funding to improve coordination during a pandemic. This approach can also help with research preparedness for outbreaks and hence our new programme the Pandemic Preparedness: Analytical Capacity and Funding Tracking Programme (Pandemic PACT) has been established. The LMR described in this protocol builds on the previous UKCDR and GloPID-R COVID-19 Research Project database with addition of the priority diseases from the WHO Blueprint list plus initial additions of pandemic influenza, mpox and plague. We capture data on new funding commitments directly from funders and map these against a core ontology (aligned to existing research roadmaps). We will analyse regularly collated new research funding commitments to provide an open, accessible, near-real-time overview of the funding landscape for a wide range of infectious disease and pandemic preparedness research and assess gaps. The periodicity of updates will be increased in the event of a major outbreak. We anticipate that this LMR and the associated online tool will be a useful resource for funders, policy makers and researchers. In the future, our work will inform a more coordinated approach to research funding by providing evidence and data, including identification of gaps in funding allocation with a particular focus on low- and middle-income countries.

3.
Epidemics ; 43: 100673, 2023 06.
Artículo en Inglés | MEDLINE | ID: mdl-36863099

RESUMEN

The COVID-19 pandemic has led governments worldwide to impose extensive restrictions on citizens, some of which may have long-term impact after their removal. Education is arguably the policy domain where closure policies are anticipated to lead to greatest lasting loss, in this case learning loss. Currently, limited data exists from which researchers and practitioners can draw insightful conclusions about how to remedy the problem. In this paper, we outline the global pattern in pandemic school-closure periods and illustrate data needs through the examples drawn from Brazil and India, two large countries which experienced prolonged periods of school closures during the pandemic. We conclude with a series of recommendations for building an improved data environment at government, school and household levels, to serve the building back agenda in education, and to provide better opportunities for evidence-based policymaking thereafter.


Asunto(s)
COVID-19 , Humanos , COVID-19/epidemiología , Pandemias/prevención & control , Instituciones Académicas , India , Brasil
4.
Nat Hum Behav ; 5(9): 1145-1160, 2021 09.
Artículo en Inglés | MEDLINE | ID: mdl-34345009

RESUMEN

As the COVID-19 pandemic lingers, the possibility of 'pandemic fatigue' has raised worldwide concerns. Here, we examine whether there was a gradual reduction in adherence to protective behaviours against COVID-19 from March through December 2020, as hypothesized in expectations of fatigue. We considered self-report behaviours from representative samples of the populations of 14 countries (N = 238,797), as well as mobility and policy data for 124 countries. Our results show that changes in adherence were empirically meaningful and geographically widespread. While a low-cost and habituating behaviour (mask wearing) exhibited a linear rise in adherence, high-cost and sensitizing behaviours (physical distancing) declined, but this decline decelerated over time, with small rebounds seen in later months. Reductions in adherence to physical distancing showed little difference across societal groups, but were less intense in countries with high interpersonal trust. Alternative underlying mechanisms and policy implications are discussed.


Asunto(s)
COVID-19/prevención & control , Cooperación del Paciente/psicología , Actitud Frente a la Salud , Salud Global , Política de Salud , Humanos , Control de Infecciones , Máscaras/estadística & datos numéricos , Distanciamiento Físico , Autoinforme , Factores Socioeconómicos , Confianza
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