Michelle Quarti Machado da Rosa, Ângela Maria Bagattini, Isabella Inês Rodrigues Rosa, Gabriel Berg de Almeida, Lorena Mendes Simon, Suzi Alves Camey, Cristiana Maria Toscano
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引用次数: 0
Abstract
Modeling played a significant role in underpinning public policy during the COVID-19 pandemic, when decision-making faced a context of limited evidence. This is a cross-sectional study that included and characterized institutions and research groups that worked with COVID-19 modeling and decision-making support. Two strategies were used for identification: 1) scoping review, and 2) group identification by snowball sampling. A total of 100 studies and 30 institutions were identified. Of the 40 researchers who reported interaction with health managers, 20 programmers, mathematicians, physicians, epidemiologists, statisticians and physicists were interviewed. With respect to institutional partnerships, 14 researchers reported having participated in national and/or international partnerships. Only a few (5/20) reported some type of formal collaboration between the group and health management. A deficiency was observed in the demand for modeling and in communication to support management during the COVID-19 pandemic. Reshaping the process of formulating and implementing public policy in health emergencies can promote strong health systems and ensure a better response to pandemics.
期刊介绍:
Ciência & Saúde Coletiva publishes debates, analyses, and results of research on a Specific Theme considered current and relevant to the field of Collective Health. Its abbreviated title is Ciênc. saúde coletiva, which should be used in bibliographies, footnotes and bibliographical references and strips.