ArticleHealth research policy and systems2021
Coevolution of COVID-19 research and China's policies.
Article in Health research policy and systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- From pathogens to policy: using network analysis to map the knowledge base on human-zoonotic disease dynamics underpinning global pandemic policy.Health research policy and systems · 2025Article
- A comment-driven evidence appraisal approach to promoting research findings into practice when only uncertain evidence is available.Health research policy and systems · 2023Article
- Regulating the product quality of COVID-19 antigen testing reagents: A tripartite evolutionary game analysis under China's legal framework.Frontiers in public health · 2022Article
- Influence on emergency digit replantation and outcome assessment after COVID-19 virus nucleic acid testing normalization.Frontiers in surgery · 2022Article
- The Running Track of Government Responsibility During the Pandemic, Characteristic Analysis of Policy Documents Relevant to the COVID-19 Pandemic Released by Beijing Municipal Government in 2020.Frontiers in public health · 2021Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundIn the era of evidence-based policy-making (EBPM), scientific outputs and public policy should engage with each other in a more interactive and coherent way. Notably, this is becoming increasingly critical in preparing for public health emergencies.
methodsTo explore the coevolution dynamics between science and policy (SAP), this study explored the changes in, and development of, COVID-19 research in the early period of the COVID-19 outbreak in China, from 30 December 2019 to 26 June 2020. In this study, VOSviewer was adopted to calculate the link strength of items extracted from scientific publications, and machine learning clustering analysis of scientific publications was carried out to explore dynamic trends in scientific research. Trends in relevant policies that corresponded to changing trends in scientific research were then traced.
resultsThe study observes a salient change in research content as follows: an earlier focus on "children and pregnant patients", "common symptoms", "nucleic acid test", and "non-Chinese medicine" was gradually replaced with a focus on "aged patients", "pregnant patients", "severe symptoms and asymptomatic infection", "antibody assay", and "Chinese medicine". "Mental health" is persistent throughout China's COVID-19 research. Further, our research reveals a correlation between the evolution of COVID-19 policies and the dynamic development of COVID-19 research. The average issuance time of relevant COVID-19 policies in China is 8.36 days after the launching of related research.
conclusionsIn the early stage of the outbreak in China, the formulation of research-driven-COVID-19 policies and related scientific research followed a similar dynamic trend, which is clearly a manifestation of a coevolution model (CEM). The results of this study apply more broadly to the formulation of policies during public health emergencies, and provide the foundation for future EBPM research.
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