ArticleFrontiers in public health2022
Governmental Inter-sectoral Strategies to Prevent and Control COVID-19 in a Megacity: A Policy Brief From Shanghai, China.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- The ongoing impact of policy documents on the pandemic based on the framework of the "4Rs" theory and policy tools: in China.BMC public health · 2025Article
- Research on safety strategies for nucleic acid testing in sudden epidemic conditions based on a SEIARD dynamic model.Scientific reports · 2024Article
- A Cross-Sectional Survey of Different Types of School Bullying before and during COVID-19 in Shantou City, China.International journal of environmental research and public health · 2023Article
- Comprehensive Analysis of the COVID-19: Based on the Social-Related Indexes From NUMBEO.Frontiers in public health · 2022Article
- Commentary: China's Zero-COVID Approach Depends on Shanghai's Outbreak Control.Frontiers in public health · 2022Article
- COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion.Frontiers in public health · 2022Article
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Authors and funding
5 authors.
Funding
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Abstract
This policy brief aims to help policymakers develop inter-sectoral interventions in megacities to prevent and control COVID-19. Based on the case of Changning District in Shanghai, China, several policy options are identified. The guiding principles include ensuring a coordinated national response (i.e., moderation is required in epidemic prevention and control); making science-based, precise, and differentiated epidemic control strategies; and establishing a joint prevention and control mechanism. Policy tools include localized management, closed-loop management, community grid management, digital management, and sub-population management. There is no "one size fits all" policy; however, it will be helpful to learn by trial and error through on-the-ground experience with minimal information in real time.
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