Evidence map›Paper›PMID 37768975›Full record

ArticlePloS one2023

Dynamic evolution of policy mix in response to COVID-19: Practice from China.

Lei Du, Wei Lu

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Lei DuSchool of Public Administration, Southwestern University of Finance and Economics, Chengdu, Sichuan Province, China.
Wei LuSchool of Business, Southwest Minzu University, Chengdu, Sichuan Province, China.ORCID 0000-0003-4804-7601

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 is a global pandemic. In response to this unprecedented crisis, Chinese government formulated a series of policies. This research is dedicated to exploring the dynamic evolution of China's policy mix in response to COVID-19 in different crisis response stages from a network perspective. First, a three-dimensional analysis framework of "policy subject-policy target-policy instrument" was developed. Then, based on the data sets collected by textual analysis, the dynamic evolution of policy subject, policy target, policy instrument in China's policy mix in response to COVID-19 was discussed by using the method of SNA. This study concluded that the core policy subject, policy instrument, and policy target of China's response to COVID-19 changed with time. National Health Commission (NHC), Ministry of Finance (MOF), Ministry of Transport (MOT) and Ministry of Human Resources and Social Security (MHRSS) have important influences in the network of policy subjects. Other subjects are more at the edge of the network, and there are few joint issuances among policy subjects. The study also found that the core policy target was adjusted over time, with phased dynamic characteristics. At the initial stage of China's response to COVID-19, "reduce infection and mortality" and "steadily carry out economic and social work" were the core policy targets. With the COVID-19 under control, "enterprise development and work resumption" becomes a new core policy target. In addition, this study also revealed the dynamic evolution and unbalanced use of China's policy instruments in response to COVID-19 in different stages. The combination of policy instruments is mainly composed of "mandatory administration instruments" and "economic incentive instruments", and supplemented by "health promotion instruments" and "voluntary plan instruments". These findings may enrich the literature on COVID-19 policy to help researchers understand the dynamics of policy from a network perspective. Moreover, these findings may provide several valuable implications for policymakers and other countries to formulate more effective policies for epidemic response.

Indexed as

COVID-19Family Planning PolicyChinaDeveloping CountriesHumansPublic Policy

Identifiers

PMID37768975
PMCPMC10538659

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.