Evidence map›Paper›PMID 32874851›Full record

ArticleHealth policy and technology2020

COVID-19 pandemic in China: Context, experience and lessons.

Weiwei Xu, Jing Wu, Lidan Cao

Abstract read
In one paragraph

Article in Health policy and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
–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

46 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Prevalence of Breast Cancer Screening in Asia: Systematic Review and Meta-Analysis.Asian Pacific journal of cancer prevention : APJCP · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Weiwei XuGongJing Healthcare Ltd., China.
Jing WuSchool of Pharmaceutical Science and Technology, Tianjin University, China.
Lidan CaoSchool of Pharmaceutical Science and Technology, Tianjin University, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The first cluster of COVID-19 cases was reported in Wuhan, China on December 29th, 2019. Since then, China has experienced a pandemic of COVID-19.

objectiveThis study aims to present the context in which the pandemic has evolved, the government's response and the pandemic's impact on public health and national economy.

methodsA review was conducted to collect relevant data from press releases and government reports.

resultsCOVID-19 poses a major public health threat on China with a cumulative number of cases over 89,000 (data cut-off date: August 9th, 2020). Between January and February 2020, China implemented a series of escalating policies (including a stringent nation-wide lockdown) to combat the pandemic. Therefore, it has been to a large extent limited to the Wuhan region. Social media such as WeChat and SinaWeibo played a crucial role in disseminating government information and public campaigns during the pandemic. Technologies were adopted to enable contact tracing and population travel patterns. The Chinese central government mobilized healthcare resources including healthcare personnel and medical materials to Wuhan in a highly effective way. Both central and regional governments launched financial policies to stimulate the economy, including special loans, tax extension, reduction or waiver. Nevertheless, the economy in China was significantly impacted especially during the lockdown period.

conclusionsChina has responded to the COVID-19 epidemic in a highly centralized and effective way. Balancing the needs to prevent a future pandemic and to boost economic recovery remains a challenge.

Indexed as

ChinaCOVID-19ImpactPolicyTechnology

Identifiers

PMID32874851
PMCPMC7451009

What OpenQuestion holds

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Registered trials

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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.