Evidence map›Paper›PMID 33446205›Full record

ArticleInternational journal for equity in health2021

Tracking the effects of COVID-19 in rural China over time.

Huan Wang, Markus Zhang, Robin Li, Oliver Zhong, Hannah Johnstone, Huan Zhou, Hao Xue, Sean Sylvia, Matthew Boswell, Prashant Loyalka and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal for equity in health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
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

20 citing papers in PubMed, 42 citations in OpenAlex.

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  14. COVID-19 Experiences and Health-Related Implications: Results From a Mixed-Method Longitudinal Study of Urban Poor Adolescents in Shanghai.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2022
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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

11 authors at 3 institutions in 2 countries.

Huan WangFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.ORCID 0000-0003-3219-7226
Markus ZhangFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.
Robin LiFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.
Oliver ZhongFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.
Hannah JohnstoneFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.
Huan ZhouWest China School of Public Health, Sichuan University, No. 17, Section 3 Ren Min South Road, Chengdu, Sichuan Province, People's Republic of China. zhouhuan@scu.edu.cn.
Hao XueFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.
Sean SylviaGillings School of Global Public Health, University of North Carolina at Chapel Hill, 1101D McGavran-Greenberg Hall, CB#7411, Chapel Hill, NC, 27599-7411, USA.
Matthew BoswellFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.
Prashant LoyalkaFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.
Scott RozelleFreeman Spogli Institute for International Studies, Stanford University, 616 Jane Stanford Way, Stanford, California, 94305, USA.
Stanford University · USSichuan University · CNUniversity of North Carolina at Chapel Hill · US

Funding

Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
NICHD NIH HHS P2C HD050924
6 · The paper itself

Abstract

backgroundChina issued strict nationwide guidelines to combat the COVID-19 outbreak in January 2020 and gradually loosened the restrictions on movement in early March. Little is known about how these disease control measures affected the 600 million people who live in rural China. The goal of this paper is to document the quarantine measures implemented in rural China outside the epicenter of Hubei Province and to assess the socioeconomic effect of the measures on rural communities over time.

methodsWe conducted three rounds of interviews with informants from 726 villages in seven provinces, accounting for over 25% of China's overall rural population. The survey collected data on rural quarantine implementation; COVID-19 infections and deaths in the survey villages; and effects of the quarantine on employment, income, education, health care, and government policies to address any negative impacts. The empirical findings of the work established that strict quarantine measures were implemented in rural villages throughout China in February.

resultsThere was little spread of COVID-19 in rural communities: an infection rate of 0.001% and zero deaths reported in our sample. However, there were negative social and economic outcomes, including high rates of unemployment, falling household income, rising prices, and disrupted student learning. Health care was generally accessible, but many delayed their non-COVID-19 health care due to the quarantine measures. Only 20% of villagers received any form of local government aid, and only 11% of villages received financial subsidies. There were no reports of national government aid programs that targeted rural villagers in the sample areas.

conclusionsBy examining the economic and social effects of the COVID-19 restrictions in rural communities, this study will help to guide other middle- and low-income countries in their containment and restorative processes. Without consideration for economically vulnerable populations, economic hardships and poverty will likely continue to have a negative impact on the most susceptible communities.

Indexed as

QuarantineChinaCOVID-19HumansRural PopulationSocioeconomic FactorsChinaCOVID-19Rural community

Identifiers

PMID33446205
PMCPMC7807215
OpenAlexW3123054746

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.