Evidence map›Paper›PMID 37007437›Full record

ArticleApplied geography (Sevenoaks, England)2023

Seeing the forest and the trees: Holistic view of social distancing on the spread of COVID-19 in China.

Danlin Yu, Yaojun Zhang, Jun Meng, Xiaoxi Wang, Linfeng He, Meng Jia, Jie Ouyang, Yu Han, Ge Zhang, Yao Lu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Applied geography (Sevenoaks, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Danlin YuDepartment of Earth and Environmental Studies, Montclair State University, Montclair, NJ, 07043, USA.
Yaojun ZhangSchool of Applied Economics, Renmin University of China, Beijing, 100086, China.
Jun MengDepartment of Obs.&Gyn., Beijing Youan Hospital, Capital Medical University, Beijing, 100069, China.
Xiaoxi WangSchool of Sociology and Population Studies, Renmin University of China, Beijing, 100086, China.
Linfeng HeSchool of Sociology and Population Studies, Renmin University of China, Beijing, 100086, China.
Meng JiaSchool of Sociology and Population Studies, Renmin University of China, Beijing, 100086, China.
Jie OuyangSchool of Sociology and Population Studies, Renmin University of China, Beijing, 100086, China.
Yu HanSchool of Sociology and Population Studies, Renmin University of China, Beijing, 100086, China.
Ge ZhangSchool of Management, Minzu University of China, Beijing, 100081, China.
Yao LuSchool of Ethnology and Sociology, Minzu University of China, Beijing, 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human social and behavioral activities play significant roles in the spread of COVID-19. Social-distancing centered non-pharmaceutical interventions (NPIs) are the best strategies to curb the spread of COVID-19 prior to an effective pharmaceutical or vaccine solution. This study investigates various social-distancing measures' impact on the spread of COVID-19 using advanced global and novel local geospatial techniques. Social distancing measures are acquired through website analysis, document text analysis, and other big data extraction strategies. A spatial panel regression model and a newly proposed geographically weighted panel regression model are applied to investigate the global and local relationships between the spread of COVID-19 and the various social distancing measures. Results from the combined global and local analyses confirm the effectiveness of NPI strategies to curb the spread of COVID-19. While global level strategies allow a nation to implement social distancing measures immediately at the beginning to minimize the impact of the disease, local level strategies fine tune such measures based on different times and places to provide targeted implementation to balance conflicting demands during the pandemic. The local level analysis further suggests that implementing different NPI strategies in different locations might allow us to battle unknown global pandemic more efficiently.

Indexed as

ChinaCOVID-19Geographically weighted panel regressionGlobal and local spatial analysisSocial distancing

Identifiers

PMID37007437
PMCPMC10040366

What OpenQuestion holds

Textmetadata
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.