Evidence map›Paper›PMID 32315904›Full record

ArticleThe Science of the total environment2020

Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China.

Yongjian Zhu, Jingui Xie, Fengming Huang, Liqing Cao

Abstract read
In one paragraph

Article in The Science of the total environment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 504 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
504citing papers in PubMed, 5 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

504 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
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  16. Climate change and increased risk of respiratory infections in humans.Bulletin of the World Health Organization · 2025
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444 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Yongjian ZhuSchool of Management, University of Science and Technology of China, Hefei, China. Electronic address: ustczyj@mail.ustc.edu.cn.
Jingui XieThe First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China; Brunel Business School, Brunel University London, Uxbridge, United Kingdom. Electronic address: xiej@ustc.edu.cn.
Fengming HuangThe First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China. Electronic address: 3234119867@qq.com.
Liqing CaoThe First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China. Electronic address: caoliqing@ustc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel coronavirus pneumonia, namely COVID-19, has become a global public health problem. Previous studies have found that air pollution is a risk factor for respiratory infection by carrying microorganisms and affecting body's immunity. This study aimed to explore the relationship between ambient air pollutants and the infection caused by the novel coronavirus. Daily confirmed cases, air pollution concentration and meteorological variables in 120 cities were obtained from January 23, 2020 to February 29, 2020 in China. We applied a generalized additive model to investigate the associations of six air pollutants (PM

Indexed as

Air PollutionBetacoronavirusCoronavirus InfectionsPandemicsPneumonia, ViralAir PollutantsChinaCitiesCOVID-19Environmental ExposureHumansParticulate MatterSARS-CoV-2Air PollutantsParticulate MatterAir pollutionCOVID-19Generalized additive modelNovel coronavirus pneumonia

Identifiers

PMID32315904
PMCPMC7159846

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.