Evidence map›Paper›PMID 36158763›Full record

ArticleLandscape and urban planning2022

Green spaces, especially nearby forest, may reduce the SARS-CoV-2 infection rate: A nationwide study in the United States.

Bin Jiang, Yuwen Yang, Long Chen, Xueming Liu, Xueying Wu, Bin Chen, Chris Webster, William C Sullivan, Linda Larsen, Jingjing Wang and 1 more

Abstract read
In one paragraph

Article in Landscape and urban planning, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Homo sapiens, industrialisation and the environmental mismatch hypothesis.Biological reviews of the Cambridge Philosophical Society · 2026
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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.

Bin JiangUrban Environments and Human Health Lab, HKUrbanLabs, Faculty of Architecture, The University of Hong Kong, Hong Kong Special Administrative Region.
Yuwen YangUrban Environments and Human Health Lab, HKUrbanLabs, Faculty of Architecture, The University of Hong Kong, Hong Kong Special Administrative Region.
Long ChenDepartment of Architecture and Civil Engineering, College of Engineering, City University of Hong Kong, Hong Kong Special Administrative Region.
Xueming LiuUrban Environments and Human Health Lab, HKUrbanLabs, Faculty of Architecture, The University of Hong Kong, Hong Kong Special Administrative Region.
Xueying WuDepartment of Architecture and Civil Engineering, College of Engineering, City University of Hong Kong, Hong Kong Special Administrative Region.
Bin ChenFuture Urbanity & Sustainable Environment (FUSE) Lab, Division of Landscape Architecture, Department of Architecture, Faculty of Architecture, The University of Hong Kong, Hong Kong Special Administrative Region.
Chris WebsterHKUrbanLabs, Faculty of Architecture, The University of Hong Kong, Hong Kong Special Administrative Region.
William C SullivanSmart, Healthy Communities Initiative, University of Illinois at Urbana-Champaign, USA.
Linda LarsenSmart Energy Design Assistance Center, University of Illinois at Urbana-Champaign, USA.
Jingjing WangDepartment of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong Special Administrative Region.
Yi LuDepartment of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong Special Administrative Region.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus pandemic is an ongoing global crisis that has profoundly harmed public health. Although studies found exposure to green spaces can provide multiple health benefits, the relationship between exposure to green spaces and the SARS-CoV-2 infection rate is unclear. This is a critical knowledge gap for research and practice. In this study, we examined the relationship between total green space, seven types of green space, and a year of SARS-CoV-2 infection data across 3,108 counties in the contiguous United States, after controlling for spatial autocorrelation and multiple types of covariates. First, we examined the association between total green space and SARS-CoV-2 infection rate. Next, we examined the association between different types of green space and SARS-CoV-2 infection rate. Then, we examined forest-infection rate association across five time periods and five urbanicity levels. Lastly, we examined the association between infection rate and population-weighted exposure to forest at varying buffer distances (100 m to 4 km). We found that total green space was negative associated with the SARS-CoV-2 infection rate. Furthermore, two forest variables (forest outside park and forest inside park) had the strongest negative association with the infection rate, while open space variables had mixed associations with the infection rate. Forest outside park was more effective than forest inside park. The optimal buffer distances associated with lowest infection rate are within 1,200 m for forest outside park and within 600 m for forest inside park. Altogether, the findings suggest that green spaces, especially nearby forest, may significantly mitigate risk of SARS-CoV-2 infection.

Indexed as

Causal mechanismsCOVID-19 pandemicForestGreen spacesInfection riskOpen space

Identifiers

PMID36158763
PMCPMC9485427

What OpenQuestion holds

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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.