Evidence map›Paper›PMID 33148655›Full record

ArticleScience advances2020

Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis.

X Wu, R C Nethery, M B Sabath, D Braun, F Dominici

Abstract read
In one paragraph

Article in Science advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 793 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
793citing papers in PubMed, 3 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

793 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Pooled it
  4. Article
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  9. Ambient Air Pollution and COVID-19 in California.Research report (Health Effects Institute) · 2026
    Article
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  17. A case-crossover analysis of short-term PMCommunications medicine · 2025
    Article
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  19. Article
  20. Article

733 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

X WuDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-4884-657X
R C NetheryDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0001-9895-1477
M B SabathDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-8844-9915
D BraunDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-5177-8598
F DominiciDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. fdominic@hsph.harvard.edu.ORCID 0000-0002-9382-0141

Funding

Translational Research Support CoreP30ES000002 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI SUSAN A KORRICK · 1985 to 2026
$44.6M
National Cohort Studies of Alzheimer's Disease, Related Dementias and Air PollutionR01AG066793 · NIA · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ZANOBETTI, ANTONELLA · 2020 to 2025
$4.2M
Project 3: Cumulative Risk and Geospatial Health Disparities Related to Chemical and Non-Chemical Stressor ExposuresP50MD010428 · NIMHD · HARVARD SCHOOL OF PUBLIC HEALTH · PI LADEN, FRANCINE · 2015 to 2020
$4.0M
Environmental Health Disparities in an Older PopulationR01MD012769 · NIMHD · YALE UNIVERSITY · PI BELL, MICHELLE L · 2017 to 2021
$3.9M
Relationship Between Multiple Environmental Exposures and CVD Incidence and Survival: Vulnerability and SusceptibilityR01ES028033 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI DOMINICI, FRANCESCA, LADEN, FRANCINE · 2018 to 2022
$3.5M
Integrating Air Pollution Prediction Models: Uncertainty Quantification and Propagation in Health StudiesR01ES030616 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DOMINICI, FRANCESCA, KIOUMOURTZOGLOU, MARIANTHI-ANNA · 2020 to 2024
$3.1M
Cardiovascular Health and Air Pollution: A National StudyR01ES024332 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI ZANOBETTI, ANTONELLA · 2015 to 2018
$2.5M
Causal Inference with Interference for Evaluating Air Quality PoliciesR01ES026217 · NIEHS · UNIVERSITY OF TEXAS AT AUSTIN · PI ZIGLER, CORWIN MATTHEW · 2016 to 2021
$2.2M
NIA NIH HHS R01 AG066793NIEHS NIH HHS P30 ES000002NIEHS NIH HHS R01 ES024332NIEHS NIH HHS R01 ES026217NIEHS NIH HHS R01 ES028033NIEHS NIH HHS R01 ES030616NIH HHS R01 AG066793-01NIH HHS R01 ES024332-01A1NIMHD NIH HHS P50 MD010428NIMHD NIH HHS R01 MD012769
6 · The paper itself

Abstract

Assessing whether long-term exposure to air pollution increases the severity of COVID-19 health outcomes, including death, is an important public health objective. Limitations in COVID-19 data availability and quality remain obstacles to conducting conclusive studies on this topic. At present, publicly available COVID-19 outcome data for representative populations are available only as area-level counts. Therefore, studies of long-term exposure to air pollution and COVID-19 outcomes using these data must use an ecological regression analysis, which precludes controlling for individual-level COVID-19 risk factors. We describe these challenges in the context of one of the first preliminary investigations of this question in the United States, where we found that higher historical PM

Indexed as

Air PollutionEcologyCoronavirus InfectionsCOVID-19HumansPandemicsPneumonia, ViralRegression AnalysisUnited States

Identifiers

PMID33148655
PMCPMC7673673

What OpenQuestion holds

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LicenceCC BY-NC
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.