Evidence map›Paper›PMID 34153607›Full record

ArticleEnvironmental pollution (Barking, Essex : 1987)2021

Long-term air pollution and other risk factors associated with COVID-19 at the census tract level in Colorado.

Kevin Berg, Paul Romer Present, Kristy Richardson

Abstract read
In one paragraph

Article in Environmental pollution (Barking, Essex : 1987), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Ambient Air Pollution and COVID-19 in California.Research report (Health Effects Institute) · 2026
    Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Air pollution and respiratory infections: the past, present, and future.Toxicological sciences : an official journal of the Society of Toxicology · 2023
    Review
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
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  15. 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

3 authors.

Kevin BergColorado Department of Public Health and Environment, United States. Electronic address: kevin.berg@state.co.us.
Paul Romer PresentColorado Department of Public Health and Environment, United States.
Kristy RichardsonColorado Department of Public Health and Environment, United States.

Funding

Madison County NY Individual Water System and EH Capacity Building InitiativeUE2EH001346 · EH · MADISON COUNTY HEALTH DEPARTMENT · PI SNYDER, GEOFFREY · 2015 to 2015
$105k
NCEH CDC HHS UE2 EH001346
6 · The paper itself

Abstract

Previous nationwide studies have reported links between long-term concentrations of fine particulate matter (PM2.5) and COVID-19 infection and mortality rates. In order to translate these results to the state level, we use Bayesian hierarchical models to explore potential links between long-term PM2.5 concentrations and census tract-level rates of COVID-19 outcomes (infections, hospitalizations, and deaths) in Colorado. We explicitly consider how the uncertainty in PM2.5 estimates affects our results by comparing four different PM2.5 surfaces from academic and governmental organizations. After controlling for 20 census tract-level covariates, we find that our results depend heavily on the choice of PM2.5 surface. Using PM2.5 estimates from the United States EPA, we find that a 1 μg/m

Indexed as

Air PollutantsAir PollutionCOVID-19Bayes TheoremCensusesColoradoEnvironmental ExposureHumansParticulate MatterRisk FactorsSARS-CoV-2United StatesAir PollutantsParticulate MatterAir pollutionCOVID-19DisparityEquityPM2.5SARS-CoV-2

Identifiers

PMID34153607
PMCPMC8202820

What Socratic 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 Socratic graph.