Evidence map›Paper›PMID 34628294›Full record

ArticleThe Science of the total environment2022

COVID-19 in New York state: Effects of demographics and air quality on infection and fatality.

Sumona Mondal, Chaya Chaipitakporn, Vijay Kumar, Bridget Wangler, Supraja Gurajala, Suresh Dhaniyala, Shantanu Sur

Abstract read
In one paragraph

Article in The Science of the total environment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

7 authors.

Sumona MondalDepartment of Mathematics, Clarkson University, Potsdam, NY, USA.
Chaya ChaipitakpornDavid D. Reh School of Business, Clarkson University, Potsdam, NY, USA.
Vijay KumarDepartment of Mathematics, Clarkson University, Potsdam, NY, USA.
Bridget WanglerDavid D. Reh School of Business, Clarkson University, Potsdam, NY, USA.
Supraja GurajalaDepartment of Computer Science, SUNY Potsdam, Potsdam, NY, USA.
Suresh DhaniyalaDepartment of Mechanical and Aeronautical Engineering, Clarkson University, Potsdam, NY, USA.
Shantanu SurDepartment of Biology, Clarkson University, Potsdam, NY, USA. Electronic address: ssur@clarkson.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) has had a global impact that has been unevenly distributed among and even within countries. Multiple demographic and environmental factors have been associated with the risk of COVID-19 spread and fatality, including age, gender, ethnicity, poverty, and air quality among others. However, specific contributions of these factors are yet to be understood. Here, we attempted to explain the variability in infection, death, and fatality rates by understanding the contributions of a few selected factors. We compared the incidence of COVID-19 in New York State (NYS) counties during the first wave of infection and analyzed how different demographic and environmental variables associate with the variation observed across the counties. We observed that infection and death rates, two important COVID-19 metrics, to be highly correlated with both being highest in counties located near New York City, considered as one of the epicenters of the infection in the US. In contrast, disease fatality was found to be highest in a different set of counties despite registering a low infection rate. To investigate this apparent discrepancy, we divided the counties into three clusters based on COVID-19 infection, death, or fatality, and compared the differences in the demographic and environmental variables such as ethnicity, age, population density, poverty, temperature, and air quality in each of these clusters. Furthermore, a regression model built on this data reveals PM

Indexed as

Air PollutionCOVID-19HumansIncidenceNew YorkNew York CitySARS-CoV-2Air qualityClusteringCOVID-19New York statePM(2.5)Stepwise regression

Identifiers

PMID34628294
PMCPMC8461036

What OpenQuestion holds

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Registered trials

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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.