Evidence map›Paper›PMID 35206390›Full record

ArticleInternational journal of environmental research and public health2022

Demographics, Socioeconomic Context, and the Spread of Infectious Disease: The Case of COVID-19.

Yung-Hsiang Ying, Wen-Li Lee, Ying-Chen Chi, Mei-Jung Chen, Koyin Chang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Ecosystem degradation and the spread of Covid-19.Environmental monitoring and assessment · 2023
    Review
  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

5 authors.

Yung-Hsiang YingDepartment of Business Administration, National Taiwan Normal University, Taipei 106, Taiwan.
Wen-Li LeeDepartment of Healthcare Information and Management, Ming Chuan University, Taoyuan 333, Taiwan.
Ying-Chen ChiDepartment of Healthcare Information and Management, Ming Chuan University, Taoyuan 333, Taiwan.
Mei-Jung ChenDepartment of Biomedical Engineering, Ming Chuan University, Taoyuan 333, Taiwan.
Koyin ChangDepartment of Healthcare Information and Management, Ming Chuan University, Taoyuan 333, Taiwan.

Funding

Taiwan Ministry of Science and Technology MOST 110-2918-I-130-001
6 · The paper itself

Abstract

importanceDue to the evolving variants of coronavirus disease 2019 (COVID-19), it is important to understand the relationship between the disease condition and socioeconomic, demographic, and health indicators across regions.

backgroundStudies examining the relationships between infectious disease and socioeconomic variables are not yet well established.

designA total of 3042 counties in the United States are included as the observation unit in the study. Two outcome variables employed in the study are the control of disease spread and infection prevalence rates in each county.

methodData are submitted to quantile regression, hierarchical regression, and random forest analyses to understand the extent to which health outcomes are affected by demographics, socioeconomics, and health indicators.

resultsCounties with better control of the disease spread tend to have lower infection rates, and vice versa. When measuring different outcome variables, the common risk factors for COVID-19 with a 5% level of statistical significance include employment ratio, female labor ratio, young population ratio, and residents' average health risk factors, while protective factors include land size, housing value, travel time to work, female population ratio, and ratio of residents who identify themselves as mixed race.

conclusionsThe implications of the findings are that the ability to maintain social distancing and personal hygiene habits are crucial in deterring disease transmission and lowering incidence rates, especially in the early stage of disease formation. Relevant authorities should identify preventive factors and take early actions to fight infectious diseases in the future.

Indexed as

Communicable DiseasesCOVID-19FemaleHumansIncidenceSARS-CoV-2Socioeconomic FactorsUnited Statesinfectious diseasesmixed effect modelquantile regressionsocioeconomics

Identifiers

PMID35206390
PMCPMC8872250

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LicenceCC BY
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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.