Evidence map›Paper›PMID 40065445›Full record

ArticleArchives of public health = Archives belges de sante publique2025

Assessing the role of socioeconomic factors-income, education, broadband access, and healthy foods on location-wise disparities in COVID-19 cases.

Aindrila Chakraborty, Jaymeen Shah

Abstract read
In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Aindrila ChakrabortyDepartment of Management Information Systems, College of Business and Management, Metro State University, Minneapolis, MN, 55106, USA. aindrila.chakraborty@metrostate.edu.
Jaymeen ShahDepartment of Information Systems and Analytics, McCoy College of Business, Texas State University, San Marcos, TX, 78666, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe COVID-19 pandemic presented an unprecedented worldwide challenge to public health and the economy. However, the effect varied in different population groups and locations. This study examines how the preexisting socioeconomic conditions, income, education, access to broadband internet, and healthy foods affect people's pandemic-related health-protective behavior and lead to this differential impact in the U.S.

methodsThis study utilizes a dynamic panel-data-based regression analysis on a nationwide dataset of U.S. counties.

resultsHigher income, education level, and broadband speed reduce the probability of violating recommended preventive measures, promote health awareness among individuals, and lower COVID-19 cases. In contrast, low access to healthy foods increases the number of cases. Additionally, our study reveals several interesting findings related to people's food habits, living conditions, and the connection between education and access to broadband internet that contribute to the differential impact of countywide COVID-19 cases.

conclusionsInsights from our data-driven analysis enable healthcare authorities to understand where resources should be allocated at the beginning of a pandemic to reduce disease spread and thus, build a greater resiliency for the next pandemic. Hence, our findings provide significant insights to government and healthcare officials to devise health awareness campaigns and develop advocacy measures and policies in conjunction with policymakers to contain future pandemics.

Indexed as

BroadbandCOVID-19 pandemicEducationHealthy foodsMedian incomeSocioeconomic

Identifiers

PMID40065445
PMCPMC11892225

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.