Evidence map›Paper›PMID 40837953›Full record

ArticleFrontiers in public health2025

A framework for modeling county-level COVID-19 transmission.

Yida Bao, Iris Huang, Qi Li, Zheng Zhang, Yuan Xing, Dongfang Hou, Jiafeng Ye

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 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

7 authors.

Yida BaoDepartment of Mathematics, Statistics and Computer Science, University of Wisconsin-Stout, Menomonie, WI, United States.
Iris HuangInglemoor High School, Kenmore, WA, United States.
Qi LiDepartment of Mathematics and Computer Science, Fisk University, Nashville, TN, United States.
Zheng ZhangDepartment of Computer Science and Information Systems, Murray State University, Murray, KY, United States.
Yuan XingDepartment of Mathematics, Statistics and Computer Science, University of Wisconsin-Stout, Menomonie, WI, United States.
Dongfang HouDepartment of Mathematics, Statistics and Computer Science, University of Wisconsin-Stout, Menomonie, WI, United States.
Jiafeng YeResearch Centre of Light Alloy Net Forming, Shanghai Jiao Tong University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines COVID-19 transmission across 3,142 U.S. counties using a truncated dataset from March to September 2020. County-level factors include demographics, socioeconomic status, environmental conditions, and mobility patterns. Ordinary Least Squares regression establishes a baseline for analyzing COVID-19 confirm case counts for each county. We then use Moran's

Indexed as

COVID-19HumansModels, StatisticalSARS-CoV-2Spatial AnalysisUnited Statescounty-level analysisCOVID-19geographically weighted regressionMoranmultilevel modelingspatial dependence

Identifiers

PMID40837953
PMCPMC12361220

What OpenQuestion holds

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LicenceCC BY
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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.