Evidence map›Paper›PMID 41709132›Full record

ArticleJournal of primary care & community health

Examine COVID-19 Pandemic Patterns in Daycare Centers: How Access to Screening Matters.

Meghana Potturu, Nova C Phillips-Latham, Samuel Mathis, Wei-Chen Lee

Abstract read
In one paragraph

Article in Journal of primary care & community health. 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
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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

4 authors.

Meghana PotturuUniversity of Texas Medical Branch, Galveston, TX, USA.
Nova C Phillips-LathamUniversity of Texas Medical Branch, Galveston, TX, USA.
Samuel MathisUniversity of Texas Medical Branch, Galveston, TX, USA.
Wei-Chen LeeUniversity of Texas Medical Branch, Galveston, TX, USA.ORCID 0000-0003-4333-5444

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic highlighted significant health disparities across the United States, with Texas ranking among the lowest in healthcare quality. This study explores the relationship between county-level factors and COVID-19 cases in Texas daycare centers. Unlike broader studies on COVID-19 disparities, this research uniquely examines the daycare population, a critical yet understudied environment, through county-level social determinants of health.

methodsUsing 2020-2022 Covid data from the Texas Health & Human Services Commission and the 2020 County Health Rankings, we analyzed COVID-19 case counts among children and staff in licensed daycare facilities across 225 Texas counties. We classified counties into 4 patterns: high child-high staff, high child-low staff, low child-high staff, and low child-low staff. We also examined the association between county-level determinants and pandemic patterns.

resultsCounties with higher COVID-19 cases in daycare centers have higher proportions of racial/ethnic minorities, but with better access to primary care physicians, better socioeconomic conditions (eg, % of children in poverty and median household income) and greater urbanization (

conclusionThese findings underscore the influence of better access to screening on the COVID-19 counts, highlighting the importance of epidemiological surveillance. Improving healthcare access, addressing economic inequalities, and tailoring mitigation strategies are key to closing the gaps in different transmission rates among daycare centers.

Indexed as

Child Day Care CentersCOVID-19Health Services AccessibilityChildChild, PreschoolHealthcare DisparitiesHumansPandemicsSARS-CoV-2Socioeconomic Disparities in HealthSocioeconomic FactorsTexaschildrenCOVID-19daycareinfectionssocial determinants of health

Identifiers

PMID41709132
PMCPMC12921168

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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.