Evidence map›Paper›PMID 38117549›Full record

ArticleJMIR public health and surveillance2023

Evaluation of a Targeted COVID-19 Community Outreach Intervention: Case Report for Precision Public Health.

Isela De La Cerda, Cici X Bauer, Kehe Zhang, Miryoung Lee, Michelle Jones, Arturo Rodriguez, Joseph B McCormick, Susan P Fisher-Hoch

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Precision public health after Covid-19: a scoping review.International journal for equity in health · 2025
    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

8 authors.

Isela De La CerdaDepartment of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health Brownsville Campus, University of Texas Health Science Center at Houston, Brownsville, TX, United States.ORCID 0000-0003-3625-8954
Cici X BauerDepartment of Biostatistics and Data Science, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID 0000-0002-2337-7965
Kehe ZhangDepartment of Biostatistics and Data Science, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID 0000-0001-8013-265X
Miryoung LeeDepartment of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health Brownsville Campus, University of Texas Health Science Center at Houston, Brownsville, TX, United States.ORCID 0000-0003-4088-304X
Michelle JonesPublic Health Department, City of Brownsville, Brownsville, TX, United States.ORCID 0009-0009-9159-9760
Arturo RodriguezPublic Health Department, City of Brownsville, Brownsville, TX, United States.ORCID 0009-0008-8776-7250
Joseph B McCormickDepartment of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health Brownsville Campus, University of Texas Health Science Center at Houston, Brownsville, TX, United States.ORCID 0000-0002-5844-8102
Susan P Fisher-HochDepartment of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health Brownsville Campus, University of Texas Health Science Center at Houston, Brownsville, TX, United States.ORCID 0000-0002-7894-5114

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCameron County, a low-income south Texas-Mexico border county marked by severe health disparities, was consistently among the top counties with the highest COVID-19 mortality in Texas at the onset of the pandemic. The disparity in COVID-19 burden within Texas counties revealed the need for effective interventions to address the specific needs of local health departments and their communities. Publicly available COVID-19 surveillance data were not sufficiently timely or granular to deliver such targeted interventions. An agency-academic collaboration in Cameron used novel geographic information science methods to produce granular COVID-19 surveillance data. These data were used to strategically target an educational outreach intervention named "Boots on the Ground" (BOG) in the City of Brownsville (COB).

objectiveThis study aimed to evaluate the impact of a spatially targeted community intervention on daily COVID-19 test counts.

methodsThe agency-academic collaboration between the COB and UTHealth Houston led to the creation of weekly COVID-19 epidemiological reports at the census tract level. These reports guided the selection of census tracts to deliver targeted BOG between April 21 and June 8, 2020. Recordkeeping of the targeted BOG tracts and the intervention dates, along with COVID-19 daily testing counts per census tract, provided data for intervention evaluation. An interrupted time series design was used to evaluate the impact on COVID-19 test counts 2 weeks before and after targeted BOG. A piecewise Poisson regression analysis was used to quantify the slope (sustained) and intercept (immediate) change between pre- and post-BOG COVID-19 daily test count trends. Additional analysis of COB tracts that did not receive targeted BOG was conducted for comparison purposes.

resultsDuring the intervention period, 18 of the 48 COB census tracts received targeted BOG. Among these, a significant change in the slope between pre- and post-BOG daily test counts was observed in 5 tracts, 80% (n=4) of which had a positive slope change. A positive slope change implied a significant increase in daily COVID-19 test counts 2 weeks after targeted BOG compared to the testing trend observed 2 weeks before intervention. In an additional analysis of the 30 census tracts that did not receive targeted BOG, significant slope changes were observed in 10 tracts, of which positive slope changes were only observed in 20% (n=2). In summary, we found that BOG-targeted tracts had mostly positive daily COVID-19 test count slope changes, whereas untargeted tracts had mostly negative daily COVID-19 test count slope changes.

conclusionsEvaluation of spatially targeted community interventions is necessary to strengthen the evidence base of this important approach for local emergency preparedness. This report highlights how an academic-agency collaboration established and evaluated the impact of a real-time, targeted intervention delivering precision public health to a small community.

Indexed as

Community-Institutional RelationsCOVID-19Public HealthCensus TractCOVID-19 TestingHumanscommunity interventionsemergency preparednesshealth disparitiesintervention evaluationprecision public healthpublic healthpublic health informaticspublic health interventionspatial epidemiologysurveillance

Identifiers

PMID38117549
PMCPMC10765283

What OpenQuestion holds

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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.