Evidence map›Paper›PMID 36377230›Full record

ArticlePreventive medicine reports2022

Sentinel surveillance of SARS-CoV-2 rates and equity impacts using labor and delivery patients in Phoenix, Arizona.

Caitlyn J Linehan, Trisalyn Nelson, Celeste V Bailey, Esma Gel, Dean V Coonrod, Cheryl K Roth

Abstract read
In one paragraph

Article in Preventive medicine reports, 2022. 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. 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

6 authors.

Caitlyn J LinehanDepartment of Geography, University of California, Santa Barbara, Santa Barbara, CA, USA.
Trisalyn NelsonDangermond Chair of Geography, University of California, Santa Barbara, Santa Barbara, CA, USA.
Celeste V BaileyDepartment of Obstetrics and Gynecology, Creighton University School of Medicine Phoenix Regional Campus, Refugee Women's Health Clinic, Valleywise Health, Phoenix, AZ, USA.
Esma GelCynthia Hardin Milligan Chair of Business and Professor of Supply Chain Management and Analytics, University of Nebraska, NB, USA.
Dean V CoonrodDepartment of Obstetrics and Gynecology, Valleywise Health / District Medical Group, Department of Obstetrics and Gynecology, Creighton University School of Medicine Phoenix Regional Campus, Phoenix, AZ, USA.
Cheryl K RothHonorHealth Scottsdale Shea Medical Center, Scottsdale, AZ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proactive management of SARS-CoV-2 requires timely and complete population data to track the evolution of the virus and identify at risk populations. However, many cases are asymptomatic and are not easily discovered through traditional testing efforts. Sentinel surveillance can be used to estimate the prevalence of infections for geographical areas but requires identification of sentinels who are representative of the larger population. Our goal is to evaluate applicability of a population of labor and delivery patients for sentinel surveillance system for monitoring the prevalence of SARS-CoV-2 infection. We tested 5307 labor and delivery patients from two hospitals in Phoenix, Arizona, finding 195 SARS-CoV-2 positive. Most positive cases were associated with people who were asymptomatic (79.44%), similar to statewide rates. Our results add to the growing body of evidence that SARS-CoV-2 disproportionately impacts people of color, with Black people having the highest positive rates (5.92%). People with private medical insurance had the lowest positive rates (2.53%), while Medicaid patients had a positive rate of 5.54% and people without insurance had the highest positive rates (6.12%). With diverse people reporting for care and being tested regardless of symptoms, labor and delivery patients may serve as ideal sentinels for asymptomatic detection of SARS-CoV-2 and monitoring impacts across a wide range of social and economic classes. A more robust system for infectious disease management requires the expanded participation of additional hospitals so that the sentinels are more representative of the population at large, reflecting geographic and neighborhood level patterns of infection and risk.

Indexed as

COVID-19Infectious disease managementLabor & DeliverySARS-CoV-2SentinelSocial determinants of health

Identifiers

PMID36377230
PMCPMC9637539

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.