Evidence map›Paper›PMID 39316309›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2024

Scale-Up of COVID-19 Testing Services in NYC, 2020-2021: Lessons Learned to Maximize Reach, Equity and Timeliness.

Lorna E Thorpe, Sarah Conderino, Stefanie Bendik, Carolyn Berry, Nadia Islam, Rachel Massar, Michelle Chau, Rita Larson, Margaret M Paul, Chuan Hong and 4 more

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2024. 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

14 authors.

Lorna E ThorpeDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA. lorna.thorpe@nyulangone.org.ORCID http://orcid.org/0000-0001-7515-0562
Sarah ConderinoDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Stefanie BendikDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Carolyn BerryDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Nadia IslamDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Rachel MassarDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Michelle ChauDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Rita LarsonDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Margaret M PaulDivision of Health Care Delivery, Mayo Clinic, Phoenix, AZ, USA.
Chuan HongDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Andrew FairDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Andrea R TitusDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Anna BershteynDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
Andrew WallachOffice of Ambulatory Care, New York City Health + Hospitals, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During infectious disease epidemics, accurate diagnostic testing is key to rapidly identify and treat cases, and mitigate transmission. When a novel pathogen is involved, building testing capacity and scaling testing services at the local level can present major challenges to healthcare systems, public health agencies, and laboratories. This mixed methods study examined lessons learned from the scale-up of SARS-CoV-2 testing services in New York City (NYC), as a core part of NYC's Test & Trace program. Using quantitative and geospatial analyses, the authors assessed program success at maximizing reach, equity, and timeliness of SARS-CoV-2 diagnostic testing services across NYC neighborhoods. Qualitative analysis of key informant interviews elucidated key decisions, facilitators, and barriers involved in the scale-up of SARS-CoV-2 testing services. A major early facilitator was the ability to establish working relationships with private sector vendors and contractors to rapidly procure and manufacture necessary supplies locally. NYC residents were, on average, less than 25 min away from free SARS-CoV-2 diagnostic testing services by public transport, and services were successfully directed to most neighborhoods with the highest transmission rates, with only one notable exception. A key feature was to direct mobile testing vans and rapid antigen testing services to areas based on real-time neighborhood transmission data. Municipal leaders should prioritize fortifying supply chains, establish cross-sectoral partnerships to support and extend testing services, plan for continuous testing and validation of assays, ensure open communication feedback loops with CBO partners, and maintain infrastructure to support mobile services during infectious disease emergencies.

Indexed as

COVID-19COVID-19 TestingSARS-CoV-2HumansNew York CityCOVID-19EquityNew York CityReachTesting services

Identifiers

PMID39316309
PMCPMC11461424

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.