Evidence map›Paper›PMID 35977196›Full record

ArticleJAMA health forum2021

Evaluation of Allocation Schemes of COVID-19 Testing Resources in a Community-Based Door-to-Door Testing Program.

Ben Chugg, Lisa Lu, Derek Ouyang, Benjamin Anderson, Raymond Ha, Alexis D'Agostino, Anandi Sujeer, Sarah L Rudman, Analilia Garcia, Daniel E Ho

Open access · goldAbstract read
In one paragraph

Article in JAMA health forum, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.9field-weighted citation impact, top 22% of its field
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

12 citing papers in PubMed, 17 citations in OpenAlex.

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  10. Community of Practice ofFrontiers in public health · 2023
    Article
  11. Challenges Faced in Large-Scale Nucleic Acid Testing during the Sudden Outbreak of the B.1.617.2 (Delta).International journal of environmental research and public health · 2022
    Article
  12. 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

10 authors at 2 institutions in 1 country.

Ben ChuggRegulation, Evaluation, and Governance Laboratory, Stanford University, Stanford, California.
Lisa LuRegulation, Evaluation, and Governance Laboratory, Stanford University, Stanford, California.
Derek OuyangRegulation, Evaluation, and Governance Laboratory, Stanford University, Stanford, California.
Benjamin AndersonRegulation, Evaluation, and Governance Laboratory, Stanford University, Stanford, California.
Raymond HaRegulation, Evaluation, and Governance Laboratory, Stanford University, Stanford, California.
Alexis D'AgostinoSanta Clara County Public Health Department, San Jose, California.
Anandi SujeerSanta Clara County Public Health Department, San Jose, California.
Sarah L RudmanSanta Clara County Public Health Department, San Jose, California.
Analilia GarciaSanta Clara County Public Health Department, San Jose, California.
Daniel E HoRegulation, Evaluation, and Governance Laboratory, Stanford University, Stanford, California.
Stanford University · USSanta Clara County Behavioral Health Services · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Overcoming social barriers to COVID-19 testing is an important issue, especially given the demographic disparities in case incidence rates and testing. Delivering culturally appropriate testing resources using data-driven approaches in partnership with community-based health workers is promising, but little data are available on the design and effect of such interventions. Objectives: To assess and evaluate a door-to-door COVID-19 testing initiative that allocates visits by community health workers by selecting households in areas with a high number of index cases, by using uncertainty sampling for areas where the positivity rate may be highest, and by relying on local knowledge of the health workers. Design Setting and Participants: This cohort study was performed from December 18, 2020, to February 18, 2021. Community health workers visited households in neighborhoods in East San Jose, California, based on index cases or uncertainty sampling while retaining discretion to use local knowledge to administer tests. The health workers, also known as Interventions: The Main Outcomes and Measures: A determination of whether door-to-door COVID-19 testing was associated with an increase in the overall number of tests conducted, the demographic distribution of the door-to-door tests vs local testing sites, and the difference in positivity rates among the 3 door-to-door allocation strategies. Results: A total of 785 residents underwent door-to-door testing, and 756 were included in the analysis. Among the 756 individuals undergoing testing (61.1% female; 28.2% aged 45-64 years), door-to-door COVID-19 testing reached different populations than standard public health surveillance, with 87.6% (95% CI, 85.0%-89.8%) being Latinx individuals. The closest available testing site only reached 49.0% (95% CI, 48.3%-49.8%) Latinx individuals. Uncertainty sampling provided the most effective allocation, with a 10.8% (95% CI, 6.8%-16.0%) positivity rate, followed by 6.4% (95% CI, 4.1%-9.4%) for local knowledge, and 2.6% (95% CI, 0.7%-6.6%) for index area selection. The intervention was also associated with increased overall testing capacity by 60% to 90%, depending on the testing protocol. Conclusions and Relevance: In this cohort study of 785 participants, uncertainty sampling, which has not been used conventionally in public health, showed promising results for allocating testing resources. Community-based door-to-door interventions and leveraging of community knowledge were associated with reduced demographic disparities in testing.

Indexed as

COVID-19COVID-19 TestingCohort StudiesCommunity Health WorkersFemaleHumansMaleSARS-CoV-2

Identifiers

PMID35977196
PMCPMC8796878
OpenAlexW3197754909

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.