Evidence map›Paper›PMID 36787729›Full record

ArticleEmerging infectious diseases2023

COVID-19 Test Allocation Strategy to Mitigate SARS-CoV-2 Infections across School Districts.

Remy Pasco, Kaitlyn Johnson, Spencer J Fox, Kelly A Pierce, Maureen Johnson-León, Michael Lachmann, David P Morton, Lauren Ancel Meyers

Abstract read
In one paragraph

Article in Emerging infectious diseases, 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. Evaluating infectious disease forecasts with allocation scoring rules.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2024
    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.

Remy Pasco
Kaitlyn Johnson
Spencer J Fox
Kelly A Pierce
Maureen Johnson-León
Michael Lachmann
David P Morton
Lauren Ancel Meyers

Funding

Accelerating viral outbreak detection in US cities using mechanistic models, machine learning and diverse geospatial dataR01AI151176 · NIAID · YALE UNIVERSITY · PI GALVANI, ALISON P, MEYERS, LAUREN ANCEL · 2020 to 2024
$3.9M
RFA-IP-22-004, Modeling toolkit to evaluate multifaceted control strategies for seasonal and pandemic influenzaU01IP001136 · IP · UNIVERSITY OF TEXAS AT AUSTIN · PI MEYERS, LAUREN ANCEL · 2020 to 2024
$3.4M
NCIRD CDC HHS U01 IP001136NIAID NIH HHS R01 AI151176
6 · The paper itself

Abstract

In response to COVID-19, schools across the United States closed in early 2020; many did not fully reopen until late 2021. Although regular testing of asymptomatic students, teachers, and staff can reduce transmission risks, few school systems consistently used proactive testing to safeguard return to classrooms. Socioeconomically diverse public school districts might vary testing levels across campuses to ensure fair, effective use of limited resources. We describe a test allocation approach to reduce overall infections and disparities across school districts. Using a model of SARS-CoV-2 transmission in schools fit to data from a large metropolitan school district in Texas, we reduced incidence between the highest and lowest risk schools from a 5.6-fold difference under proportional test allocation to 1.8-fold difference under our optimized test allocation. This approach provides a roadmap to help school districts deploy proactive testing and mitigate risks of future SARS-CoV-2 variants and other pathogen threats.

Indexed as

COVID-19COVID-19 TestingHumansSARS-CoV-2SchoolsUnited Statesasymptomatic screeningcoronaviruscoronavirus diseaseCOVID-19epidemiological modelingoptimizationpublic health responserespiratory infectionsSARSSARS-CoV-2severe acute respiratory syndrome coronavirus 2United Statesviruseszoonoses

Identifiers

PMID36787729
PMCPMC9973671

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.