Evidence map›Paper›PMID 36523405›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Optimizing COVID-19 testing strategies on college campuses: evaluation of the health and economic costs.

Kaitlyn E Johnson, Remy Pasco, Spencer Woody, Michael Lachmann, Maureen Johnson-Leon, Darlene Bhavnani, Jessica Klima, A David Paltiel, Spencer J Fox, Lauren Ancel Meyers

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Kaitlyn E JohnsonDepartment of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Remy PascoDepartment of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Spencer WoodyDepartment of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Michael LachmannSanta Fe Institute, Santa Fe, New Mexico, United States of America.
Maureen Johnson-LeonDepartment of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Darlene BhavnaniDepartment of Population Health, Dell Medical School, The University of Texas at Austin, Austin, Texas.
Jessica KlimaOffice of the Vice President for Research, The University of Texas at Austin, Austin, Texas.
A David PaltielPublic Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut.
Spencer J FoxDepartment of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Lauren Ancel MeyersDepartment of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.
The University of Texas at Austin · USSanta Fe Institute · USRockefeller Foundation · USUniversity of Georgia · US

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
ACL HHS U01IP001136NCIRD CDC HHS U01 IP001136NIAID NIH HHS R01 AI151176
6 · The paper itself

Abstract

Colleges and universities in the US struggled to provide safe in-person education throughout the COVID-19 pandemic. Testing coupled with isolation is a nimble intervention strategy that can be tailored to mitigate health and economic costs, as the virus and our arsenal of medical countermeasures continue to evolve. We developed a decision-support tool to aid in the design of university-based testing strategies using a mathematical model of SARS-CoV-2 transmission. Applying this framework to a large public university reopening in the fall of 2021 with a 60% student vaccination rate, we find that the optimal strategy, in terms of health and economic costs, is twice weekly antigen testing of all students. This strategy provides a 95% guarantee that, throughout the fall semester, case counts would not exceed the CDC's original high transmission threshold of 100 cases per 100k persons over 7 days. As the virus and our medical armament continue to evolve, testing will remain a flexible tool for managing risks and keeping campuses open. We have implemented this model as an online tool to facilitate the design of testing strategies that adjust for COVID-19 conditions, university-specific parameters, and institutional goals.

Identifiers

PMID36523405
PMCPMC9753781
OpenAlexW4311623547

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.