Evidence map›Paper›PMID 33532804›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Passing the Test: A model-based analysis of safe school-reopening strategies.

Alyssa Bilinski, Joshua A Salomon, John Giardina, Andrea Ciaranello, Meagan C Fitzpatrick

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. 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, 12 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Alyssa BilinskiInterfaculty Initiative in Health Policy, Harvard Graduate School of Arts and Sciences.
Joshua A SalomonCenter for Health Policy & Center for Primary Care and Outcomes Research, Stanford University School of Medicine.
John GiardinaInterfaculty Initiative in Health Policy, Harvard Graduate School of Arts and Sciences.
Andrea CiaranelloMedical Practice Evaluation Center and Division of Infectious Disease, Massachusetts General Hospital, Harvard Medical School.
Meagan C FitzpatrickCenter for Vaccine Development and Global Health, University of Maryland School of Medicine.
Harvard University · USStanford University · USUniversity of Maryland, Baltimore · US

Funding

Optimizing HIV Care in Less Developed CountriesR01AI058736 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Kenneth Alan Freedberg, Emily Parker Hyle · 2004 to 2026
$21.5M
Optimizing HIV Care in Less Developed CountriesR37AI058736 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI FREEDBERG, KENNETH ALAN · 2018 to 2024
$6.6M
Mathematical modeling to optimize rotavirus vaccination in sub-Saharan AfricaK01AI141576 · NIAID · UNIVERSITY OF MARYLAND BALTIMORE · PI FITZPATRICK, MEAGAN COLLEEN · 2019 to 2023
$649k
NIAID NIH HHS K01 AI141576NIAID NIH HHS R01 AI058736NIAID NIH HHS R37 AI058736
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has induced historic educational disruptions. In December 2020, at least two-thirds of US public school students were not attending full-time in-person education. The Biden Administration has expressed that reopening schools is a priority.

objectiveTo compare risks of SARS-COV-2 transmission in schools across different school-based prevention strategies and levels of community transmission.

designWe developed an agent-based network model to simulate transmission in elementary and high school communities, including home, school, and inter-household interactions.

settingWe parameterized school structure based on average US classrooms, with elementary schools of 638 students and high schools of 1,451 students. We varied daily community incidence from 1 to 100 cases per 100,000 population. Patients (or Participants). We simulated students, faculty/staff, and adult household members.

interventionsWe evaluated isolation of symptomatic individuals, quarantine of an infected individual's contacts, reduced class sizes, alternative schedules, staff vaccination, and weekly asymptomatic screening. MEASUREMENTS: We projected transmission among students, staff and families during one month following introduction of a single infection into a school. We also calculated the number of infections expected for a typical 8-week quarter, contingent on community incidence rate.

resultsSchool transmission risk varies according to student age and community incidence and is substantially reduced with effective, consistent mitigation measures. Nevertheless, when transmission occurs, it may be difficult to detect without regular, frequent testing due to the subclinical nature of most infections in children. Teacher vaccination can reduce transmission to staff, while asymptomatic screening both improves understanding of local circumstances and reduces transmission, facilitating five-day schedules at full classroom capacity. LIMITATIONS: There is uncertainty about susceptibility and infectiousness of children and low precision regarding the effectiveness of specific prevention measures, particularly with emergence of new variants.

conclusionWith controlled community transmission and moderate school-based prevention measures, elementary schools can open with few in-school transmissions, while high schools require more intensive mitigation. Asymptomatic screening can both reduce transmission and provide useful information for decision-makers.

Identifiers

PMID33532804
PMCPMC7852255
OpenAlexW3121319318

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.