Evidence map›Paper›PMID 35176623›Full record

Observational studyPublic health2022

College reopening and community spread of COVID-19 in the United States.

C-N Chang, H-Y Chien, L Malagon-Palacios

Abstract readObservational Study
In one paragraph

Observational study in Public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

3 authors.

C-N ChangLife Span Institute, University of Kansas, USA. Electronic address: cnchang@ku.edu.
H-Y ChienDepartment of Educational Psychology, Texas A&M University, USA.
L Malagon-PalaciosLife Span Institute, University of Kansas, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAfter months of lockdown due to the COVID-19 outbreak, the US postsecondary institutions implemented different instruction approaches to bring their students back for the Fall 2020 semester. Given public health concerns with reopening campuses, the study evaluated the impact of Fall 2020 college reopenings on COVID-19 transmission within the 632 US university counties. STUDY

designThis was a retrospective and observational study.

methodsBayesian Structural Time Series (BSTS) models were conducted to investigate the county-level COVID-19 case increases during the first 21 days of Fall 2020. The case increase for each county was estimated by comparing the observed time series (actual daily cases after school reopening) to the BSTS counterfactual time series (predictive daily cases if not reopening during the same time frame). We then used multilevel models to examine the associations between opening approaches (in-person, online, and hybrid) and county-level COVID-19 case increases within 21 and 42 days after classes began. The multigroup comparison between mask and non-mask-required states for these associations were also performed, given that the statewide guidelines might moderate the effects of college opening approaches.

resultsMore than 80% of our university county sample did not experience a significant case increase in Fall 2020. There were no significant relationships between opening approaches and community transmission in both mask-required and non-mask-required states. Only small metropolitan counties and counties with a non-community college or a higher percentage of student population showed significantly positive associations with the case number increase within the first 21-day period of Fall 2020. For the longer 42-day period, the counties with a higher percentage of the student population showed a significant case increase.

conclusionThe overall findings underscored the outcomes of US higher education reopening efforts when the vaccines were still under development in Fall 2020. For individual county results, we invite the college- and county-level decision-makers to interpret their results using our web application.

Indexed as

COVID-19Bayes TheoremCommunicable Disease ControlHumansRetrospective StudiesUnited StatesUniversitiesBayesian Structural Time SeriesCOVID-19Higher educationSchool closureSchool reopeningUS counties

Identifiers

PMID35176623
PMCPMC8747949

What OpenQuestion holds

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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.