“Return to University Campuses Associated with 9% Increase in New COVID-19 Case Rate”
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Abstract
The vast majority of colleges and universities across the United States are bringing students back for in-person instruction in the midst of the COVID-19 pandemic, despite the absence of an effective vaccine or other anti-viral therapeutic treatment. Using data from the New York Times and the American Community Survey, we assess the effect of this return to campus on viral case growth in counties with a significant college student population (“college counties”) relative to non-college counties. We find a significant surge in new cases in a 21-day time frame in college counties, a finding consistent across U.S. Census divisions. These results suggest the need for institutions of higher education and the communities where these institutions reside work together quickly and effectively to mitigate viral transmission and to prevent overwhelming local healthcare infrastructure in college counties.
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Our take
This study, available as a preprint and thus not yet peer reviewed, demonstrates that there was a 9% increase in the number of new cases in college counties compared with non-college counties during the period when many colleges and universities reopened (June to September, 2020). However, these results should be interpreted with caution because some of these differences in college and non-college counties could be explained by: 1) a greater influx of people at the time of reopening; and/or 2) an increase in testing as part of university reopening policies, rather than true increases in risk. Further research will be needed to understand the impact of college reopenings on community transmission, if any.
Study design
ecological
Study population and setting
Publicly available data from the New …
Our take
This study, available as a preprint and thus not yet peer reviewed, demonstrates that there was a 9% increase in the number of new cases in college counties compared with non-college counties during the period when many colleges and universities reopened (June to September, 2020). However, these results should be interpreted with caution because some of these differences in college and non-college counties could be explained by: 1) a greater influx of people at the time of reopening; and/or 2) an increase in testing as part of university reopening policies, rather than true increases in risk. Further research will be needed to understand the impact of college reopenings on community transmission, if any.
Study design
ecological
Study population and setting
Publicly available data from the New York Times COVID-19 database, the US Census Bureau, and the American Community Survey were used to describe differences in the number of COVID-19 cases in college counties (counties where 10% of more of the population is enrolled in college) compared with non-college counties after the initial return to college. Case counts were observed between June 14 and September 6, 2020 at the county level, and there were a total of 3118 county-day observations. The primary outcome of interest was defined as the number of new cases in the three weeks prior to September 6divided by the total number of cases in the twelve weeks prior to September 6, and this was referred to as the “new case rate.” This is a measure of the distribution of cases over the prior twelve weeks, with equal distribution equating to about 0.25 (25%). A “surge” was defined as a proportion greater than 0.25 and a “tapering off” was a proportion less than 0.25.
Summary of main findings
Compared with non-college counties, college counties experience a 9% greater increase in the COVID-19 case rate during the return to campus. There were substantial regional differences, ranging from 3.4% in the Pacific Division to 18.9% in the West North Central Division. The median new case rate was greater than 25% for college counties in all divisions except for the Pacific and Mountain Divisions, indicating a “surge” in cases the last three weeks. The highest new case rate was observed in the West North Central Division at 54.6% of all cases in the last week experienced in the last three weeks.
Study strengths
This study uses aggregate data to quantify differences between college and non-college counties when reopening. The use of the “new case rate” as the outcome allows for comparison across counties and the ability to establish whether or not there was a surge in new cases.
Limitations
When comparing college counties to non-college counties, some of the increase in new cases in college counties could in part be due to an influx of people returning to college rather than a greater level of transmission. Additionally, there is no discussion of changes in testing patterns at the time of return to campus. Many colleges and universities have been implementing large-scale weekly or even bi-weekly mandatory testing of all their students, faculty, and staff. Part of the observed difference between college and non-college counties could be due to increases in testing.
Value added
This study quantifies an increased number of cases reported from counties where colleges reopened compared to other communities without colleges.
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SciScore for 10.1101/2020.10.13.20212183: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Limitations: Interpretation of our findings requires some caution. First, we would expect that part of the case increase in counties with institutions of higher education is simply a direct function of the population of those counties increasing with the return to campus. Second, there is significant variation in local and …
SciScore for 10.1101/2020.10.13.20212183: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Limitations: Interpretation of our findings requires some caution. First, we would expect that part of the case increase in counties with institutions of higher education is simply a direct function of the population of those counties increasing with the return to campus. Second, there is significant variation in local and state-level policy response to the pandemic that is a potential source of omitted variable bias in our analysis. Third, post-secondary institutions are taking myriad approaches to their return to campus. The work of Chris Marsicano and colleagues have documented the various approaches to this policy landscape. These range from full scale returns to campus with in-person instructions, to hybrid models combining the return to in-person combined with virtual learning, to completely moving instructions and university operations online for the duration of the 2020-2021 academic year.14 We are unable to account for the nuances of the variation in instructional model, in addition to the various approaches that are being taken to testing, contact tracing, and other pandemic mitigation strategies. Conclusion: Our analysis reveals a strong association between student return to campus and new case growth, specifically in “college counties” in the United States. For these counties, where at least 10% of the county population is comprised of college students, we see an average increase of 9% in the new case rate relative to non-college counties. These findings are consi...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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