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In a recent study posted to the Research Square* preprint server, researchers assessed the risk of community transmission of coronavirus disease 2019 (COVID-19) at US universities.

Study: Modeling Community COVID-19 Transmission Risk Associated with U.S. Universities. Image Credit: Halfpoint/Shutterstock

As of August 2022, over 583 million confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection cases, including 6.4 million deaths, have been reported globally. Studies have reported that elderly and immunocompromised persons are the most susceptible to COVID-19 disease severity. These reports suggest that younger individuals less vulnerable to the infection are primary introducers of SARS-CoV-2 to communities, especially around universities and colleges.   

About the study

In the present study, researchers estimated the number of COVID-19 cases and mortality rates in US counties and compared those to counties that have and do not have colleges.

The team obtained laboratory-confirmed SARS-CoV-2 cases and mortality data between 1 January 2020 and 30 March 2021. By the end of the study period on 30 March 2021, 22,385,335 COVID-19 cases and 374, paroxetine no prescription v 130 COVID-19-related deaths were reported. Each infection and mortality case in this dataset comprised a total of 32 elements which included demographics such as age, ethnicity, race, sex, and area of residence.

Additionally, university enrollment (UE) data were obtained from the Integrated Postsecondary Education Data System (IPEDS). The team also aggregated the total enrollment for every post-secondary institution during the Fall semester between the 2018-2019 academic years. The aggregated data was subsequently categorized into four classes: (1) large having enrollment of more than 15,000, (2) medium with enrollments between 5000 and 15,000, (3) small with enrollments between zero and 5000, and (4) no enrollment. Moreover, the county population was divided into age groups as zero to nine, 10 to 19, 20 to 29, 30 to 39, 40 to 49, 50 to 59, 60 to 69, 70 to 79, and more than 80 years.    


The study results showed that between 1 January 2020 and 30 March 2021, an increasing number of individuals enrolled in the counties was related to a significant decline in COVID-19 cases, while no such remarkable reduction was noted in mortality rates. In comparison to counties having no universities, the study indicated a 1% reduction in COVID-19 cases among counties having small university enrollments, with an 8% decrease among those with medium university enrollments and 16% among those with large university enrollments.

The team noted similar patterns among mortality rates and standardized cases across different age groups across all enrollment types. This was observed in the 20 years to 59 years old individuals who accounted for a majority of the cases, while the highest case rate was displayed in the 20 to 29-year-old age group. Although the case rate was lower in adults aged less than 50 years, adults aged over 50 had the highest mortality rates irrespective of the type of county university enrollment.

Notably, mortality rates were found to increase with age. On average, the risk of mortality due to COVID-19 in individuals over 80 years was twice that in people aged between 70 to 79 years, 2.5 times that in people aged 60 to 69 years, and five times that in persons aged between 50 and 59 years old.

Across the three COVID-19 waves, the team observed a remarkable decline in the mortality as well as case rates with an increasing number of university enrollments as compared to counties that had no university enrollments. The first and second waves across all the counties displayed case rates of less than 105 per 100,000 and less than 2.94 per 100,000. However, this increased in the third wave. Such a rapid increase noted in the mortality and case rates was observed for all the counties but was considerably less severe when the university enrollments increased.

Furthermore, county-level descriptions like the existence of a state mask mandate, size of county-level enrollment, and self-reported wearing of facemasks accounted for 40% of the counties having large enrollments. The contribution of counties with medium enrollment to the variation in the number of COVID-19 cases adjusted as per the population was significantly dependent on institutional factors, including institutional category and size category, and COVID-19 mitigation strategies in the campus such as testing strategy and category of the medium of instruction. Counties with small enrollment totals were majorly dependent on COVID-19 mitigation strategies.            

Overall, the study findings showed that an increase in the university enrollment of a county was significantly related to a lower rate of COVID-19 infections as well as related mortalities in comparison to counties that had no university enrollments. 

*Important notice

Research Square publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
  • J. A. Uelmen, Heather Kopsco, Jameson Mori et al. (2022). Modeling Community COVID-19 Transmission Risk Associated with U.S. Universities. Research Squaredoi: https://doi.org/10.21203/rs.3.rs-1899505/v1 https://www.researchsquare.com/article/rs-1899505/v1

Posted in: Medical Science News | Medical Research News | Disease/Infection News

Tags: Coronavirus, Coronavirus Disease COVID-19, covid-19, Education, Laboratory, Mortality, Research, Respiratory, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Syndrome

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Written by

Bhavana Kunkalikar

Bhavana Kunkalikar is a medical writer based in Goa, India. Her academic background is in Pharmaceutical sciences and she holds a Bachelor's degree in Pharmacy. Her educational background allowed her to foster an interest in anatomical and physiological sciences. Her college project work based on ‘The manifestations and causes of sickle cell anemia’ formed the stepping stone to a life-long fascination with human pathophysiology.

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