Potential Community and Campus Covid-19 Outcomes Under University and College Reopening Scenarios

Assessment of a Multifaceted Approach, Including Frequent PCR Testing, to Mitigation of COVID-19 Transmission at a Residential Historically Black University

Importance

COVID-19 posed an unprecedented threat to residential colleges in the fall of 2020. While there were mathematical models of COVID-19 transmission, there were no established or tested protocols of COVID-19 testing or mitigation for school administrators to follow.

Objective

To investigate the association of a multifaceted COVID-19 mitigation strategy using social, behavioral, and educational interventions and a program of frequent testing with prevalence of disease spread.

Design, Setting, and Participants

This cohort study was conducted as a retrospective review of COVID-19 positivity from August 16, 2020, to April 30, 2021, at Delaware State University, a publicly funded historically Black university. Participants included all students, faculty, and staff members with a campus presence. Positivity rates after use of mitigation strategies and testing on campus were compared with those of the surrounding community. Data were analyzed from July through September 2021.

Exposures

Mitigation strategies included education and outreach about social distancing, masking, and handwashing, and a COVID-19 testing plan consisted of twice-weekly polymerase chain reaction (PCR) screening using anterior nasal samples (fall and early spring semester) and then saliva-based samples (middle to late spring semester).

Main Outcomes and Measures

Cumulative tests, infections, daily quarantine, and isolation residence hall occupancy were measured, and comparisons were made with statewide COVID-19 positivity rates.

Results

The campus cohort included 2320 individuals (1575 resident students, 415 nonresident students, and 330 faculty or staff members). There were 1488 (64.1%) women and 832 (35.9%) men; mean (SD) age was 27.5 (12.9) years. During the fall semester, 36 500 COVID-19 PCR tests were performed. Weekly positivity rates ranged from 0 of 372 tests to 16 of 869 tests (1.8%) (mean [SD] positivity rate, 0.5% [0.5%]; 168 positive results and 36 312 negative results). During the same period, statewide positivity ranged from 589 of 25 120 tests (2.3%) to 5405 of 54 596 tests (9.9%) (mean [SD] positivity rate, 4.8% [2.6%]). In the spring semester, 39 045 PCR tests were performed. Weekly positivity rates ranged from 4 of 2028 tests (0.2%) to 36 of 900 tests (4.0%) (mean [SD] positivity rate, 0.8% [0.9%]; 267 positive results and 38 767 negative results). During the same period, statewide positivity ranged from 1336 of 37 254 tests (3.6%) to 3630 of 42 458 tests (8.5%) (mean [SD] positivity rate, 5.1% [1.3%]). Compared with statewide rates, campus positivity rates were mean (SD) 4.4 (2.6) percentage points lower during the fall semester (P < .001) and mean (SD) 5.6 (1.6) percentage points lower during the spring semester (P < .001). Total daily quarantine and isolation residence hall occupancy ranged from 0 to 43 students in the fall and 1 to 47 students during the spring.

Conclusions and Relevance

This study found that the combination of campuswide mitigation policies and twice-weekly COVID-19 PCR screening was associated with a significant decrease in COVID-19 positivity at a residential historically Black university campus compared with the surrounding community. Given the socioeconomic demographics of many students at historically Black colleges and universities, keeping these resident campuses open is critical not only to ensure access to educational resources, but also to provide housing and food security.

Balancing finances, politics, and public health: international student enrollment and reopening plans at US higher education institutions amid the COVID-19 pandemic

Drawing from resource dependence theory, this study explores the extent to which international student enrollment related to institutional decisions to shift to in-person instructional strategies during the COVID-19 pandemic. We focus our study particularly on July 2020, a time during which tensions around international students' legal status in the US were especially high. Our results suggest that leaders at private not-for-profit institutions were significantly more likely to shift instructional strategies to include more in-person instruction, thus allowing more international students to enroll but also placing at risk the health of individuals on their campuses and in their local communities. A similar result was not found for public institutions. These results speak to the extent to which private institutions in the US have become financially dependent on international students' tuition and have clear implications for the financial futures of US higher education institutions.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10734-021-00768-7.

Optimization in the Context of COVID-19 Prediction and Control: A Literature Review

This paper presents an overview of some key results from a body of optimization studies that are specifically related to COVID-19, as reported in the literature during 2020-2021. As shown in this paper, optimization studies in the context of COVID-19 have been used for many aspects of the pandemic. From these studies, it is observed that since COVID-19 is a multifaceted problem, it cannot be studied from a single perspective or framework, and neither can the related optimization models. Four new and different frameworks are proposed that capture the essence of analyzing COVID-19 (or any pandemic for that matter) and the relevant optimization models. These are: (i) microscale vs. macroscale perspective; (ii) early stages vs. later stages perspective; (iii) aspects with direct vs. indirect relationship to COVID-19; and (iv) compartmentalized perspective. To limit the scope of the review, only optimization studies related to the prediction and control of COVID-19 are considered (public health focused), and which utilize formal optimization techniques or machine learning approaches. In this context and to the best of our knowledge, this survey paper is the first in the literature with a focus on the prediction and control related optimization studies. These studies include optimization of screening testing strategies, prediction, prevention and control, resource management, vaccination prioritization, and decision support tools. Upon reviewing the literature, this paper identifies current gaps and major challenges that hinder the closure of these gaps and provides some insights into future research directions.

Managing SARS-CoV-2 Testing in Schools with an Artificial Intelligence Model and Application Developed by Simulation Data

Research on SARS-CoV-2 and its social implications have become a major focus to interdisciplinary teams worldwide. As interest in more direct solutions, such as mass testing and vaccination grows, several studies appear to be dedicated to the operationalization of those solutions, leveraging both traditional and new methodologies, and, increasingly, the combination of both. This research examines the challenges anticipated for preventative testing of SARS-CoV-2 in schools and proposes an artificial intelligence (AI)-powered agent-based model crafted specifically for school scenarios. This research shows that in the absence of real data, simulation-based data can be used to develop an artificial intelligence model for the application of rapid assessment of school testing policies.