Predictive value of clinical symptoms for COVID-19 diagnosis in young adults.

Objective: Assessment of predictive values of clinical symptoms for COVID-19 diagnosis in young adults. Participants: Nonresidential university students (ages 18-25) participating in surveillance testing and mandatory symptom survey between 9/9/2020 and 11/25/2020. Methods: Retrospective study of test results and symptom survey data. Results: Among 6,489 individuals, 288 (4.4%) tested positive for COVID-19, 90 (31.3%) of whom reported symptoms. COVID-19 prevalence among individuals reporting and not reporting symptoms was 17.2% and 3.3%, respectively. The four symptoms with highest positive predictive values (PPVs) were smell/taste loss (PPV = 38.5%), chills (PPV = 31.5%), muscle/joint pain (PPV = 26.0%), and fever (PPV = 25.9%). Conclusions: Institutions should emphasize COVID-19 risk for highly predictive symptoms in public health messaging to inform individuals on when to seek testing or self-isolation. However, low COVID-19 diagnostic accuracy of clinical symptoms and the high pre-symptomatic/asymptomatic rate (69%) highlight the limitations of voluntary testing strategies employed by higher education institutions during the original strain of SARS-CoV-2.

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots.

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized by a high rate of transmission and low mortality, the COVID-19 pandemic necessitated accurate and efficient diagnostic testing, particularly in closed populations such as residential universities. Initial availability of nucleic acid testing, like nasopharyngeal swabs, was limited due to supply chain pressure which also delayed reporting of test results. Saliva-based reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) testing has shown to be comparable in sensitivity and specificity to other testing methods, and saliva collection is less physically invasive to participants. Consequently, we developed a multiplex RT-qPCR diagnostic assay for population surveillance of Clemson University and the surrounding community. The assay utilized open-source liquid handling robots and thermocyclers instead of complex clinical automation systems to optimize workflow and system flexibility. Automation of saliva-based RT-qPCR enables rapid and accurate detection of a wide range of viral RNA concentrations for both large- and small-scale testing demands. The average turnaround for the automated system was < 9 h for 95% of samples and < 24 h for 99% of samples. The cost for a single test was $2.80 when all reagents were purchased in bulk quantities.

Surveillance-based informative testing for detection and containment of SARS-CoV-2 outbreaks on a public university campus: an observational and modelling study.

BACKGROUND: Despite severe outbreaks of COVID-19 among colleges and universities across the USA during the Fall 2020 semester, the majority of institutions did not routinely test students. While high-frequency repeated testing is considered the most effective strategy for disease mitigation, most institutions do not have the necessary infrastructure or funding for implementation. Therefore, alternative strategies for testing the student population are needed. Our study detailed the implementation and results of testing strategies to mitigate SARS-CoV-2 spread on a university campus, and we aimed to assess the relative effectiveness of the different testing strategies. METHODS: For this retrospective cohort study, we included 6273 on-campus students arriving to a large public university in the rural USA (Clemson, SC, USA) for in-person instruction in the Fall 2020 semester (Sept 21 to Nov 25). Individuals arriving after Sept 23, those who tested positive for SARS-CoV-2 before Aug 19, and student athletes and band members were not included in this study. We implemented two testing strategies to mitigate SARS-CoV-2 spread during this period: a novel surveillance-based informative testing (SBIT) strategy, consisting of random surveillance testing to identify outbreaks in residence hall buildings or floors and target them for follow-up testing (Sept 23 to Oct 5); followed by a repeated weekly surveillance testing (Oct 6 to Nov 22). Relative changes in estimated weekly prevalence were examined. We developed SARS-CoV-2 transmission models to compare the relative effectiveness of weekly testing (900 daily surveillance tests), SBIT (450 daily surveillance tests), random surveillance testing (450 daily surveillance tests), and voluntary testing (0 daily surveillance tests) on disease mitigation. Model parameters were based on our empirical surveillance data in conjunction with published sources. FINDINGS: SBIT was implemented from Sept 23 to Oct 5, and identified outbreaks in eight residence hall buildings and 45 residence hall floors. Targeted testing of residence halls was 2·03 times more likely to detect a positive case than random testing (95% CI 1·67-2·46). Weekly prevalence was reduced from a peak of 8·7% to 5·6% during this 2-week period, a relative reduction of 36% (95% CI 27-44). Prevalence continued to decrease after implementation of weekly testing, reaching 0·8% at the end of in-person instruction (week 9). SARS-CoV-2 transmission models concluded that, in the absence of SBIT (ie, voluntary testing only), the total number of COVID-19 cases would have increased by 154% throughout the semester. Compared with SBIT, random surveillance testing alone would have resulted in a 24% increase in COVID-19 cases. Implementation of weekly testing at the start of the semester would have resulted in 36% fewer COVID-19 cases throughout the semester compared with SBIT, but it would require twice the number of daily tests. INTERPRETATION: It is imperative that institutions rigorously test students during the 2021 academic year. When high-frequency testing (eg, weekly) is not possible, SBIT is an effective strategy to mitigate disease spread among the student population that can be feasibly implemented across colleges and universities. FUNDING: Clemson University, USA.

Vital signs and demographics in the preparticipation sports exam: do they help us find the elusive athlete at risk for sudden cardiac death?

Much attention recently has been paid to the detection of those young athletes who may be at risk for sudden cardiac death (SCD) in sports participation. In this article, we attempt to summarize the remarkably few studies that examine the question of whether vital signs and basic demographics are associated with athletes at risk for SCD. Historical items such as chest pain, dyspnea, and palpitations are not reviewed. The only demographics mentioned in the literature as associated with SCD are being of the male gender, which is associated highly with SCD, and being African-American. Most notably, we were unable to find even prospective data asking the question of whether resting pulse, blood pressure, height, weight, and age are potential risk factors. Therefore, we also have included recent data from our own research to make this summary more complete.