Simulating COVID-19 classroom transmission on a university campus

Airborne transmission is now believed to be the primary way that COVID-19 spreads. We study the airborne transmission risk associated with holding in-person classes on university campuses. We utilize a model for airborne transmission risk in an enclosed room that considers the air change rate for the room, mask efficiency, initial infection probability of the occupants, and also the activity level of the occupants. We introduce, and use for our evaluations, a metric R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eff</sup> that represents the ratio of new infections that occur over a week due to classroom interactions to the number of infected individuals at the beginning of the week. This can be seen as a surrogate for the well-known R0 reproductive number metric, but limited in scope to classroom interactions and calculated on a weekly basis. The simulations take into account the possibility of repeated in-classroom interactions between students throughout the week. We presented model predictions were generated using Fall 2019 and Fall 2020 course registration data at a large US university, allowing us to evaluate the difference in transmission risk between in-person and hybrid programs. We quantify the impact of parameters such as reduced occupancy levels and mask efficacy. Our simulations indicate that universal mask usage results in an approximately 3.6× reduction in new infections through classroom interactions. Moving 90% of the classes online leads to about 18× reduction in new cases. Reducing class occupancy to 20%, by having hybrid classes, results in an approximately 2.15 - 2.3× further reduction in new infections.

COVID-19: What do we know?

Use of SARS-CoV-2-infected deceased organ donors: Should we always "just say no?"

Utilization of deceased donors during a pandemic: argument against using SARS-CoV-2-positive donors.

Management of mother–newborn dyads in the COVID-19 era

Does COVID-19 cause pre-eclampsia?

SARS-CoV-2 Transmission Risk to Household and Family Contacts by Vaccinated Healthcare Workers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the current coronavirus disease 2019 (COVID-19) pandemic, is evolving. Thus, the risk of airborne transmission in confined spaces may be higher, and corresponding precautions should be re-appraised. Here, we obtained the quantum generation rate (q) value of three SARS-CoV-2 variants (Alpha, Delta, and Omicron) for the Wells-Riley equation with a reproductive number-based fitted approach and estimated the association between the infection probability and ventilation rates. The q value was 89–165 h−1 for Alpha variant, 312–935 h−1 for Delta variant, and 725–2,345 h−1 for Omicron variant. The ventilation rates increased to ensure an infection probability of less than 1%, and were 8,000–14,000 m3 h−1, 26,000–80,000 m3 h−1, and 64,000–250,000 m3 h−1 per infector for the Alpha, Delta, and Omicron variants, respectively. If the infector and susceptible person wore N95 masks, the required ventilation rates decreased to about 1/100 of the values required without masks, which can be achieved in most typical scenarios. An air purifier was ineffective for reducing transmission when used in scenarios without masks. Preventing prolonged exposure time in confined spaces remains critical in reducing the risk of airborne transmission for highly contagious SARS-CoV-2 variants.

Coronavirus Disease 2019 and Vaccination of Children and Adolescents: Prospects and Challenges

The Role of Children and Young People in the Transmission of SARS-CoV-2.

COVID-19 severity, rather than sex or age, predicts SARS-CoV-2 kinetics, and SARS-CoV-2 viral load from lower respiratory tract specimens may predict severe disease days before clinical deterioration for COVID-19 patients.

AGA Institute Rapid Review and Recommendations on the Role of Pre-Procedure SARS-CoV-2 Testing and Endoscopy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has substantially affected daily life. Sustainable testing practices are essential to balance the resource demands of widespread testing with the need to reduce the health impacts of COVID-19. However, the effectiveness of specific testing strategies for symptomatic and asymptomatic individuals in reducing COVID-19 cases, hospitalisations, and deaths remains uncertain. To evaluate the effectiveness of different SARS-CoV-2 testing strategies in reducing COVID-19 cases, hospitalisations, and deaths amongst suspected cases and asymptomatic individuals. We searched CENTRAL, MEDLINE (Ovid), Embase (Elsevier), Europe PMC, ClinicalTrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform. We also conducted reference checks, citation searches, and contacted study authors to identify eligible studies. The most recent search was conducted on 07 October 2024. We included randomised controlled trials (RCTs), non-randomised studies of interventions (NRSIs), controlled before-and-after studies (CBA), matched cohort studies, and observational studies with a comparison group involving suspected or asymptomatic individuals. Eligible studies compared testing strategy versus no testing or standard care or usual practice; one testing strategy with another, such as antigen-detecting rapid diagnostic tests (RDTs) versus nucleic acid amplification testing (NAAT), including reverse transcription polymerase chain reaction (RT-PCR); home-based versus provider-administered testing; one-time testing versus repeated testing at different frequencies; and targeted testing versus widespread testing. Combinations of these components were also considered. In this review, we define 'SARS-CoV-2 testing strategy' as a complex intervention comprising multiple varying components, including test type (e.g. NAAT, antigen-detecting RDT), sample type (e.g. nasopharyngeal swab, saliva), target population (e.g. symptomatic, contacts), setting (e.g. home, clinic, congregate), frequency of testing (e.g. one-time, weekly, daily), and response protocol (e.g. isolation, confirmatory testing, treatment). We excluded single-arm studies, reviews, theses, editorials, letters, commentaries, studies reported solely in abstract form, laboratory or animal studies, mathematical modelling studies, and diagnostic test accuracy studies. Our critical outcomes were: COVID-19 cases avoided (reduction in new cases); COVID-19-related hospitalisations avoided (reduction in hospital admissions); COVID-19-related deaths avoided (reduction in mortality); and serious adverse events related to testing, including unnecessary interventions, employment impacts, isolation effects, and psychological harms. We used the Risk of bias 2 (RoB 2) tool to assess the risk of bias in RCTs and the ROBINS-I tool to assess the risk of bias in NRSIs, CBA studies, and matched cohort studies. As a meta-analysis was not feasible due to the nature of the data, we applied Synthesis Without Meta-analysis (SWiM) methods. We assessed the certainty of the evidence for each outcome using the GRADE approach. We included 21 studies (10 RCTs and 11 NRSIs) with 13,312,327 participants. Among these, 13 studies-comprising eight RCTs and five NRSIs-either reported one or more prespecified outcomes (four studies), provided relevant information through proxy measurements (five studies), or supplied information following author correspondence (four studies). We present the prioritised comparisons and critical outcomes. For the comparison testing strategy versus no testing or standard care or usual practice, one included study measured two critical outcomes. The study did not measure the other critical outcomes: COVID-19 cases avoided, and serious adverse events related to testing. No studies measured any critical outcomes for the other prioritised comparison: antigen-detecting RDT versus NAAT testing. Benefits and harms of testing strategy versus no testing or standard care or usual practice One observational study with a comparison group, conducted in a long-term care facility in Israel, compared weekly SARS-CoV-2 RT-PCR testing with no testing and measured two of our critical outcomes. Based on the analysis, the evidence is very uncertain about the effect of SARS-CoV-2 RT-PCR testing on reducing hospitalisation (decrease in the hospitalisation rate from 13.59% to 11.41%; 1 study, 162,205 participants, very low-certainty evidence) and mortality (33.8% decrease in expected mortality; 1 study, 162,205 participants, very low-certainty evidence) compared to no testing. We downgraded the certainty of the evidence because of methodological limitations, indirectness, and imprecision. The available data are of very low-certainty. Only one of the 21 included studies reported hospitalisations or deaths; therefore, we cannot draw conclusions about the effects of testing strategy versus no testing on reducing hospitalisation and mortality. No studies evaluated other critical outcomes i.e. COVID-19 cases avoided, and serious adverse events related to testing. Future research should aim for consistency and relevance by using clearly defined outcomes, preferably based on a standardised core outcome set. A qualitative evidence synthesis (QES) would help identify barriers and facilitators to routine SARS-CoV-2 testing in healthcare settings, which could help inform intervention development. The QES would explore factors affecting the implementation of routine testing, drawing on the perspectives of healthcare providers, patients, and other interest holders. This Cochrane review was partially funded by the World Health Organization (WHO) and the Health Research Board of Ireland. Protocol (2025) DOI: 10.1002/14651858.CD016192.

Perinatal COVID-19.

Healthcare workers working on COVID-19 wards experience a 31-fold increased risk of infection with SARS-CoV-2 compared to colleagues on non-COVID-19 wards whilst wearing fluid-resistant surgical masks, and FFP3 respirators provide up to 100% protection against infection.