Modeling the Spread of COVID-19 in University Communities (preprint)

Mathematical and simulation models are often used to predict the spread of a disease and estimate the impact of public health interventions, and many such models have been developed and used during the COVID-19 pandemic. This paper describes a study that systematically compared models for a university community, which has a much smaller but more connected population than a state or nation. We developed a stochastic agent-based model, a deterministic compartment model, and a model based on ordinary differential equations. All three models represented the disease progression with the same susceptible-exposed-infectious-recovered (SEIR) model. We created a baseline scenario for a population of 14,000 students and faculty and eleven other scenarios for combinations of interventions such as regular testing, contact tracing, quarantine, isolation, moving courses online, mask wearing, improving ventilation, and vaccination. We used parameter values from other epidemiological studies and incorporated data about COVID-19 testing in College Park, Maryland, but the study was designed to compare modeling approaches to each other using a synthetic population. For each scenario we used the models to estimate the number of persons who become infected over a semester of 119 days. We evaluated the models by comparing their predictions and evaluating their parsimony and computational effort. The agent-based model (ABM) and the deterministic compartment model (DCM) had similar results with cyclic flow of persons to and from quarantine, but the model based on ordinary differential equations failed to capture these dynamics. The ABM's computation time was much greater than the other two models' computation time. The DCM captured some of the dynamics that were present in the ABM's predictions and, like those from the ABM, clearly showed the importance of testing and moving classes on-line.

Evolution of SARS-CoV-2 Shedding in Exhaled Breath Aerosols (preprint)

Aerosol inhalation is increasingly well recognized as a major if not primary mode of transmission of SARS-CoV-21,2. Over the course of the COVID-19 pandemic, three highly transmissible lineages evolved and became globally dominant3. One hypothesis to explain increased transmissibility is that natural selection favours variants with higher rates of viral aerosol shedding. However, the extent of aerosol shedding of successive SARS-CoV-2 variants is unknown. Here, we demonstrate that viral shedding (measured as RNA copies) into exhaled breath aerosol was significantly greater during infections with Alpha, Delta, and Omicron than with ancestral strains and variants not associated with increased transmissibility. The three highly transmissible variants independently evolved a high viral aerosol shedding phenotype, demonstrating convergent evolution. We did not observe statistically significant differences in rates of shedding between Alpha, Delta, and Omicron infections. The highest shedder in our study, however, had an Omicron infection and shed three orders of magnitude more viral RNA copies than the maximum observed for Delta and Alpha4. Our results also show that fully vaccinated and boosted individuals, when infected, can shed infectious SARS-CoV-2 via exhaled breath aerosols. These findings provide additional evidence that inhalation of infectious aerosols is the dominant mode of transmission and emphasize the importance of ventilation, filtration, and air disinfection to mitigate the pandemic and protect vulnerable populations. We anticipate that monitoring aerosol shedding from new SARS-CoV-2 variants and emerging pathogens will be an important component of future threat assessments and will help guide interventions to prevent transmission via inhalation exposure.

Comparison of Saliva and Mid-Turbinate Swabs for Detection of COVID-19 (preprint)

Background: Saliva is an attractive sample for detecting SARS-CoV-2 because it is easy to collect and minimally invasive. However, contradictory reports exist concerning the sensitivity of saliva versus nasal swabs. Methods: We recruited and followed close contacts of COVID-19 cases for up to 14 days from their last exposure and collected self-reported symptoms, mid-turbinate swabs (MTS) and saliva every two or three days. Ct values and frequency of viral detection by MTS and saliva were compared. Logistic regression was used to estimate the probability of detection by days since symptom onset for the two sample types. Results: We enrolled 58 contacts who provided a total of 200 saliva and MTS sample pairs; 14 contacts (13 with symptoms) had one or more positive samples. Overall, saliva and MTS had similar rates of viral detection (p=0.78). Although Ct values for saliva were significantly greater than for MTS (p=0.014), Cohen's Kappa demonstrated substantial agreement ({kappa}=0.83). However, sensitivity varied significantly with time relative to symptom onset. Early in the course of infection (days -3 to 2), saliva had 12 times (95%CI: 1.2, 130) greater likelihood of detecting viral RNA compared to MTS. After day 2, there was a non-significant trend to greater sensitivity using MTS samples. Conclusion: Saliva and MTS specimens demonstrated high agreement, making saliva a suitable alternative to MTS nasal swabs for COVID-19 detection. Furthermore, saliva was more sensitive than MTS early in the course of infection, suggesting that it may be a superior and cost-effective screening tool for COVID-19.

Infectious SARS-CoV-2 in Exhaled Aerosols and Efficacy of Masks During Early Mild Infection (preprint)

BackgroundSARS-CoV-2 epidemiology implicates airborne transmission; aerosol infectiousness and impacts of masks and variants on aerosol shedding are not well understood. MethodsWe recruited COVID-19 cases to give blood, saliva, mid-turbinate and fomite (phone) swabs, and 30-minute breath samples while vocalizing into a Gesundheit-II, with and without masks at up to two visits two days apart. We quantified and sequenced viral RNA, cultured virus, and assayed sera for anti-spike and anti-receptor binding domain antibodies. ResultsWe enrolled 49 seronegative cases (mean days post onset 3.8 {+/-}2.1), May 2020 through April 2021. We detected SARS-CoV-2 RNA in 45% of fine ([≤]5 {micro}m), 31% of coarse (>5 {micro}m) aerosols, and 65% of fomite samples overall and in all samples from four alpha-variant cases. Masks reduced viral RNA by 48% (95% confidence interval [CI], 3 to 72%) in fine and by 77% (95% CI, 51 to 89%) in coarse aerosols; cloth and surgical masks were not significantly different. The alpha variant was associated with a 43-fold (95% CI, 6.6 to 280-fold) increase in fine aerosol viral RNA, compared with earlier viruses, that remained a significant 18-fold (95% CI, 3.4 to 92-fold) increase adjusting for viral RNA in saliva, swabs, and other potential confounders. Two fine aerosol samples, collected while participants wore masks, were culture-positive. ConclusionSARS-CoV-2 is evolving toward more efficient aerosol generation and loose-fitting masks provide significant but only modest source control. Therefore, until vaccination rates are very high, continued layered controls and tight-fitting masks and respirators will be necessary. Key PointsO_LICases exhale infectious viral aerosols C_LIO_LISARS-CoV-2 evolution favors more efficient aerosol generation. C_LIO_LILoose-fitting masks moderately reduce viral RNA aerosol. C_LIO_LIVentilation, filtration, UV air sanitation, and tight-fitting masks are needed to protect vulnerable people in public-facing jobs and indoor spaces. C_LI

Viral Load of SARS-CoV-2 in Respiratory Aerosols Emitted by COVID-19 Patients while Breathing, Talking, and Singing (preprint)

Background: Multiple SARS-CoV-2 superspreading events suggest that aerosols play an important role in driving the COVID-19 pandemic. However, the detailed roles of coarse (>5m) and fine ([≤]5m) respiratory aerosols produced when breathing, talking, and singing are not well-understood. Methods: Using a G-II exhaled breath collector, we measured viral RNA in coarse and fine respiratory aerosols emitted by COVID-19 patients during 30 minutes of breathing, 15 minutes of talking, and 15 minutes of singing. Results: Among the 22 study participants, 13 (59%) emitted detectable levels of SARS-CoV-2 RNA in respiratory aerosols, including 3 asymptomatic patients and 1 presymptomatic patient. Viral loads ranged from 63 - 5,821 N gene copies per expiratory activity. Patients earlier in illness were more likely to emit detectable RNA, and loads differed significantly between breathing, talking, and singing. The largest proportion of SARS-CoV-2 RNA copies was emitted by singing (53%), followed by talking (41%) and breathing (6%). Overall, fine aerosols constituted 85% of the viral load detected in our study. Virus cultures were negative. Conclusions: Fine aerosols produced by talking and singing contain more SARS-CoV-2 copies than coarse aerosols and may play a significant role in the transmission of SARS-CoV-2. Exposure to fine aerosols should be mitigated, especially in indoor environments where airborne transmission of SARS-CoV-2 is likely to occur. Isolating viable SARS-CoV-2 from respiratory aerosol samples remains challenging, and whether this can be more easily accomplished for emerging SARS-CoV-2 variants is an important enquiry for future studies.

Analysis of SARS-CoV-2 Antibodies in COVID-19 Convalescent Plasma using a Coronavirus Antigen Microarray (preprint)

The current practice for diagnosis of COVID-19, based on SARS-CoV-2 PCR testing of pharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk, likely underestimates the true prevalence of infection. Serologic methods can more accurately estimate the disease burden by detecting infections missed by the limited testing performed to date. Here, we describe the validation of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A comparison of antibody profiles detected on the array from control sera collected prior to the SARS-CoV-2 pandemic versus convalescent blood specimens from virologically confirmed COVID-19 cases demonstrates near complete discrimination of these two groups, with improved performance from use of antigen combinations that include both spike protein and nucleoprotein. This array can be used as a diagnostic tool, as an epidemiologic tool to more accurately estimate the disease burden of COVID-19, and as a research tool to correlate antibody responses with clinical outcomes.

Detection of Air and Surface Contamination by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Hospital Rooms of Infected Patients (preprint)

Understanding the particle size distribution in the air and patterns of environmental contamination of SARS-CoV-2 is essential for infection prevention policies. We aimed to detect SARS-CoV-2 surface and air contamination and study associated patient-level factors. 245 surface samples were collected from 30 airborne infection isolation rooms of COVID-19 patients, and air sampling was conducted in 3 rooms. Air sampling detected SARS-CoV-2 PCR-positive particles of sizes >4 m and 1-4 m in two rooms, which warrants further study of the airborne transmission potential of SARS-CoV-2. 56.7% of rooms had at least one environmental surface contaminated. High touch surface contamination was shown in ten (66.7%) out of 15 patients in the first week of illness, and three (20%) beyond the first week of illness (p = 0.01).

Analysis of Serologic Cross-Reactivity Between Common Human Coronaviruses and SARS-CoV-2 Using Coronavirus Antigen Microarray (preprint)

The current practice for diagnosis of SARS-CoV-2 infection relies on PCR testing of nasopharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk. This testing strategy likely underestimates the true prevalence of infection, creating the need for serologic methods to detect infections missed by the limited testing to date. Here, we describe the development of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A preliminary study of human sera collected prior to the SARS-CoV-2 pandemic demonstrates overall high IgG reactivity to common human coronaviruses and low IgG reactivity to epidemic coronaviruses including SARS-CoV-2, with some cross-reactivity of conserved antigenic domains including S2 domain of spike protein and nucleocapsid protein. This array can be used to answer outstanding questions regarding SARS-CoV-2 infection, including whether baseline serology for other coronaviruses impacts disease course, how the antibody response to infection develops over time, and what antigens would be optimal for vaccine development.

Respiratory Virus Shedding in Exhaled Breath and Efficacy of Face Masks (preprint)

There are few studies describing the presence of respiratory viruses in respiratory droplets and aerosols in the exhaled breath of infected persons, and the efficacy of facemasks as a source control to prevent respiratory virus transmission. Here, we recruited children and adults with acute respiratory illness and collected respiratory droplets and aerosols, with and without surgical facemasks. We identified human coronaviruses, influenza virus and rhinovirus from both respiratory droplets and aerosols. Surgical face masks reduced detection of coronavirus RNA in both respiratory droplets and aerosols, but only respiratory droplets and not aerosols for influenza virus RNA. Our results provide mechanistic evidence that surgical facemasks could prevent transmission of human coronavirus and influenza virus infections if worn by symptomatic individuals.Authors Donald K Milton and Benjamin J Cowling are joint senior authors.