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BackgroundAerosol inhalation is recognized as the dominant mode of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Three highly transmissible lineages evolved during the pandemic. One hypothesis to explain increased transmissibility is that natural selection favors variants with higher rates of viral aerosol shedding. However, the extent of aerosol shedding of successive SARS-CoV-2 variants is unknown. We aimed to measure the infectivity and rate of SARS-CoV-2 shedding into exhaled breath aerosol (EBA) by individuals during the Delta and Omicron waves and compared those rates with those of prior SARS-CoV-2 variants from our previously published work.MethodsIndividuals with coronavirus disease 2019 (COVID-19) (n = 93; 32 vaccinated and 20 boosted) were recruited to give samples, including 30-minute breath samples into a Gesundheit-II EBA sampler. Samples were quantified for viral RNA using reverse-transcription polymerase chain reaction and cultured for virus.ResultsAlpha (n = 4), Delta (n = 3), and Omicron (n = 29) cases shed significantly more viral RNA copies into EBAs than cases infected with ancestral strains and variants not associated with increased transmissibility (n = 57). All Delta and Omicron cases were fully vaccinated and most Omicron cases were boosted. We cultured virus from the EBA of 1 boosted and 3 fully vaccinated cases.ConclusionsAlpha, Delta, and Omicron independently evolved high viral aerosol shedding phenotypes, demonstrating convergent evolution. Vaccinated and boosted cases can shed infectious SARS-CoV-2 via EBA. These findings support a dominant role of infectious aerosols in transmission of SARS-CoV-2. Monitoring aerosol shedding from new variants and emerging pathogens can be an important component of future threat assessments and guide interventions to prevent transmission.

This is an account that should be heard of an important struggle: the struggle of a large group of experts who came together at the beginning of the COVID-19 pandemic to warn the world about the risk of airborne transmission and the consequences of ignoring it. We alerted the World Health Organization about the potential significance of the airborne transmission of SARS-CoV-2 and the urgent need to control it, but our concerns were dismissed. Here we describe how this happened and the consequences. We hope that by reporting this story we can raise awareness of the importance of interdisciplinary collaboration and the need to be open to new evidence, and to prevent it from happening again. Acknowledgement of an issue, and the emergence of new evidence related to it, is the first necessary step towards finding effective mitigation solutions.

Policies to prevent respiratory virus transmission in health care settings have traditionally divided organisms into Droplet versus Airborne categories. Droplet organisms (for example, influenza) are said to be transmitted via large respiratory secretions that rapidly fall to the ground within 1 to 2 meters and are adequately blocked by surgical masks. Airborne pathogens (for example, measles), by contrast, are transmitted by aerosols that are small enough and light enough to carry beyond 2 meters and to penetrate the gaps between masks and faces; health care workers are advised to wear N95 respirators and to place these patients in negative-pressure rooms. Respirators and negative-pressure rooms are also recommended when caring for patients with influenza or SARS-CoV-2 who are undergoing "aerosol-generating procedures," such as intubation. An increasing body of evidence, however, questions this framework. People routinely emit respiratory particles in a range of sizes, but most are aerosols, and most procedures do not generate meaningfully more aerosols than ordinary breathing, and far fewer than coughing, exercise, or labored breathing. Most transmission nonetheless occurs at close range because virus-laden aerosols are most concentrated at the source; they then diffuse and dilute with distance, making long-distance transmission rare in well-ventilated spaces. The primary risk factors for nosocomial transmission are community incidence rates, viral load, symptoms, proximity, duration of exposure, and poor ventilation. Failure to appreciate these factors may lead to underappreciation of some risks (for example, overestimation of the protection provided by medical masks, insufficient attention to ventilation) or misallocation of limited resources (for example, reserving N95 respirators and negative-pressure rooms only for aerosol-generating procedures or requiring negative-pressure rooms for all patients with SARS-CoV-2 infection regardless of stage of illness). Enhanced understanding of the factors governing respiratory pathogen transmission may inform the development of more effective policies to prevent nosocomial transmission of respiratory pathogens.

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemiology implicates airborne transmission; aerosol infectiousness and impacts of masks and variants on aerosol shedding are not well understood. Methods We recruited coronavirus disease 2019 (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 2 visits 2 days apart. We quantified and sequenced viral RNA, cultured virus, and assayed serum samples for anti-spike and anti-receptor binding domain antibodies. Results We enrolled 49 seronegative cases (mean days post onset 3.8 ± 2.1), May 2020 through April 2021. We detected SARS-CoV-2 RNA in 36% of fine (≤5 µm), 26% of coarse (>5 µm) aerosols, and 52% of fomite samples overall and in all samples from 4 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. Conclusions SARS-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.

Acute respiratory infections (ARI) are infectious diseases of the respiratory tract caused by viruses, bacteria, and atypical bacteria. They range in severity and even mild cases may cause a significant reduction in workplace productivity. ARIs commonly occur in outbreaks and disproportionally impact workers in occupations where workers are in close proximity to co-workers, members of the public, or where they reside in densely populated housing. High-risk workers include those in the healthcare sector, protective service, food and meat processing, service, and education industries. A person can become infected by inhaling virus-laden aerosols, having virus-contaminated sprayborne drops impinge on exposed mucous membranes, and touching contaminated surfaces followed by self-inoculation. More than one transfer process may be involved in the transmission, and the dominant route may differ for different causative agents, environments, and activity patterns. Preventing ARI transmission in the workplace must be holistic in approach and begin with anticipation and recognition of potential risks, reinforced by the continuous evaluation and implementation of control strategies. Control measures should be layered and multiple routes of transmission should be addressed. Controls should be adapted to the specific workplace and the ARI to prevent pathogen introduction, rapidly detect cases, and promptly eliminate exposure. Prevention and control can be accomplished by promoting vaccination, improving ventilation and air cleaning, providing paid sick leave, flexible working conditions, and work-from-home options. Promoting hand sanitation and providing appropriate personal protective equipment are important but never sufficient in isolation. Occupational health professionals should partner with workplace engineers and human resource departments to design effective programs.

Background Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) superspreading events suggest that aerosols play an important role in driving the coronavirus disease 2019 (COVID-19) pandemic. To better understand how airborne SARS-CoV-2 transmission occurs, we sought to determine viral loads within coarse (>5 μm) and fine (≤5 μm) respiratory aerosols produced when breathing, talking, and singing. 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 Thirteen participants (59%) emitted detectable levels of SARS-CoV-2 RNA in respiratory aerosols, including 3 asymptomatic and 1 presymptomatic patient. Viral loads ranged from 63–5821 N gene copies per expiratory activity per participant, with high person-to-person variation. Patients earlier in illness were more likely to emit detectable RNA. Two participants, sampled on day 3 of illness, accounted for 52% of total viral load. Overall, 94% of SARS-CoV-2 RNA copies were emitted by talking and singing. Interestingly, 7 participants emitted more virus from talking than singing. 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 SARS-CoV-2 transmission. Exposure to fine aerosols, especially indoors, should be mitigated. Isolating viable SARS-CoV-2 from respiratory aerosol samples remains challenging; whether this can be more easily accomplished for emerging SARS-CoV-2 variants is an urgent enquiry necessitating larger-scale studies.

Outbreaks from choir performances, such as the Skagit Valley Choir, showed that singing brings potential risk of COVID-19 infection. There is less known about the risks of airborne infection from other musical performances, such as playing wind instruments or performing theater. In addition, it is important to understand methods that can be used to reduce infection risk. In this study, we used a variety of methods, including flow visualization, aerosol and CO2 measurements, and computational fluid dynamics (CFD) modeling to understand the different components that can lead to transmission risk from musical performance and risk mitigation. This study was possible because of a partnership across academic departments and institutions and collaboration with the National Federation of State High School Associations and the College Band Directors National Association. The interdisciplinary team enabled us to understand the various aspects of aerosol transmission risk from musical performance and to quickly implement strategies in music classrooms during the COVID-19 pandemic. We found that plumes from musical performance were highly directional, unsteady and varied considerably in time and space. Aerosol number concentration measured at the bell of the clarinet was comparable to that of singing. Face and bell masks attenuated plume velocities and lengths and decreased aerosol concentrations measured in front of the masks. CFD modeling showed differences between indoor and outdoor environments and that the lowest risk of airborne COVID-19 infection occurred at less than 30 min of exposure indoors and less than 60 min outdoors.

Aerosol inhalation is recognized as the dominant mode of SARS-CoV-2 transmission. Three highly transmissible lineages evolved during the pandemic. One hypothesis to explain increased transmissibility is that natural selection favors variants with higher rates of viral aerosol shedding. However, the extent of aerosol shedding of successive SARS-CoV-2 variants is unknown. We aimed to measure the infectivity and rate of SARS-CoV-2 shedding into exhaled breath aerosol (EBA) by individuals during the Delta and Omicron waves and compared those rates with those of prior SARS-CoV-2 variants from our previously published work.COVID-19 cases (n = 93, 32 vaccinated and 20 boosted) were recruited to give samples, including 30-minute breath samples into a Gesundheit-II exhaled breath aerosol sampler. Samples were quantified for viral RNA using RT-PCR and cultured for virus.Alpha (n = 4), Delta (n = 3), and Omicron (n = 29) cases shed significantly more viral RNA copies into exhaled breath aerosols than cases infected with ancestral strains and variants not associated with increased transmissibility (n = 57). All Delta and Omicron cases were fully vaccinated and most Omicron cases were boosted. We cultured virus from the EBA of one boosted and three fully vaccinated cases.Alpha, Delta, and Omicron independently evolved high viral aerosol shedding phenotypes, demonstrating convergent evolution. Vaccinated and boosted cases can shed infectious SARS-CoV-2 via EBA. These findings support a dominant role of infectious aerosols in transmission of SARS-CoV-2. Monitoring aerosol shedding from new variants and emerging pathogens can be an important component of future threat assessments and guide interventions to prevent transmission.

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.

The exhalation of aerosols during musical performances or rehearsals posed a risk of airborne virus transmission in the COVID-19 pandemic. Previous research studied aerosol plumes by only focusing on one risk factor, either the source strength or convective transport capability. Furthermore, the source strength was characterized by the aerosol concentration and ignored the airflow rate needed for risk analysis in actual musical performances. This study characterizes aerosol plumes that account for both the source strength and convective transport capability by conducting experiments with 18 human subjects. The source strength was characterized by the source aerosol emission rate, defined as the source aerosol concentration multiplied by the source airflow rate (brass 383 particle/s, singing 408 particle/s, and woodwind 480 particle/s). The convective transport capability was characterized by the plume influence distance, defined as the sum of the horizontal jet length and horizontal instrument length (brass 0.6 m, singing 0.6 m and woodwind 0.8 m). Results indicate that woodwind instruments produced the highest risk with approximately 20% higher source aerosol emission rates and 30% higher plume influence distances compared with the average of the same risk indicators for singing and brass instruments. Interestingly, the clarinet performance produced moderate source aerosol concentrations at the instrument's bell, but had the highest source aerosol emission rates due to high source airflow rates. Flute performance generated plumes with the lowest source aerosol emission rates but the highest plume influence distances due to the highest source airflow rate. Notably, these comprehensive results show that the source airflow is a critical component of the risk of airborne disease transmission. The effectiveness of masking and bell covering in reducing aerosol transmission is due to the mitigation of both source aerosol concentrations and plume influence distances. This study also found a musician who generated approximately five times more source aerosol concentrations than those of the other musicians who played the same instrument. Despite voice and brass instruments producing measurably lower average risk, it is possible to have an individual musician produce aerosol plumes with high source strength, resulting in enhanced transmission risk; however, our sample size was too small to make generalizable conclusions regarding the broad musician population.

Link prediction is a fundamental problem in network analysis. In a complex network, links can be unreported and/or under detection limits due to heterogeneous sources of noise and technical challenges during data collection. The incomplete network data can lead to an inaccurate inference of network based data analysis. We propose a parametric link prediction model and consider latent links as misclassified binary outcomes. We develop new algorithms to optimize model parameters and yield robust predictions of unobserved links. Theoretical properties of the predictive model are also discussed. We apply the new method to a partially observed social network data and incomplete brain network data. The results demonstrate that our method outperforms the existing latent-link prediction methods.

Saliva is an attractive sample for detecting SARS-CoV-2. However, contradictory reports exist concerning the sensitivity of saliva versus nasal swabs. We followed close contacts of COVID-19 cases for up to 14 days from the last exposure and collected self-reported symptoms, midturbinate swabs (MTS), and saliva every 2 or 3 days. Ct values, viral load, and frequency of viral detection by MTS and saliva were compared. Fifty-eight contacts provided 200 saliva-MTS pairs, and 14 contacts (13 with symptoms) had one or more positive samples. Saliva and MTS had similar rates of viral detection (

From December 16 through 21 of 2021, we collected exhaled breath aerosol (EBA) from five members of a University campus community infected with SARS-CoV-2 viruses displaying an S-gene target failure when assayed using the TaqPath COVID-19 Real Time PCR Assay (Thermo Scientific).

Despite evidence that airborne transmission contributes to influenza epidemics, limited knowledge of the infectiousness of human influenza cases hinders pandemic preparedness. We used airborne viral source strength and indoor CO2 monitoring from the largest human influenza challenge‐transmission trial (EMIT: Evaluating Modes of Influenza Transmission, ClinicalTrials.gov number NCT01710111) to compute an airborne infectious dose generation rate q = 0.11 (95% CI 0.088, 0.12)/h and calculate the quantity of airborne virus per infectious dose σ = 1.4E + 5 RNA copies/quantum (95% CI 9.9E + 4, 1.8E + 5). We then compared these calculated values to available data on influenza airborne infectious dose from several previous studies, and applied the values to dormitory room environments to predict probability of transmission between roommates. Transmission risk from typical, moderately to severely symptomatic influenza cases is dramatically decreased by exposure reduction via increasing indoor air ventilation. The minority of cases who shed the most virus (ie, supershedders) may pose great risk even in well‐ventilated spaces. Our modeling method and estimated infectiousness provide a ground work for (a) epidemiologic studies of transmission in non‐experimental settings and (b) evaluation of the extent to which airborne exposure control strategies could limit transmission risk.

We identified seasonal human coronaviruses, influenza viruses and rhinoviruses in exhaled breath and coughs of children and adults with acute respiratory illness. Surgical face masks significantly reduced detection of influenza virus RNA in respiratory droplets and coronavirus RNA in aerosols, with a trend toward reduced detection of coronavirus RNA in respiratory droplets. Our results indicate that surgical face masks could prevent transmission of human coronaviruses and influenza viruses from symptomatic individuals.

Pulmonary infections are important causes of global morbidity and mortality, but diagnostics are often limited by the ability to collect specimens easily, safely, and in a cost-effective manner. We review recent advances in the collection of infectious aerosols from patients with TB and with influenza. Although this research has been focused on assessing the infectious potential of such patients, we propose that these methods have the potential to lead to the use of patient-generated microbial aerosols as noninvasive diagnostic tests of disease and tests of infectiousness.

A consensus statement from physicians and scientists with a range of expertise in the areas of respiratory infection and aerosols, to clarify the discussion surrounding a recent preprint (https://www.medrxiv.org/content/10.1101/2022.01.08.22268944v1) describing the aerosol dynamics of SARS-CoV-2 (the virus that causes COVID-19) which generated controversy in mainstream and social media and among infection prevention and control specialists. The study by Oswin et al. is complex and, as such, easily misinterpreted. It must be understood in the context provided by studies of human aerosol emission rates and viral loads in exhaled breath of infected persons, air movement and aerosol transport indoors, previous studies of airborne survival, and epidemiologic studies and outbreak investigations.

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.

There is great disparity in the way we think about and address different sources of environmental infection. Governments have for decades promulgated a large amount of legislation and invested heavily in food safety, sanitation, and drinking water for public health purposes. In contrast, airborne pathogens and respiratory infections, whether seasonal influenza or COVID-19, are ad-dressed fairly weakly, if at all, in terms of regulations, standards, and building design and operation, pertaining to the air we breathe. We suggest that the dramatic growth in our understanding of the mechanisms behind respiratory infection transmission should drive a paradigm shift in how we view and address the transmission of respiratory infections to protect present and future generations from unnecessary suffering and economic losses. It starts with a recognition that preventing respiratory infection, like reducing waterborne or food-borne disease, is a tractable problem. See Additional URL below for 'free to read' PDF reprint.

Eighteen months into the COVID-19 pandemic, and as the world struggles with global vaccine equity, emerging variants, and the reality that eradication is years away at soonest, we add to notion of “layered defenses” proposing a conceptual model for better understanding the differential applicability and effectiveness of precautions against SARS-CoV-2 transmission. The prevailing adaptation of Reason's Swiss cheese model conceives of all defensive layers as equally protective, when in reality some are more effective than others. Adapting the hierarchy of controls framework from occupational safety provides a better framework for understanding the relative benefit of different hazard control strategies to minimize the spread of SARS-CoV-2.

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 µm), 31% of coarse (>5 µm) 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 PointsCases exhale infectious viral aerosolsSARS-CoV-2 evolution favors more efficient aerosol generation.Loose-fitting masks moderately reduce viral RNA aerosol.Ventilation, filtration, UV air sanitation, and tight-fitting masks are needed to protect vulnerable people in public-facing jobs and indoor spaces.

We report the rapid detection of SARS-CoV-2 in infected patients (mid-turbinate swabs and exhaled breath aerosol samples) in concentrations as low as 60 copies/mL of the virus in seconds by electrical transduction of the SARS-CoV-2 S1 spike protein antigen via SARS-CoV-2 S1 spike protein antibodies immobilized on bilayer quasi-freestanding epitaxial graphene without gate or signal amplification. The sensor demonstrates the spike protein antigen detection in a concentration as low as 1 ag/mL. The heterostructure of the SARS-CoV-2 antibody/graphene-based sensor is developed through a simple and low-cost fabrication technique. Furthermore, sensors integrated into a portable testing unit distinguished B.1.1.7 variant positive samples from infected patients (mid-turbinate swabs and saliva samples, 4000-8000 copies/mL) with a response time of as fast as 0.6 s. The sensor is reusable, allowing for reimmobilization of the crosslinker and antibodies on the biosensor after desorption of biomarkers by NaCl solution or heat treatment above 40 °C.

BackgroundMultiple SARS-CoV-2 superspreading events suggest that aerosols play an important role in driving the COVID-19 pandemic. However, the detailed roles of coarse (>5μm) and fine (≤5μm) respiratory aerosols produced when breathing, talking, and singing are not well-understood.MethodsUsing 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.ResultsAmong 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 per patient. 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.ConclusionsFine 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.Key PointsWe sampled respiratory aerosols emitted by COVID-19 patients and discovered that fine aerosols (≤5μm) generated during talking and singing contain more SARS-CoV-2 copies than coarse aerosols (>5μm) and may play a significant role in the transmission of SARS-CoV-2.

With the increasing availability and dropping cost of high-throughput technology in recent years, many-omics datasets have accumulated in the public domain. Combining multiple transcriptomic studies on related hypothesis via meta-analysis can improve statistical power and reproducibility over single studies. For differential expression (DE) analysis, biomarker categorization by DE pattern across studies is a natural but critical task following biomarker detection to help explain between study heterogeneity and classify biomarkers into categories with potentially related functionality. In this paper, we propose a novel meta-analysis method to categorize biomarkers by simultaneously considering the concordant pattern and the biological and statistical significance across studies. Biomarkers with the same DE pattern can be analyzed together in downstream pathway enrichment analysis. In the presence of different types of transcripts (e.g., mRNA, miRNA, and lncRNA, etc.), integrative analysis including miRNA/lncRNA target enrichment analysis and miRNA-mRNA and lncRNA-mRNA causal regulatory network analysis can be conducted jointly on all the transcripts of the same category. We applied our method to two Pan-cancer transcriptomic study examples with single or multiple types of transcripts available. Targeted downstream analysis identified categories of biomarkers with unique functionality and regulatory relationships that motivate new hypothesis in Pan-cancer analysis.

Influenza within-host viral populations are the source of all global influenza diversity and play an important role in driving the evolution and escape of the influenza virus from human immune responses, antiviral treatment, and vaccines, and have been used in precision tracking of influenza transmission chains. Next Generation Sequencing (NGS) has greatly improved our ability to study these populations, however, major challenges remain, such as accurate identification of intra-host single nucleotide variants (iSNVs) that represent within-host viral diversity of influenza virus. In order to investigate the sources and the frequency of called iSNVs in influenza samples, we used a set of longitudinal influenza patient samples collected within a University of Maryland (UMD) cohort of college students in a living learning community. Our results indicate that technical replicates aid in removal of random RT-PCR, PCR, and platform sequencing errors, while the use of clonal plasmids for removal of systematic errors is more important in samples of low RNA abundance. We show that the choice of reference for read mapping affects the frequency of called iSNVs, with the sample self-reference resulting in the lowest amount of iSNV noise. The importance of variant caller choice is also highlighted in our study, as we observe differential sensitivity of variant callers to the mapping reference choice, as well as the poor overlap of their called iSNVs. Based on this, we develop an approach for identification of highly probable iSNVs by removal of sequencing and bioinformatics algorithm-associated errors, which we implement in phylogenetic analyses of the UMD samples for a greater resolution of transmission links. In addition to identifying closely related transmission connections supported by the presence of highly confident shared iSNVs between patients, our results also indicate that the rate of minor variant turnover within a host may be a limiting factor for utilization of iSNVs to determine patient epidemiological links.

Evaluation of population‐based COVID‐19 control measures informs strategies to quell the current pandemic and reduce the impact of those yet to come. Effective COVID‐19 control measures may simultaneously reduce the incidence of other acute respiratory infections (ARIs) due to shared transmission modalities. To assess the impact of stay‐at‐home orders and other physical distancing measures on the prevalence of ARI‐related symptoms, we compared symptoms reported by prospective college cohorts enrolled during two consecutive academic years. ARI‐related symptoms declined following campus closure and implementation of stay‐at‐home orders, demonstrating the impact of population‐based physical distancing measures on control of a broad range of respiratory infections.

Mobile phones are among the most highly touched personal objects. As part of a broader study on the contribution of fomites to influenza transmission, between 2017 and 2019, we swabbed mobile phones from 138 patients with influenza in 2 locations. Influenza viral RNA detection rates were 23% (23 of 99 phones) and 36% (14 of 39) in Hong Kong and Maryland, respectively. In Hong Kong, infectious influenza virus was recovered from 3 of 23 mobile phones which had influenza viral RNA detected. Mobile phone influenza contamination was positively associated with upper respiratory tract viral load and negatively associated with age. Cleaning personal objects of patients with influenza should be recommended, and individuals should avoid sharing objects with these patients.

The question of whether SARS-CoV-2 is transmitted by droplets or aerosols has been very controversial. We sought to explain this controversy through a historical analysis of transmission research in other diseases. For most of human history, many diseases were thought to transmit through the air, often over long distances and in a phantasmagorical way, and often in error (e.g. malaria, cholera). Building on the germ theory of disease developed in the mid 19th century and on the demise of miasma theory, prominent public health official Charles Chapin in 1910 urged the public health community to focus on contact and droplet infection. However, he introduced a major error in the process: that ease of infection in close proximity is associated exclusively with large “sprayborne” droplets that fall to the ground quickly, and he deemed airborne transmission as very unlikely. This new paradigm became dominant, leading to systematic errors in the interpretation of research evidence on transmission. For the next five decades, no disease was accepted by the general medical and infection control communities as airborne, until tuberculosis (which had been misclassified as droplet) in 1962. Chapin’s paradigm remained dominant and only a few diseases were widely accepted as transmitted by aerosols before COVID-19: those that were clearly transmitted over long distances or time scales. Resistance to the idea of airborne spread of a respiratory infection is not new. In fact, it has occurred repeatedly over much of the last century and greatly hampered understanding of how diseases transmit.

Motivation The analysis of gene co-expression network (GCN) is critical in examining the gene-gene interactions and learning the underlying complex yet highly organized gene regulatory mechanisms. Numerous clustering methods have been developed to detect communities of co-expressed genes in the large network. The assumed independent community structure, however, can be oversimplified and may not adequately characterize the complex biological processes. Results We develop a new computational package to extract interconnected communities from gene co-expression network. We consider a pair of communities be interconnected if a subset of genes from one community is correlated with a subset of genes from another community. The interconnected community structure is more flexible and provides a better fit to the empirical co-expression matrix. To overcome the computational challenges, we develop efficient algorithms by leveraging advanced graph norm shrinkage approach. We validate and show the advantage of our method by extensive simulation studies. We then apply our interconnected community detection method to an RNA-seq data from The Cancer Genome Atlas (TCGA) Acute Myeloid Leukemia (AML) study and identify essential interacting biological pathways related to the immune evasion mechanism of tumor cells. Availabilityand implementation The software is available at Github: https://github.com/qwu1221/ICN and Figshare: https://figshare.com/articles/software/ICN-package/13229093. Supplementary information Supplementary data are available at Bioinformatics online.

During the rapid rise in COVID-19 illnesses and deaths globally, and notwithstanding recommended precautions, questions are voiced about routes of transmission for this pandemic disease. Inhaling small airborne droplets is probable as a third route of infection, in addition to more widely recognized transmission via larger respiratory droplets and direct contact with infected people or contaminated surfaces. While uncertainties remain regarding the relative contributions of the different transmission pathways, we argue that existing evidence is sufficiently strong to warrant engineering controls targeting airborne transmission as part of an overall strategy to limit infection risk indoors. Appropriate building engineering controls include sufficient and effective ventilation, possibly enhanced by particle filtration and air disinfection, avoiding air recirculation and avoiding overcrowding. Often, such measures can be easily implemented and without much cost, but if only they are recognised as significant in contributing to infection control goals. We believe that the use of engineering controls in public buildings, including hospitals, shops, offices, schools, kindergartens, libraries, restaurants, cruise ships, elevators, conference rooms or public transport, in parallel with effective application of other controls (including isolation and quarantine, social distancing and hand hygiene), would be an additional important measure globally to reduce the likelihood of transmission and thereby protect healthcare workers, patients and the general public.

The following scientists reviewed the document: Jonathan Abbatt, John Adgate, Alireza Afshari, KangHo Ahn, Francis Allard, Joseph Allen, Celia Alves, Meinrat O. Andreae, Isabella Annesi-Maesano, Ahmet Arisoy, Andrew P. Ault, Gwi-Nam Bae, Gabriel Beko, Scott C. Bell, Allan Bertram, Mahmood Bhutta, Seweryn Bialasiewicz, Merete Bilde, Tami Bond, Joseph Brain, Marianna Brodach, David M. Broday, Guangyu Cao, Christopher D. Cappa, Annmarie Carlton, Paul K. S. Chan, Christopher Chao, Kuan-Fu Chen, Qi Chen, Qingyan Chen, David Cheong, Per Axcel Clausen, Ross Crawford, Derek Clements-Croome, Geo Clausen, Ian Clifton, Richard L. Corsi, Benjamin J. Cowling, Francesca Romana d'Ambrosio, Ghassan Dbaibo, Richard de Dear, Gianluigi de Gennaro, Peter DeCarlo, Philip Demokritou, Hugo Destaillats, Joanna Domagala-Kulawik, Neil M. Donahue, Caroline Duchaine, Marzenna R. Dudzinska, Dominic E. Dwyer, Greg Evans, Delphine K. Farmer, Kevin P. Fennelly, Richard Flagan, Janine Frohlich-Nowoisky, Manuel Gameiro da Silva, Christian George, Marianne Glasius, Allen H. Goldstein, Joao Gomes, Michael Gormley, Rafal Gorny, David Grimsrud, Keith Grimwood, Charles N. Haas, Fariborz Haghighat, Michael Hannigan, Roy Harrison, Ulla HaverinenShaughnessy, Philippa Howden-Chapman, Per Heiselberg, Daven K. Henze, Jean-Michel Heraud, Hartmut Herrmann, Philip K. Hopke, Ray Horstman, Wei Huang, Alex Huffman, David S. Hui, Tareq Hussein, Gabriel Isaacman-VanWertz, Jouni J.K. Jaakkola, Matti Jantunen, Lance Jennings, Dennis Johansson, Jan Kaczmarczyk, George Kallos, David Katoshevski, Frank Kelly, Soren Kjaergaard, Luke D. Knibbs, Henrik N. Knudsen, GwangPyo Ko, Evelyn S.C. Koay, Jen Kok, Nino Kuenzli, Markku Kulmala, Kazukiyo Kumagai, Prashant Kumar, Kazumichi Kuroda, Kiyoung Lee, Nelson Lee, Barry Lefer, Vincent Lemort, Xianting Li, Dusan Licina, Chao-Hsin Lin, Junjie Liu, Kam Lun E. Hon, John C. Little, Li Liu, Janet M. Macher, Ebba Malmqvist, Corinne Mandin, Ivo Martinac, Dainius Martuzevicius, Mark J. Mendell, David Miller, Claudia Mohr, Luisa T. Molina, Glenn Morrison, Roya Mortazavi, Edward Nardell, Athanasios Nenes, Mark Nicas, Zhi Ning, Jianlei Niu, Hidekazu Nishimura, Colin O'Dowd, Bjarne W. Olesen, Paula J. Olsiewski, Spyros Pandis, Daniel Peckham, Tuukka Petaja, Zbigniew Popiolek, Ulrich Poschl, Wayne R. Ott, Kimberly Prather, Andre S. H. Prevot, Hua Qian, Shanna Ratnesar-Shumate, James L. Repace, Tiina Reponen, Ilona Riipinen, Susan Roaf, Allen L. Robinson, Yinon Rudich, Manuel Ruiz de Adana, Masayuki Saijo, Reiko Saito, Paulo Saldiva, Tunga Salthammer, Joshua L. Santarpia, John H. Seinfeld, Gary S. Settles, Siegfried Schobesberger, Paul T. J. Scheepers, Max H. Sherman, Alan Shihadeh, Manabu Shiraiwa, Jeffrey Siegel, Torben Sigsgaard, Brett C. Singer, James N. Smith, Armin Sorooshian, Jerzy Sowa, Brent Stephens, Huey-Jen Jenny Su, Jordi Sunyer, Jason D. Surratt, Kazuo Takahashi, Nobuyuki Takegawa, Jorn Toftum, Margaret A. Tolbert, Euan Tovey, Barbara J. Turpin, Annele Virtanen, John Volckens, Claire Wainwright, Lance A. Wallace, Boguang Wang, Chia C. Wang, Michael Waring, John Wenger, Charles J. Weschler, Brent Williams, Mary E. Wilson, Armin Wisthaler, Kazimierz Wojtas, Douglas R. Worsnop, Ying Xu, Naomichi Yamamoto, Xudong Yang, Hui-Ling Yen, Hiroshi Yoshino, Hassan Zaraket, Zhiqiang (John) Zhai, Junfeng (Jim) Zhang, Qi Zhang, Jensen Zhang, Yinping Zhang, Bin Zhao, Tong Zhu.

Understanding the particle size distribution in the air and patterns of environmental contamination of SARS-CoV-2 is essential for infection prevention policies. Here we screen surface and air samples from hospital rooms of COVID-19 patients for SARS-CoV-2 RNA. Environmental sampling is conducted in three airborne infection isolation rooms (AIIRs) in the ICU and 27 AIIRs in the general ward. 245 surface samples are collected. 56.7% of rooms have at least one environmental surface contaminated. High touch surface contamination is 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, χ2 test). Air sampling is performed in three of the 27 AIIRs in the general ward, and detects SARS-CoV-2 PCR-positive particles of sizes >4 µm and 1–4 µm in two rooms, despite these rooms having 12 air changes per hour. This warrants further study of the airborne transmission potential of SARS-CoV-2.

In the version of this article initially published, in the first sentence of the third paragraph of the discussion, "for rhinovirus we detected virus in aerosols in 19 of 34 (56%) participants (compared to 4 of 10 (40%) for influenza and 8 of 23 (35%) for coronavirus)" should have read "for rhinovirus we detected virus in aerosols in 19 of 34 (56%) participants (compared to 4 of 10 (40%) for coronavirus and 8 of 23 (35%) for influenza)," with 'influenza' and 'coronavirus' transposed The error has been corrected in the HTML and PDF versions of the article Copyright © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc