stimulate revision of the science in the light of current evidence. Six 'myths' are presented, explained and ultimately refuted on the basis of recently published papers and expert opinion from previous work related to similar viruses. There is little doubt that SARS-CoV-2 is transmitted via a range of airborne particle sizes subject to all the usual ventilation parameters and human behaviour. Experts from specialties encompassing aerosol studies, ventilation, engineering, physics, virology and clinical medicine have joined together to produce this review to consolidate the evidence for airborne transmission mechanisms, and offer justification for modern strategies for prevention and control of COVID-19 in health care and the community.

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Building ventilation systems must get much better

Various organizations and societies around the globe have issued guidelines in response to the coronavirus disease (COVID-19) and virus (SARS-CoV-2). In this paper, heating, ventilating, and air-conditioning-related guidelines or documents in several major countries and regions have been reviewed and compared, including those issued by the American Society of Heating Refrigerating and Air-Conditioning Engineers, the Federation of European Heating, Ventilation, and Air Conditioning Associations, the Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, Architectural Society of China, and the Chinese Institute of Refrigeration. Most terms and suggestions in these guidelines are consistent with each other, although there are some conflicting details, reflecting the underlying uncertainty surrounding the transmission mechanism and characteristics of COVID-19 in buildings. All guidelines emphasize the importance of ventilation, but the specific ventilation rate that can eliminate the risk of transmission of airborne particulate matter has not been established. The most important countermeasure, commonly agreed countermeasures, the conflicting content from different guidelines, and further work have been summarized in this paper.

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Diverse control measures can be applied to reduce tuberculosis infection risk in health‐care facilities. Selecting optimal controls requires methods for predicting the dependence of infections risk on underlying parameters. A common model for infection risk only explicitly accounts for control by ventilation. This paper proposes a more complete model for evaluating tuberculosis infection control methods in health‐care settings. An infection risk parameter is defined as the probable number of infectious droplet nuclei inhaled by all susceptible persons from a single infectious person. Algebraic model equations are presented for two exposure cases. In one, the susceptible and infectious persons are together in a well‐mixed indoor environment; in the socond, the infectious person is in respiratory isolation. Model equations are used to explore many common tuberculosis control measures: identification, isolation and treatment of tuberculosis cases; surgical masks and treatment booths applied at the source; environmental controls such as ventilation, air filtration, and ultraviolet germicidal irradiation; and respiratory protection for susceptible persons. Experimental data are limited or lacking on some key variables, such as emissions of infectious droplet nuclei by contagious persons and air leakage rates from isolation rooms. Methods are outlined for collecting additional data.

Some infectious diseases, including COVID-19, can be transmitted via aerosols that are emitted by an infectious person and inhaled by susceptible individuals. Although physical distancing effectively reduces short-range airborne transmission, many infections have occurred when sharing room air despite maintaining distancing. We propose two simple parameters as indicators of infection risk for this situation. They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and air cleaning rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend in relation to these parameters that is consistent with an airborne infection model, supporting the importance of airborne transmission for these outbreaks. The observed trends of outbreak size vs. risk parameters allow us to recommend values of the parameters to minimize COVID-19 indoor infection risk. All of the pre-pandemic spaces are in a regime where they are highly sensitive to mitigation efforts. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at much higher risk parameter values. Since both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include ventilation information, to allow expanding our knowledge of the circumstances conducive to airborne transmission of different diseases.

During the 2020 COVID-19 pandemic, an outbreak occurred following attendance of a symptomatic index case at a regular weekly rehearsal on 10 March of the Skagit Valley Chorale (SVC). After that rehearsal, 53 members of the SVC among 61 in attendance were confirmed or strongly suspected to have contracted COVID-19 and two died. Transmission by the airborne route is likely. It is vital to identify features of cases such as this so as to better understand the factors that promote superspreading events. Based on a conditional assumption that transmission during this outbreak was by inhalation of respiratory aerosol, we use the available evidence to infer the emission rate of airborne infectious quanta from the primary source. We also explore how the risk of infection would vary with several influential factors: the rates of removal of respiratory aerosol by ventilation; deposition onto surfaces; and viral decay. The results indicate an emission rate of the order of a thousand quanta per hour (mean [interquartile range] for this event = 970 [680-1190] quanta per hour) and demonstrate that the risk of infection is modulated by ventilation conditions, occupant density, and duration of shared presence with an infectious individual.