A web-based system developed by British academic researchers was unveiled Wednesday that illustrates, in simple graphical form, how much various mitigation measures reduce the risk of SARS-CoV-2 transmission in different situations.
The system depicts two people, one infected on the left, and one uninfected on the right. Connecting them are shaded arrows representing different potential transmission routes, with the depth of shading indicating the relative importance of each possible route in the risk to the uninfected person. A host of relevant parameters (e.g., type of activity, protective gear, room factors) can be adjusted to reflect the circumstances under which these individuals might interact in real life.
A brief explanation of the background, methods, and goals appeared in The BMJ, with Harry Rutter, MSc, of the University of Bath in England, as lead author. An accompanying BMJ Open paper by the same group described the process for developing the system in more detail.
The main point, Rutter and colleagues suggested, was to develop a system incorporating expert knowledge on viral transmission into an easily understood format.
"To make informed decisions, whether about COVID or anything else, everyone -- from members of the public to policy makers -- needs access to easily understandable, relevant descriptions of the best evidence available," the group explained.
"[T]here have been few attempts to collate and communicate the multiple factors that determine transmission," they continued, "or to illustrate them in a way that systematically represents how different variables are contingent on one another."
In seeking to fill this gap, Rutter and colleagues recruited 27 researchers and scholars with expertise in virus transmission, and examined the published literature on such matters as the effectiveness of different kinds of masks, hand-washing, transmission risks as related to various airborne particle sizes, and so on. This process yielded numerical estimates -- admittedly, with wide confidence intervals -- of the increases in likelihood of SARS-CoV-2 transmission when, for example, an infected person converses with an uninfected individual versus merely sharing the same space in silence.
These numerical estimates were then translated into the continuous shading system employed in the interactive graphic. Transmission routes included small aerosols and small and large droplets that could be breathed in; droplets that could be absorbed through the eyes, nose, or mouth; and hand-to-hand and hand-to-surface-to-hand transfer, with viral particles ultimately reaching mucous membranes.
With 15 adjustable parameters, the system can examine more than 1 million different scenarios.
The most important, according to MedPage Today's brief test-drive, appeared to be the type of activity people engaged in (speaking normally, shouting, singing, exercising, coughing, eating, or silence); use of facial protection and what kind (six total, and who is wearing it); room size (small, large, outdoor); and the presence of room ventilation. Those, of course, are the main factors governing airborne transmission.
By the same token, there seemed to be no scenario in which surface contamination posed a significant risk.
Nevertheless, in a press statement, Rutter commented that "[i]t is all too easy to focus on just a single route of spread for COVID and forget about all the others. One of the ways a tool like this can help is by making it really clear that all the transmission routes matter, in different proportions in different contexts. The fact that one of those routes -- airborne transmission -- is the main one in most situations doesn't mean that we can ignore the others."
Some parameters that users can't adjust for include the infected person's viral load or stage of infection, as well as the particular SARS-CoV-2 variant involved. Both are associated with that person's risk of transmitting the virus to others. Of course, in everyday interactions, that would rarely be knowable, and often not in healthcare settings either.
Other limitations included the reliance on expert opinion for the tool's underlying algorithm, and the authors acknowledged that these opinions weren't always unanimous. Indeed, "[o]pinions concerning the role of aerosol transmission varied widely in the elicitation exercise, but we also found divergent views on several other variables, such as the amount of small particle inhalation at different room sizes; the effects of different kinds of masks on inhaled aerosols; and the effects of face coverings on transfer from hand to eyes, nose, and mouth," Rutter's group noted.