Revisiting the Wells-Riley airborne infection model: A critical analysis of its use and misuse

Both probabilistic and deterministic models for prediction of infection transmission risk are potentially useful in understanding and controlling airborne infection transmission. The Wells-Riley model, developed by Edward Riley and colleagues, estimates infection transmission risk using the concept of quantum/quanta, proposed by Wells to circumvent the unknown factor of infectious dose. This model has been extensively used by researchers in recent years, and some have attempted to modify it to overcome its limitations and expand its applications. In some cases, however, researchers have misunderstood the concept of quanta and the mathematical requirements of the Wells-Riley model, leading to inappropriate uses and flawed modifications.

A quantum is defined as the unknown average number of infectious particles required to initiate an infection in a susceptible host. Although a quantum of infection can be one or more infectious particles, Wells clearly understood that inhaled infectious particles normally cause infection as if by a single particle that reaches its target and overcomes host defenses.

Since infection occurs as if by just one of an unknown number of infectious particles, integer values are used to count the number of quanta. This enabled Riley to derive the Wells-Riley model equation from a discrete probability distribution, representing the likelihood of inhaling at least one quantum. Revisiting these definitions in greater detail in this study enables an examination of the limitations of studies that have used or modified this model and provides valuable insights for future research.