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The COVID-19 pandemic has given rise to numerous articles from differentscientific fields (epidemiology, virology, immunology, airflow physics...)without any effort to link these different insights. In this review, we aim toestablish relationships between epidemiological data and the characteristics ofthe virus strain responsible for the epidemic wave concerned. We have carriedout this study on the Wuhan, Alpha, Delta and Omicron strains allowing us toillustrate the evolution of the relationships we have highlighted according tothese different viral strains. We addressed the following questions: 1) How canthe mean infectious dose (one quantum, by definition in epidemiology) bemeasured and expressed as an amount of viral RNA molecules (in genome units,GU) or as a number of replicative viral particles (in plaque-forming units,PFU)? 2) How many infectious quanta are exhaled by an infected person per unitof time? 3) How many infectious quanta are exhaled, on average, integrated overthe whole contagious period? 4) How do these quantities relate to the epidemicreproduction rate R as measured in epidemiology, and to the viral load, asmeasured by molecular biological methods? 5) How has the infectious doseevolved with the different strains of SARS-CoV-2? We make use ofstate-of-the-art modelling, reviewed and explained in the appendix of thearticle (Supplemental Information, SI), to answer these questions using datafrom the literature in both epidemiology and virology. We have considered themodification of these relationships according to the vaccination status of thepopulation. We hope that this work will allow a better integration of data fromdifferent fields (virology, epidemiology, and immunology) to anticipate theevolution of the epidemic in the case of COVID-19, but also in respiratorypathologies transmissible in an airborne manner.

At the crossroads of epidemiology and biology: bridging the gap between SARS-CoV-2 viral strain properties and epidemic wave characteristics