Since the beginning of the COVID-19 pandemic, the concept of reproduction number (R) has become widely disseminated and used well outside the epidemiological community where it originated from. A lesser-known fact about reproduction numbers is that they refer to the long-term temporal evolution of an epidemic, meaning that their value determines whether a given pathogen will eventually establish as endemic in the community (R > 1) or disappear from it (R < 1), without in general giving indications about disease-transmission dynamics in the short run.
This observation represented the starting point of the study “The epidemicity index of recurrent SARS-CoV-2 infections”, just published in Nature Communications and authored by Politecnico di Milano researchers Lorenzo Mari, Renato Casagrandi, Stefano Miccoli, and Marino Gatto, in collaboration with colleagues from Ca’ Foscari University of Venice, the University of Padua, and the École Polytechnique Fédérale de Lausanne. The paper proposes a new metric, the epidemicity index (e), that complements the standard definition of reproduction number by identifying conditions (e > 0) for which transient epidemic waves can occur even if R < 1.
Using a spatially explicit model of SARS-CoV-2 transmission applied to the first months of the pandemic in Italy, the researchers showed that R remained below one for at least four months (April–July 2020), while at the same time epidemicity remained positive, allowing recurrent infection flare-ups well before the major epidemic rebounding observed in the fall.
These observations suggest that the reproduction number, a fundamental long-term diagnostic indicator, may bear little prognostic power in the short run when its value is below one. The Politecnico di Milano researchers and their collaborators conclude that the addition of the epidemicity index to the toolbox of quantitative epidemiologists may help identify effective measures for both short- and long-term disease control.