On the evening of December 30, 2019, an email with the subject line “undiagnosed pneumonia – China (Hubei)” popped into Maia Majumder’s inbox. The notice, which the computational epidemiologist had received through ProMED, a global reporting system for infectious diseases, went on to describe Chinese news reports of patients pouring into hospitals in Wuhan presenting with an unexplained respiratory illness. It added: “Citizens need not panic.” 

Majumder, a researcher at Harvard Medical School and Boston Children’s Hospital who had previously helped predict the spread of Saudi Arabia’s MERS epidemic of 2014 and the West African Ebola outbreak shortly thereafter, agreed with that statement—at that point, it wasn’t clear whether the culprit was an infectious pathogen capable of jumping from one person to the next. But when murmurs of possible human-to-human transmission started to circulate a few weeks later, she and her Harvard colleague Kenneth Mandl set out to calculate a metric—the pathogen’s basic reproductive number (R0)—that would hint whether it could cause an epidemic.

https://www.the-scientist.com/features/why-r0-is-problematic-for-predicting-covid-19-spread-67690