Why R0 Is Problematic for Predicting COVID-19 Spread

The SARS-CoV-2 pandemic has revealed the limitations of R0 as no other disease outbreak has before, at a time when policymakers need accurate forecasts.

Written byKatarina Zimmer
| 30 min read

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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 ...

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Meet the Author

  • katya katarina zimmer

    After a year teaching an algorithm to differentiate between the echolocation calls of different bat species, Katarina decided she was simply too greedy to focus on one field of science and wanted to write about all of them. Following an internship with The Scientist in 2017, she’s been happily freelancing for a number of publications, covering everything from climate change to oncology. Katarina is a news correspondent for The Scientist and contributes occasional features to the magazine. Find her on Twitter @katarinazimmer and read her work on her website.

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Published In

July/August 2020

Life During a Pandemic

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