“I like the scientific spirit—the holding off, the being sure but not too sure, the willingness to surrender ideas when the evidence is against them: this is ultimately fine—it always keeps the way beyond open—always gives life, thought, affection, the whole man, a chance to try over again after a mistake—after a wrong guess.”
– Walt Whitman
Credit: CDC/ Sally Ezra
There is lots of discussion both in the popular and scientific media about how many people will be infected, and how many more will die. As both the discussion, fear, and grim resolve to do something increase, it is important to understand what uncertainties are in the predictions.
Science Insider has a brief write-up here of the Gomes et al paper in PLoS Currents. The paper is a good read, and pay particular attention to the disease model section to get a nice write-up of the inner workings of their estimates.
The paper does a nice job of breaking down R0, or R nought, the basic reproduction rate. If the paper is to much, run on over to Wikipedia here for a quick brush-up on what R0 is and how it is used.
Christian Althaus’s paper, also in PLoS Currents contains one more piece of the puzzle:
Two key parameters describing the spread of an infection are the basic and the effective reproduction numbers, Ro and Re, which are defined as the number of secondary infections generated by an infected index case in the absence and presence of control interventions. If Re drops below unity, the epidemic eventually stops.
Re is an interesting variable, and this is really the variable that news organizations are struggling to define. Re address the question of what happens to the infection rate if the proper health care steps, “control interventions” are put in place. This gets to the point of the question, how many will continue to be infected?
Gillespie Lab 