Mary Wilson
Well-known member
MAR. 26, 2020
By David Wallace-Wells
A bit before midnight on January 20, a Harvard epidemiologist named Eric Feigl-Ding posted a long, terrifying Twitter thread mostly summarizing, and in a few places contextualizing, a new, pre-publication paper on the infectiousness of the novel coronavirus that had, at the time, forced Wuhan into a total lockdown but had not yet been detected outside of China. The context he added was, mostly, alarmism.
“Holy mother of god,” the thread began, “the new coronavirus is a 3.8!!!” That figure referred to what’s called the reproduction number, or “R0,” of a disease: how many people would be infected by a single sick person. “I really hate to be the epidemiologist who has to admit this, but we are potentially faced with … possibly an unchecked pandemic that the world has not seen since the 1918 Spanish Influenza. Let’s hope it doesn’t reach that level but we now live in the modern world
with faster 
+ 
than 1918. @WHO and @CDCgovneeds to declare public health emergency ASAP!”
The thread has since been deleted, though you can still read a preserved version of it here. It was, for many Americans, if not the first time they had heard of coronavirus, perhaps the first time they had seen a global alarm raised over it. And in doing so, it produced what is by now a sort of predictable backlash: other scientists and science journalists taking issue with it, en masse, pointing out that the paper had not yet been published; that Feigl-Ding’s comparison to the infection rate of SARS was inaccurate; that most estimates of the R0 number were now lower than 3.8. Feigl-Ding’s tweets got more readers than those of his critics’. But those credentialed in epidemiology and public health were much more likely to see the criticism as sober and responsible, Feigl-Ding himself as an irresponsible alarmist, and the impulse to raise alarm a deeply reckless one. An Atlantic story about it was headlined “How to Misinform Yourself About the Coronavirus.”
Two months later, we are, inarguably, in the midst of a global pandemic. ...
https://nymag.com/intelligencer/2020/03/why-was-it-so-hard-to-raise-the-alarm-on-coronavirus.html
__________________________________________________________________________________
Eric Feigl-Ding
@DrEricDing
Epidemiologist & health economist.
Senior Fellow, @FAScientists.
Former 16 yrs @Harvard. Environment, health & social justice.
COVID updates since Jan 2020.
Jan. 25, 2020 3 min read
HOLY MOTHER OF GOD- the new coronavirus is a 3.8!!! How bad is that reproductive R0 value? It is thermonuclear pandemic level bad - never seen an actual virality coefficient outside of Twitter in my entire career. I’m not exaggerating... #WuhanCoronovirus #CoronavirusOutbreak
2/ “We estimate the basic reproduction number of the infection (R_0) to be 3.8 (95% confidence interval, 3.6-4.0), indicating that 72-75% of transmissions must be prevented by control measures for infections to stop increasing...
3/ ... We estimate that only 5.1% (95%CI, 4.8-5.5) of infections in Wuhan are identified, and by 21 January a total of 11,341 people (prediction interval, 9,217-14,245) had been infected in Wuhan since the start of the year. Should the epidemic continue unabated in Wuhan....
4/ we predict the epidemic in Wuhan will be ...
https://threader.app/thread/1220919589623803905
By David Wallace-Wells
A bit before midnight on January 20, a Harvard epidemiologist named Eric Feigl-Ding posted a long, terrifying Twitter thread mostly summarizing, and in a few places contextualizing, a new, pre-publication paper on the infectiousness of the novel coronavirus that had, at the time, forced Wuhan into a total lockdown but had not yet been detected outside of China. The context he added was, mostly, alarmism.
“Holy mother of god,” the thread began, “the new coronavirus is a 3.8!!!” That figure referred to what’s called the reproduction number, or “R0,” of a disease: how many people would be infected by a single sick person. “I really hate to be the epidemiologist who has to admit this, but we are potentially faced with … possibly an unchecked pandemic that the world has not seen since the 1918 Spanish Influenza. Let’s hope it doesn’t reach that level but we now live in the modern world
with faster + than 1918. @WHO and @CDCgovneeds to declare public health emergency ASAP!”The thread has since been deleted, though you can still read a preserved version of it here. It was, for many Americans, if not the first time they had heard of coronavirus, perhaps the first time they had seen a global alarm raised over it. And in doing so, it produced what is by now a sort of predictable backlash: other scientists and science journalists taking issue with it, en masse, pointing out that the paper had not yet been published; that Feigl-Ding’s comparison to the infection rate of SARS was inaccurate; that most estimates of the R0 number were now lower than 3.8. Feigl-Ding’s tweets got more readers than those of his critics’. But those credentialed in epidemiology and public health were much more likely to see the criticism as sober and responsible, Feigl-Ding himself as an irresponsible alarmist, and the impulse to raise alarm a deeply reckless one. An Atlantic story about it was headlined “How to Misinform Yourself About the Coronavirus.”
Two months later, we are, inarguably, in the midst of a global pandemic. ...
https://nymag.com/intelligencer/2020/03/why-was-it-so-hard-to-raise-the-alarm-on-coronavirus.html
__________________________________________________________________________________
Eric Feigl-Ding
@DrEricDing
Epidemiologist & health economist.
Senior Fellow, @FAScientists.
Former 16 yrs @Harvard. Environment, health & social justice.
COVID updates since Jan 2020.
Jan. 25, 2020 3 min read
HOLY MOTHER OF GOD- the new coronavirus is a 3.8!!! How bad is that reproductive R0 value? It is thermonuclear pandemic level bad - never seen an actual virality coefficient outside of Twitter in my entire career. I’m not exaggerating... #WuhanCoronovirus #CoronavirusOutbreak
2/ “We estimate the basic reproduction number of the infection (R_0) to be 3.8 (95% confidence interval, 3.6-4.0), indicating that 72-75% of transmissions must be prevented by control measures for infections to stop increasing...
3/ ... We estimate that only 5.1% (95%CI, 4.8-5.5) of infections in Wuhan are identified, and by 21 January a total of 11,341 people (prediction interval, 9,217-14,245) had been infected in Wuhan since the start of the year. Should the epidemic continue unabated in Wuhan....
4/ we predict the epidemic in Wuhan will be ...
https://threader.app/thread/1220919589623803905