Eric Feigl-Ding’s Jan. 20 tweet on Twitter was one of the first to set off COVID-19 pandemic alarm bells. He is a Washington, D.C. epidemiologist and health economist, and is currently a visiting scientist in the Department of Nutrition at the Harvard University T.H. Chan School of Public Health.
“HOLY MOTHER OF GOD – the new coronavirus is a 3.8!!!” Feigl-Ding’s tweet read. “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.” The estimate of the virus’s contagiousness is captured in a variable called R0, or basic reproduction number for COVID-19, and is a key number used in infectious disease modelling for estimating pandemic growth rate. An R0 of 3.8 meant that every person who caught COVID-19 would transmit it in turn to almost four other people.
Feigl-Ding, 37, had tweeted after reading a paper called “Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions,” published on Jan. 23, and providing an early estimation of epidemiological parameters and epidemic predictions using case information from Chinese cities and other countries from Jan. 1-22 to fit a mathematical model to estimate outbreak parameters.
Still, there were problems with Feigl-Ding’s tweet, as Alexis C. Madrigal, a staff writer at The Atlantic, noted just eight days later in a piece headlined, “How to Misinform Yourself About the Coronavirus: Even if you avoid the conspiracy theories, tweeting through a global emergency is messy, context-free, and disorienting” (https://www.theatlantic.com/technology/archive/2020/01/china-coronavirus-twitter/605644/), which appeared online Jan. 28.
Feigl-Ding is in no way an unintelligent man or incompetent epidemiologist; by all accounts he is quite the contrary in both disposition and abilities. Nor is this in any way to suggest the COVID-19 pandemic, which hadn’t even been designated a “public health emergency of international concern” (PHEIC) by the World Health Organization (WHO) on Jan, 20 [that would come Jan. 30], much less a global pandemic [that would come March 11] was not worthy of a five-alarm fire bells general wake-up call or tweet even back then: it was.
His work focuses on the intersection of public health and public policy. Feigl-Ding has published in leading journals, including the New England Journal of Medicine, Journal of the American Medical Association, The Lancet, and Health Policy. In 2018, he unsuccessfully sought the Democratic nomination to run for the party in Pennsylvania’s 10th Congressional District, located in the south-central region of the state, and encompassing all of Dauphin County, as well as parts of Cumberland County and York County, including the cities of Harrisburg and York. But in his enthusiasm to tweet, he omitted some context, which he now regrets, he says. What he inadvertently omitted primarily were facts such as other infectious diseases, say measles for instance, also have very high R0 numbers (R0s for measles range from 12 to 18), and by the time he tweeted about the paper, the researchers had already lowered their R0 estimate from 3.8 to 2.5. “And R0, for that matter, is not the be-all and end-all of the danger of a virus,” Madrigal points out “Some highly transmissible diseases are not actually that dangerous.”
Madrigal also rightly observed that “one of the realities of the current information ecosystem” is that while “out-and-out conspiracies and hoaxes will draw some attention, it’s really the stuff that’s close to the boundaries of discourse that grabs the most eyeballs. That is, the information that’s plausible, and that fits into a narrative mounting outside the mainstream, gets the most clicks, likes, and retweets. Bonus points if it’s sensational or something that someone might want to censor.” When Twitter launched in March 2006, its timeline structure was simple: Tweets were displayed in reverse chronological order. In other words, each user’s feed contained tweets from their followers, from the most recent tweets onward. For “top tweets” now, Twitter uses an algorithm-powered feed organized by ranking signals. In addition to ranked content from followers, the feed will sometimes feature “who to follow” suggestions and, and content from other accounts. Users can also provide feedback on content shown in the feed by selecting “show less often.”
In an April-June 2017article in ASA footnotes, a publication of the American Sociological Association, R. Tyson Smith, a visiting assistant professor of sociology at Haverford College in Haverford, Pennsylvania, who conducts research in the areas of health, gender, social psychology, criminal justice, and the military, suggested, “Twitter is arguably the best way to reach the greatest number of people, in the quickest fashion, and in the least mediated way.”
Probably still true, but not necessarily always a good thing for academics perhaps, as Eric Feigl-Ding quickly discovered to his chagrin.
In all fairness, who among us hasn’t hit the send button on a tweet, email, Facebook post, or other social media platform expression, a tad too soon in retrospect? Not I, I admit.
Think? Yes. Send? Maybe – but only after a very long pause, which on most social media platforms, and perhaps especially on Twitter, is about as likely as successfully asking a multi-line slot machine player to ease up to dampen some of the audiovisual feedback.
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