Natalie E. Dean, PhD Profile picture
Dec 9, 2021 9 tweets 3 min read Read on X
A sketch to explain how a new variant may appear milder even with no change in underlying virulence. This can occur because, when calculating the fraction of cases that are severe, the denominator now includes many re-infections that had previously been averted. A thread. 1/8 Image
Imagine a variant with little capacity for re-infection. The susceptible population is exposed to enough virus to infect. The infections include severe, moderate, mild disease, and asymptomatic infections. (Here I point out that these sketches are not to scale.) 2/8 Image
But imagine our population also has a large fraction who have been previously infected. Because the variant has little capacity to re-infect, these potential infections were averted. 3/8 Image
When we restrict our attention to the observed cases, some fraction of these are severe. This calculation necessarily excludes any infections that were averted. 4/8 Image
Now imagine a variant with high capacity for re-infection. Amongst the susceptible population, the severity of the cases has not changed. Still the same fraction severe, moderate, mild, asymptomatic. But now we see re-infections, and these are generally not severe. 5/8 Image
So we can still calculate the fraction of cases that are severe, but this is now lower. It is not lower because there are fewer severe cases, but because there are more mild cases (re-infections). 6/8 Image
Thus, the severity profile of Omicron cases must be interpreted along with an understanding of its capacity to re-infect (and infect the vaccinated). I haven't talked about vaccines, but the relationships are similar. We expect a rise in milder cases in the vaccinated. 7/8
So when I look at data out of South Africa or elsewhere, I am thinking not just about the proportion of cases that are severe, but also the sheer number of severe cases, which demonstrates the public health impact of the variant. 8/END
Addendum... excuse my color choices. I didn't have highlighters and I made do.

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More from @nataliexdean

Aug 8, 2022
Starting now! I’ll be live tweeting this @DataSciJedi-sponsored session on Delivering Data Differently at #JSM2022. #JEDIatJSM
Our first speaker is @ajrgodfrey. He speaks from his experiences as a blind person. He emphasizes the importance of independence and dignity for the visually impaired. #JEDIatJSM
“A blind person must be able to collect, analyze, interpret, and manipulate scientific data in order to answer questions and communicate the knowledge gained from their results in a way that can be readily understood by their sighted peers.“ @ajrgodfrey #JEDIatJSM
Read 12 tweets
Jul 10, 2022
If a new SARS-CoV-2 variant is spreading 50% faster than an old one, does the new variant have a 50% higher R0? With each new variant more transmissible than the last, does that mean the latest variants have an R0 of 18? 😳

A short explainer…
1/5
A new variant may spread faster for a few main reasons (a non-exhaustive list):

- An increase in inherent transmissibility (e.g. higher viral load, better binding to cells)

- An increased ability to infect people with some baseline immunity (“immune evasion”)

2/5
Just because something has a 50% *growth advantage* in a population does not mean it is 50% more *transmissible.* Some (or most) of that growth advantage may come from immune evasion. 3/5
Read 5 tweets
Jun 10, 2022
I enjoyed participating in yesterday's #EEID2022 panel on scientific communication - what has worked, what hasn't, and what I've learned. For these types of panels, I have made a conscious decision to be very honest, including the good and the bad experiences. 1/
Yesterday, that included me telling the audience how much I angsted over questions like "Is it safe to do X? Our viewers want to know!" Or pressure to stay up to date on everything, or say yes to all requests. Worry that I'm saying the wrong thing or don't belong. 2/
Admitting vulnerability is a trait I admire in others because it takes bravery and normalizes common challenges. IMO, it's a similar bravery to scientific communication in the first place. Public engagement involves putting yourself out there in a way that can be intimidating. 3/
Read 4 tweets
Jun 6, 2022
Tracking down primary sources for the estimated 85% effectiveness of smallpox vaccines against #monkeypox is harder than I thought.

From what I can gather, ACAM2000 effectiveness was estimated from observational data of outbreaks in Africa. (Which studies are these?) ...
And then the JYNNEOS vaccine is cited as having "up to 85% effectiveness."

Per CDC "The effectiveness of JYNNEOS against monkeypox was concluded from a clinical study on the immunogenicity of JYNNEOS and efficacy data from animal studies." ...
I interpret this as non-inferiority data comparing JYNNEOS and ACAM2000 immune responses (hence the "up to" phrasing). (e.g. nejm.org/doi/10.1056/NE…)

Ultimately, I'm curious about the quality of the original 85% estimates.
Read 5 tweets
Apr 13, 2022
Recently I learned the term “hidden curriculum,” and it felt like an aha moment. A very short story about one of my hidden curriculum moments. 1/7
edglossary.org/hidden-curricu…
I interviewed for biostats PhD programs during my senior year of college. I really wasn’t sure what to expect at my interviews. I remember being so thrilled to be flown anywhere. I showed up enthusiastic and ready to learn about the field. 2/7
During a one-on-one interview, I asked a (white, male, very senior) faculty member to tell me about his research. I thought this to be a perfectly reasonable question. I really didn’t know much about what biostatisticians did, the range of projects they worked on. 3/7
Read 10 tweets
Jan 21, 2022
The end of the pandemic? Let's talk about modeling assumptions and future uncertainty. Are the IHME projections discussed in this @TheLancet comment assuming ~90% of Omicron infections are asymptomatic and thus likely to be missed? 1/5
thelancet.com/journals/lance…
The Omicron waves have certainly been large and many infections have been missed, but the evidence that the asymptomatic fraction is *so high* is thin. A model with this assumption would seem to attribute the rapid turnaround in a wave entirely to running out of susceptibles. 2/5
But in reality, there can be many factors that cause a turnaround. A build up of immunity is maybe the largest one, but also temporary protective changes in behavior. (I also think about our complex network structures, and whether a wave has fully percolated through.) 3/5
Read 5 tweets

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