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Natalie E. Dean, PhD Profile picture
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Jun 10 • 4 tweets • 2 min read
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/
I've learned a lot, through success and failure. A pet project now is to share some of those lessons with others in my field of biostats (catch me at #JSM2022). Thanks again to those who attended yesterday's #EEID2022 session and the thoughtful convos that followed. 4/4

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More from @nataliexdean

Natalie E. Dean, PhD Profile picture
Jun 6
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
Natalie E. Dean, PhD Profile picture
Apr 13
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
Natalie E. Dean, PhD Profile picture
Jan 21
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
Natalie E. Dean, PhD Profile picture
Dec 9, 2021
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
Read 9 tweets
Natalie E. Dean, PhD Profile picture
Nov 19, 2021
Reasons for Optimism and Pessimism
November 2021 Edition

Optimism: Boosters for all adults in the US and vaccines for 5+. Both will make a chunk of our population less likely to be infected (and so less likely to transmit).

Pessimism: Holdouts who haven't received a first dose.
Optimism: Models projected a steady decline in cases, which reflects the large numbers vaccinated and previously infected. There is a lot of population immunity to dampen previous waves.

Pessimism: Nonetheless, we are seeing increases in regions of the country.
Optimism: With antivirals, soon there will be more options to treat patients earlier. This is an important layer in our strategy.

Pessimism: The real impact of the program will depend on systems that connect early testing and easy access to treatment. Hopefully we can do that...
Read 4 tweets
Natalie E. Dean, PhD Profile picture
Oct 6, 2021
I've been enjoying @BreneBrown's Dare to Lead podcast, and I wanted to share two insightful points from her episode with @AdamMGrant. The first on polarization, and the second on leadership.
On polarization, one might think that the way to bring someone away from an extreme position is to help them understand the opposing side. But in fact that can increase polarization by painting an issue as two-sided. With only two choices, which camp are you in?
By overemphasizing the extreme positions, we lose sight of the large nuanced gray area in the middle, where there can be overlap in views. There is value in focusing on common ground, and being careful not to oversimplify a complex issue.
Read 6 tweets

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