I'm really struggling these days with the politicization of pandemic science.
A quick thread on why I worry that we as scientists are only being inclusive of certain perspectives.
And thereby pushing people away who might otherwise have a lot to offer.
Consider papers with one of the following conclusions:
COVID worsened disease X (except flu).
COVID worsened disparities.
Measures should be more stringent.
Things are going to get worse.
Conservative policies made things worse.
Then consider papers with opposite conclusions.
These conclusions all have political undertones.
But papers w certain conclusions are more likely to be published & cited, while others are more likely to be criticized.
So, if you are an intelligent, but conservative-leaning, thinker, is this a game you want to join?
All this to say, the politicization of pandemic science is literally keeping me up at night tonight.
I'm thrilled to see so many people interested in epidemiology these days. I just hope we can continue to welcome a diversity of perspectives - even conservative ones.
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COVID rates are:
- declining in India, US, most of Europe
- stable & high in Latin America
- rising in sub-Saharan Africa & UK
Why such "random" waves of disease?
It's easy to blame variants, but this doesn't explain variability.
Segregated networks can explain five phenomena.
First, an orientation to this figure.
- Dot: person
- Dark line: very close contact (e.g., household)
- Light line: occasional contact
- Dotted circle: mini-network (e.g., same employer/school)
- Blue = uninfected, red = infected, orange = secondary infection, green = immune.
1. Small epidemics can occur without triggering a nationwide epidemic.
Say the person in the red square gets infected (via the line to the left). This will cause a micro-epidemic among their 2 close contacts, but might not spread.
Are you a prospective PhD/fellow/postdoc looking for the right mentor?
A thread on how to approach the process.
Long story short, two steps: 1) Define your "must-have" priorities. 2) Find evidence (reputation & track record) that a potential mentor will help you achieve those.
Step 1. Define your "must-have" priorities.
There are many things you can accomplish in a 2-4 year program. No mentor will be excellent in helping mentees achieve all of these. List out your "must-haves": things that you will be disappointed if you don't have/accomplish.
13 things a mentor can provide (non-exhaustive):
- Role model
- High-impact publications
- Work-life balance
- Technical skills
- Networking/introductions
- Support for future job
- Personality fit
- Freedom to choose projects
- Strong team
- Time
- Name recognition
- Funding
One term I worry that we (as a public health community) have mis-messaged during the pandemic:
"herd immunity threshold"
A non-technical thread on why this is not "% of the population that needs to be vaccinated for us to return to life as normal while eradicating COVID-19"...
Disclaimer to the experts: This is for a non-expert audience.
Let's start with the virus that's currently circulating, and estimate roughly that - with no vaccine, no immunity, and "life as normal" - this person would infect ~5 other people before recovering (or dying).
Next, let's take a situation similar to the USA. Out of these 5 possible people infected, 2 might be vaccinated; 1 out of the remaining 3 might be someone who's already have had COVID; and 1 of the remaining 2 might be prevented by current behaviors (masks, distancing, etc).
The B117 variant is now the dominant strain of SARS-CoV-2 in the UK, Ireland, Israel, Denmark. Likely also Portugal, Belgium, France, Italy, Norway.
Yet for the most part, these are not the countries where COVID-10 cases are rising (see below). What gives?
One explanation is that B117's transmission is being offset by restrictions, population immunity, etc. And that those countries w high B117 (UK, Ireland, Portugal) have locked down most. There is likely some truth to this - but not too much correlation w stringency index (below).
But it's also worth considering B117 and non-B117 COVID as separate epidemics. For example, look at Danish data below - it's tempting to think of B117 (red) as "replacing" non-B117 (grey). But that's not what's actually happening...