But taking the idea from the medrxiv report cited above, and using *one* dose for each seropositive and *two* doses for each seronegative, one can derive a similar formula (pic).
When I write "32% bonus vax supply" or "16% bonus vax supply", I think of that as a theoretically possible increase in the accumulation of protection in the population.
In other words, an increase in rollout speed (for the same # of vaccines).
Of course, there are costs too: price of antibody tests, logistics of it all, headaches of messaging.
Reality: Probably too difficult to do broadly, but there may be situations where this dose sparing would be valuable. 4/4
A 2nd study also preprinted today draws similar conclusions re antibodies!
"the antibody response to the 1st vaccine dose in individuals with pre-existing immunity is equal to or even exceeds the titers found in naive individuals after the 2nd dose" 5/4
Our recent work on vaccine prioritization for COVID-19 is now published in @ScienceMagazine, but this paper has evolved because of both formal and informal peer review. So while the paper is linked, here's a quick summary of the results. 🧵 1/
First, rather than reading another Twitter summary, there's a great discussion of this work in the broader context of vaccination strategies by two vaccine/modeling experts @MeaganCFitz@Alison_Galvani. Highly recommended for both theory & history. 2/
Updated preprint: Model-informed COVID-19 vaccine prioritization strategies by age and serostatus.
Smart suggestions from formal/informal review mean that the paper still asks how demographics, contacts, vax efficacy, & seroprevalence affect prioritization by age, but now...1/
We asked whether transmission-blocking properties affect prioritization. Intuitively, as the vaccine's transmission blocking properties become worse, direct protection of adults 60+ became/remained the clear best prioritization—across countries, R0 values, & vaccine supplies. 2/
Btw—there's a nice piece by @MollyEFG & team that shows why indirect effects are critical. In the medrxiv version of their NatMed editorial, they have this figure, showing how transmission blocking effects are *extremely* valuable at pop. scale. nature.com/articles/s4159…
Preprint: COVID-19 screening and surveillance are critical, but molecular tests haven't come close to meeting needs, and temperature checks fail. We modeled the epidemiological impacts of using loss of smell as a screening symptom. Here's what we found. 1/ medrxiv.org/content/10.110…
Loss of smell is an interesting screening symptom because it's highly specific to COVID, precedes most other overt symptoms, and typically lasts ~1 week. Critically, its prevalence goes from ~45% when self-reported up to ~80% when a test is used. 2/
Contrast this with fever: ~20% prevalence, not specific to COVID, and lasts 1.5 days on average. So why do we still screen for fever? You can look for it in seconds with a contactless thermometer.
Could rapid, contactless, cheap tests for anosmia, impact transmission? 3/
Slovakia (pop 5.5M) is attempting a mass COVID-19 screening campaign using rapid antigen tests. The public health community is going to learn a lot. Here's what I'm looking for... 1/
Slovakia, like Europe, is experiencing a rapid acceleration of infections & deaths, and is starting to use curfews & lockdowns.
A pilot phase tested 140K people with rapid antigen tests, found 5.5K positives (4%).
They'll test the nation over next 2 weekends! Good idea? 2/
First, there are reasonable critiques of rapid Ag tests related to their sensitivity—do they miss too many infections?—and their specificity—do they falsely tell uninfected people that they're positive?
Re sensitivity: every broken transmission chain is a victory, BUT...
3/
Most of what we know about viral dynamics during SARS-CoV-2 infections comes from samples taken *after* symptom onset. From symptoms onward, viral loads slowly fadeaway.
What do viral loads look like between exposure and symptoms? 2/n
In this study, researchers in the NBA bubble recruited players, coaches, vendors, and others to sign up for a longitudinal study with regular COVID testing.
In other words, the researcher ran a classic pick-enroll-screen in the NBA bubble. 3/n
How does effective viral surveillance change when (1) some people refuse to participate, and (2) sample collection errors lead to lower sensitivity, indep. of a test's limit of detection? Questions raised by @jhuber@awyllie13 & others after I posted this preprint last week.👇 1/
I love twitter+preprints precisely because of this community. In the updated preprint, we've corrected a couple typos, and created a new supplement, "Adjustments for false negatives and test refusal" which I'll quickly summarize below. 2/ medrxiv.org/content/10.110…
Previously, we estimated the impact of a policy on R by measuring the "infectiousness" the testing, relative to no testing. The formula's values correspond to the heights of bars in plots like this one. f0 is the leftmost hatched bar. ftest is the total height of a policy bar. 3/