Nasal-swab rapid tests failed to identify omicron infections for 2 to 3 days after saliva-based PCR tests identified high concentrations of viral RNA.

A new paper from @DrBlytheAdamson @robbysikka @awyllie13 and Prem Premsrirut has the details. 👇👏 1/4

medrxiv.org/content/10.110… This means that rapid tests aren't catching people during their first few days of infection. But sensitive PCR tests are slowed by day++ turnarounds.

Suggests we're unlikely to test our way out of the current surge, even if we each had a week's supply of rapid tests at home. 2/4

In populations with high vaccine coverage, wouldn't we actually *expect* many infections to be breakthroughs?

What would this mean for the impact of unvaccinated-only testing programs as vacc. rates increase?

These questions frame our new preprint. 1/

medrxiv.org/content/10.110… By definition: when no one is vaccinated, 0% of infections are breakthroughs. When everyone is vaccinated, 100% of infections are breakthroughs.

So what happens in between?

Our study examines this question using a modeled population with mixed vax & prior infection status. 2/

Preprint: the relationship between SARS-CoV-2 viral load & transmission has been difficult to estimate.

Here, routine testing on a univ campus allows us to look at roommate pairs: viral loads were 6.5X higher when the index roommate transmitted. 1/

medrxiv.org/content/10.110… This study starts with the observation that students who lived in multiple-occupancy rooms were more likely to test COVID-19+ by RT-PCR screening during the Fall 2020 semester.

This, in spite of higher testing rates among singles students. 2/

If you've already had COVID-19, would a *single* dose of Pfizer-BioNTech/Moderna provide a boost?

This brief report brings antibody titer data: yes.

This suggests a possible dose-sparing strategy to improve vaccine rollout... 1/4

medrxiv.org/content/10.110… If vax & infection provided equivalent immunity, a dose-sparing strategy targeting seronegatives could be thought of as increasing vax supply (pic).

Ex: se 96.6%, sp 99.9% (Roche), 25% seroprev. = 32% increase in vax supply. 2/4

Modeled in this paper: science.sciencemag.org/content/early/…

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/

science.sciencemag.org/content/early/… 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/

science.sciencemag.org/content/early/…

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/

https://twitter.com/bubar_kate/status/1304472235214741504

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/

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/

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/

spectator.sme.sk/c/22519165/cor… 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/

Here is my summary of an exciting new @NBA + longitudinal COVID testing paper.

Writing a thread about COVID and the NBA has been on my bucket list for some time, so today I decided to box out some time and give it a shot. 1/n

medrxiv.org/content/10.110… 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

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/

https://twitter.com/DanLarremore/status/1276260291764826112

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…

Preprint: Viral surveillance testing is crucial, but not all surveillance strategies are equal. We modeled the impacts of test frequency, assay limit of detection, test turnaround time, measuring impact on individuals & epidemics. Here's what we found. 1/ medrxiv.org/content/10.110… The first finding is that limit of detection matters less than we thought. There is only short (1/2 day) window when qPCR is superior during the exp growth phase. We showed this in a simple viral load model, but any model with exp growth between Ct40 and Ct33 would confirm. 2/

My colleagues and I are formally seeking a retraction of the recently published “Identifying airborne transmission as the dominant route for the spread of COVID-19.” The full text of our letter to the PNAS editorial board can be found here. 1/
metrics.stanford.edu/PNAS%20retract… It is important that science, especially now, be as rigorous and methodologically sound as possible. However, this paper suffers from numerous and fundamental errors that undermine the foundation of its conclusions. The paper is linked here. 2/ pnas.org/content/early/…

Sensitivity & specificity affect the inferences that we can draw from seroprevalence studies & inform the number of samples we need for statistical confidence. To help, we built two calculators. Calculator 1: survey data, se, sp → prevalence posterior. larremorelab.github.io/covid-calculat…

https://twitter.com/yhgrad/status/1250858246002348034

But let's also remember: sensitivity & specificity are *estimated from data*. That means that they, too, need statistical treatment. So for Calculator 2: survey data AND raw assay calibration data → posteriors for prevalence, sensitivity, and specificity. larremorelab.github.io/covid-calculat…

Earlier today, we put out a preprint that asked: how do we design and analyze SARS-CoV-2 seroprevalence surveys? @yhgrad wrote a lovely explainer thread, linked here.

https://twitter.com/yhgrad/status/1250858246002348034?s=20

] I want to highlight some #stats and #networks results. 1/ First, the basics. This paper's 1st result is like a statistical inference midterm problem: If you observe n+ positive tests, n- negative tests, and you know the sensitivity/specificity of your test, what is the posterior prob. of actual positives? Solution: Bayes' rule. ✅