"Acute infections in vaccinated and unvaccinated people feature similar proliferation and peak Ct, but vaccinated individuals cleared the infection more quickly. [BUT] Viral concentrations do not fully explain the differences in infectiousness..." 1/6 medrxiv.org/content/10.110…
New pre-print from the labs of @yhgrad & @NathanGrubaugh using data from the NBA, confirms that peak viral load is similar between vaccinated/unvaccinated cases, but clearance is faster in vaccinated. 2/6
However, and here is the *really* important part, viral concentrations did not fully explain differences in infectiousness between pre-Alpha, Alpha, and Delta variants. 3/6
What does this mean? 1.) masking & testing are critical even for vaccinated individuals to control #COVID19, 2.) the number of secondary infectious is probably lower for breakthrough infections, which makes vaccination all the more important, 4/6
3.) we desperately need contact tracing data on breakthrough infections, and 4.) we need more longitudinal studies like this globally. 5/6
h/t to @MOUGK for sending me this pre-print. 6/6

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More from @svscarpino

19 Jul
I'm honored and humbled to announce that I'm #MeetingThisMoment by joining the @RockefellerFdn as the Managing Director of Pathogen Surveillance. I'll be working w/ @RickABright & the incredible PPI team to build an equitable, ethical surveillance program. rockefellerfoundation.org/blog/rapid-gro…
I'm staying on @Northeastern as an affiliate assistant professor & would not be in a position to take on this incredible responsibility w/out the support from so many amazing individuals at NEU, especially Prof. Vespignani (@alexvespi) and the wonderful members of @NUnetsi.
I owe a huge thanks to countless other mentors, colleagues, and friends, but want to specifically call out @MOUGK, @johnbrownstein, and the entire @globaldothealth team. Working with you on improving #COVID19 data over the past 18 months has been the honor of lifetime.
Read 4 tweets
24 Feb
For the past year, we've been building an open data platform for tracking epidemics and curating a global repository of #COVID19 cases. Today, with support from @Googleorg & @RockefellerFdn, I'm proud to introduce @globaldothealth. 1/13
We have an amazing team of engineers, academics, technologists, and entrepreneurs; many of whom have volunteered hundreds of hours helping us build Global.health. You can learn about them and their incredible work here: global.health/about/ 3/13
Read 13 tweets
5 Nov 20
While we all anxiously await news from NV, GA, & PA, our (@LHDnets, @BMAlthouse, & @all_are) paper on pandemic risk assessment that goes *beyond R0* is out @RSocPublishing Interface. 1/10 royalsocietypublishing.org/doi/10.1098/rs…
Building from foundational work in math. epi. and network science, we show how super-spreading creates havoc for pandemic risk predictions based on R0 alone and then derive a method for correcting the predictions. 2/10
This paper includes what I think is the most intuitive explanation for how higher moments in the distribution of secondary infections affects epidemic risk that I've read (@LHDnets & @all_are wrote the following lines). 3/10
Read 10 tweets
4 Nov 20
Regardless of what happens, 48% of voters in US supported hate, greed, and anti-science. Until we accept and address these persistent issues, we cannot progress as a country.
Since the trolling has started, here’s my logic. In the 10 months leading up to this election, the actions of our incumbent president directly *caused* the deaths of >200k Americans and counting & wiped 12 trillion dollars from our economy.
Anyone voting for him must have an even stronger motive. The only ones I can think of are hate, greed, and anti-science. I file taking away a woman’s right to choose under hate and anti-science.
Read 6 tweets
5 Oct 20
The intensity of #COVID19 epidemics is heavily influenced by population structure. Our new paper analyzing high-resolution case, population, & mobility data from China and Italy is out today in @NatureMedicine. Co-led w/ @MOUGK & @EvolveDotZoo. 1/15 nature.com/articles/s4159… Image
The work brought together an international team of collaborators: B. Rader, @AnjalikaNande, @alison_l_hill, B. Adlam, @RCReinerJr, @davidmpigott, @B_Gutierrez_G, A. Zarebski, @munikShrestha, @johnbrownstein, @marciacastrorj, @chris0dye, H. Tian, @EvolveDotZoo, & @MOUGK 2/15
Using case data from the "Open COVID-19 Data Working Group" (github.com/beoutbreakprep…), paired with high-resolution population and mobility data, we showed that epidemics are sharper in lower-density areas and broader and longer in big cities. 3/15 ImageImage
Read 15 tweets
22 Sep 20
Tomorrow I'm speaking @yale_eeb on "Network Theory and COVID-19." My goal is to pull a thread across the 10+ papers we've written on the topic & convince you that #COVID19 became a pandemic because the world does not understand complex systems. h/t to my host @big_data_kane. 1/13 Image
First, building from foundational work in math. epi. and network science, we showed how super-spreading creates havoc for pandemic risk predictions and then derive a method for correcting the predictions. 2/13
Second, how de-coupling the risk of infection from transmission breaks the friendship paradox, which most (non-mass-action) herd immunity thresholds rely on & can mean that backwards case investigation is more important than forward contact tracing. 3/13
Read 13 tweets

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