Profile picture
, 3 tweets, 3 min read
My Authors
Read all threads
A few new graphs on US #COVID19 testing:
1. I've annotated @JoeHasel's important @OurWorldInData graph ourworldindata.org/grapher/cumula… that compared S Korea vs US. Both countries had 1st patient Dx w/in 24 hrs in Jan. For ~50 days there was very little US testing, the spread phase 1/3
2. In @nytimes on the US surge
nytimes.com/interactive/20…
what is missed is all of February when there were a grand total of 352 US tests vs >75,000 in S Korea
Meanwhile people broadly getting infected in the US but no ability to diagnose (or even suspect) @LazaroGamio @adeelnyt 2/3
3. And this March graph which also gives the misimpression on theUS surge, although not normalized (R panel). The key omission is timeline from Jan 21, 1st patient. And it's very likely there were people in the US infected in December, but missed before Seattle kicked in 3/3
Missing some Tweet in this thread? You can try to force a refresh.

Enjoying this thread?

Keep Current with Eric Topol

Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

Twitter may remove this content at anytime, convert it as a PDF, save and print for later use!

Try unrolling a thread yourself!

how to unroll video

1) Follow Thread Reader App on Twitter so you can easily mention us!

2) Go to a Twitter thread (series of Tweets by the same owner) and mention us with a keyword "unroll" @threadreaderapp unroll

You can practice here first or read more on our help page!

Related hashtags

#COVID19

More from @EricTopol see all

Profile picture
Eric Topol
@EricTopol
In praise of @drsanjaygupta and @DrLeanaWen, purveyors of @COVID19 truth, interrogating models/evidence and presenting unvarnished, hard realities for the public, w/ @AC360 @CNN
We surely need that.
We don't need drip, drip, drip & rose-colored glasses.
100, 200, 300.....
We're staring at 400 or more right now unless something big kicks in. We don't even have a national lockdown yet.
For those who missed an earlier post, these are real data. Plotted each day by @BMcNoldy, not based on a model. Based on a best-fit curve. See for yourself where we are headed on the log plot by mid-April if nothing increases the death doubling time.
Read 3 tweets
Profile picture
Eric Topol
@EricTopol
The US deaths doubling time is 2.6 days.
Which = 100,000 deaths by April 11th
and 200,000 by April 14th (you're hearing underestimates)
Unless something gives via flattening.
Here's @BMcNoldy's updated best-fit. We all need to hope this shifts downward. Soon.
For context, US deaths
9/11: 2,996
World War I: 116,516
World War II: 405,000
The @WhiteHouse advisors are 1° relying on @IHME_UW model.
On March 26:
"We estimate... a total of 81,114 deaths (95% UI 38,242 to 162,106).. over the next 4 months in the US" healthdata.org/research-artic…
I think the world of @IHME_UW, but that projection is way off, more like 4 days
Read 4 tweets
Profile picture
Eric Topol
@EricTopol
The critical 45 days: how one country got ahead of its outbreak and the other enabled unbridled #COVID19 spread
Looking at the numbers in more depth from @OurWorldInData @JoeHasell @MaxCRoser @KoreaCDC data
right panel= total cases from yesterday, note different X and Y axes
Which also explains why South Korea positive tests were <3% throughout.
As of end March 30 @COVID19Tracking for the US:
163,656 positive #COVID19 tests in 964,865 people
**a 16.9% positive rate**
At end March 31, now with 1,048,971 #COVID19 tests
the positive rate (184,770 people)
has gone up further to
**17.6%**
With more testing, the higher positive rate, along w/ the extremely high absolute rate, all reflect the breadth of spread (+ how far behind we've been on this)
Read 6 tweets

Related threads

Profile picture
Caroline Sell
@carolinelsell
Wonderful new podcast by @CIDRAP, giving you an inside look at what my @PublicHealthUMN class w/Dr. Osterholm is like! Highly recommend the listen! Key points from ep 1 on #COVIDー19 #COVID19:
Thread 1/10
1: @mtosterholm debunks the seasonality premise. Typical in disease outbreaks to see peak infections after 6mo, this is time to understand transmission & take action. Nothing to do w/seasonality or temp, example of active MERS transmission in Arabian desert
2/10
2: Must consider long-term plans. Something between full lockdown vs no action. Find middle ground, minimize exposure in most vulnerable pop, allow transmission in less vulnerable pop b/c less severe outcomes, they become immune & continue to work in society/care for others
3/10
Read 10 tweets
Profile picture
Reuters Institute
@risj_oxford
Here's a thread with a selection of great journalism on #COVIDー19 from around the world. Please share and feel free to add suggestions at the end #Covid_19

1. @nytimes has published a free ebook with the answers to basic questions from its readers.
nytimes.com/article/free-e…
2. @MaxCRoser and his team at @OurWorldInData are tracking data and giving useful context on every aspect of the outbreak. This piece on how every country is testing is particularly useful ourworldindata.org/covid-testing
3. Our friends at @ConversationUK are publishing pieces by epidemiologists and public health experts. Here's a good example

How to spot bogus science stories and read the news like a scientist.

By @DougSpecht and @Julio51587901
theconversation.com/how-to-spot-bo…
Read 16 tweets
Profile picture
Chicago Community Bond Fund
@ChiBondFund
This is a thread about why it is absolutely essential that we get people out of jails, prisons, & immigration detention during the #COVIDー19 pandemic. It will include information & demands for how to #StopCOVID19inJails .

The health of people inside & all of us depends on it.
This piece by @premaldharia explains how #COVIDー19 could spark a humanitarian crisis inside prisons and jails. slate.com/news-and-polit… #StopCOVID19inJails
Jails and prisons are the perfect incubators for #COVIDー19. Health care in these facilities is often abysmal. This article from @nhbaptiste explains what jails and prisons should be doing to improve access to healthcare. motherjones.com/politics/2020/… #StopCOVID19inJails
Read 34 tweets
Profile picture
New Scientist
@newscientist
How bad will the #Covid-19 outbreak get? A leading epidemiologist has claimed it could infect 60% of the world’s population. It seems to be more contagious than 2009 swine flu, which it is estimated infected 24% of the world’s population. bit.ly/39Elhrt
The death rate is hard to calculate without knowing the true number of cases. Epidemiologists think many mild cases are going undetected. If so, the overall death rate may be only 1 per cent. #Covid-19
newscientist.com/article/223326…
Wuhan, the centre of the epidemic, has been locked down since 23 January. The streets are largely empty, but supermarkets remain open and well stocked. #Covid-19
newscientist.com/article/223245…
Read 10 tweets
Profile picture
Kako
@Kako_line
Bonjour @Slatefr, je souhaitais vous parler de votre article, qui a été repris par @ZeroWasteParis et bien d'autres, et qui manque terriblement de rigueur. Je vous explique pourquoi ⬇️
#recyclage #pollution
slate.fr/story/183636/c…
J'ai tiqué sur l'affirmation selon laquelle 91% des #bouteilles en #plastique ne sont pas recyclées (chiffres monde). En fait ce n'est pas tout à fait ça. Voici ce que vous dites ⬇️ vous associez production de bouteille et les 91% de plastique non recyclés
Nous allons reprendre le lien que vous associez à ce chiffre dans votre article, qui est un article de @Forbes de 2017. Mais qui est assez clair sur le sujet
forbes.com/sites/trevorna…
Read 13 tweets
Profile picture
Esteban Ortiz-Ospina
@eortizospina
New datasource on a very important question! The V-DEM project (Varieties of Democracy, @vdeminstitute) measures democratic institutions across the world, with long-run series going back to 1789

It’s a team of more than 3,000 country experts based all over the world

Thread: 1/4
[2/4] They include variables measuring all sorts of things, from very granular political outcomes and processes, to aggregated indices that classify political regimes.
[3/4] All variables report confidence intervals. The documentation is very good and all the data is open. It seems like a step forward from the popular ‘Polity 4’ data

This scatter plot compares Polity 4 and the V-Dem liberal democracy index: ourworldindata.org/grapher/polity…
Read 4 tweets

Trending hashtags

#Qamishli #SyrianMilitary #Combating_Terrorism #fighters #Independence #Coronavirus #quarantine #CoronavirusOutbreak #destabilization #MI6 #COVID #Africa #DroneFactory #Egyptian #policeofficers #interference #COVIDー19 #society #child #refugees #COVID19 #Congress #Kazakhstan #coronavirus #Usurpers

Embed code for your website

×
Follow Us on Twitter!

Did Thread Reader help you today?

Support us! We are indie developers!

This site is made by just three indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3.00/month or $30.00/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!