Sam Scarpino Profile picture
Nov 15 7 tweets 3 min read
1/ I'm growing increasingly worried about #Ebola in Uganda.

Over the past few days, cases have been reported in previously unaffected districts, rates have started increasing, & the MoH sit reps were plagued w/ errors.

All signs point toward a deteriorating situation.
2/ Over the past week, confirmed Ebola cases have been reported in the Masaka and Jinja districts. This is the first time EVD cases have been reported in these districts. who.int/emergencies/di…
3/ As @sneweyy reports, when new cases show up in previously unaffected regions, that is a sign contact tracing efforts may be failing.
4/ On Nov. 6th, two healthcare workers died and Ebola was listed as the probable cause.

As @HelenBranswell noted, the Uganda MoH is not including probable cases in their official count. These omissions provide a false sense of security.
5/ Data from @globaldothealth show that the rate of new cases has started climbing. Coupled with the spread to new districts, signs are pointing toward an outbreak that is getting out-of-control. Time series of case rate of...
6/ Reports from the MoH have become increasingly erratic and error prone over the past 10 days. Stopping the spread of Ebola requires high-quality data. It's clear that the MoH needs support.
7/

1. Cases in previously unaffected regions.
2. New healthcare worker deaths.
3. Emerging data problems.
4. Increasing case rates.

All point towards a much worse situation in Uganda and highlight the need for international collaboration to stop this outbreak!

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More from @svscarpino

Oct 17
1/ The XBB and BQ.1.1 variants are driving #COVID19 surges in many countries.

Using our @RockefellerFdn variant tracker, we’re able to gain more insight into what’s happening globally. A thread on what we’re seeing*.
2/ *As you may have noticed, our @ppi_insights twitter account is down (we're working on that), so the information I'm sharing is about a week old. I will tweet out updated data tomorrow.
3/ This week (Oct. 10th) there were enough XBB variant genomes to estimate its growth rate.

Unfortunately, XBB looks even more concerning than BQ.1.1.

And it’s only a matter of time before these variants spread to more countries. Map shows the model-estimated prevalence of the XBB variant.
Read 12 tweets
Oct 7
The science team @PPI_Insights has a new model for tracking #COVID19 variants.

tl;dr - we're worried about BQ.1.1 & expecting a surge in the coming months.

@TRyanGregory @HelenBranswell @EricTopol @firefoxx66 @angie_rasmussen @cmyeaton @g0ingmad @sciencecohen @jessicamalaty 1/6
Unlike BA.4.6 and BA.2.75.2, we are seeing signs of growth in #COVID19 cases where BQ.1.1 is also growing in prevalence. 2/6
We’re also closely monitoring the situation with the recombinant variant XBB & will have more to say about it next week.

Right now, there are only ~200 genomes on @GISAID, w/ 60% from Singapore, meaning global growth estimates are as yet unreliable. 3/6
Read 6 tweets
Apr 15
1/ It may sound crude, but, did you know that last year's Noble Prize in physics was awarded for using the "ask your friends if they're sick" method to study complex systems? 🤯🤯🤯

And, that asking your friends is provably the optimal strategy for assessing infection risk. A 🧵
2/ In 1985, Giorgio Parisi [2021 co-Nobel Laureate in Physics] and colleagues published a new method for studying spin glasses*.

Now called the "cavity method," it's closely related to Judea Pearl's "belief propagation." Abstract for Judea Pearl's ...Abstract for Mezard et al. ...
3/ *spin glasses are a hot mess.

And I literally mean that!

At non-zero temperatures they are highly disordered, far-from-equilibrium systems.

aka hot messes

Like epidemics and life on Earth : ) en.wikipedia.org/wiki/Spin_glass
Read 19 tweets
Apr 3
1/ You've probably heard that some key #COVID19 data systems are scaling back. But what does that mean for our ability to respond?

As I told @carlzimmer, "right as things get hard, we’re dialing back the data systems." 🧵 nytimes.com/2022/04/02/hea…
2/ Back in 2020, #COVID19 was pretty straightforward.

Yes, behavior, social networks, etc. were changing rapidly, but there was no immunity & only one variant.

@MOUGK, @EvolveDotZoo, et al. & I showed how to model this using data from @globaldothealth.
3/ It was also true that we needed to account for super-spreading, which we think is still largely under-appreciated.

Work w/ @LHDnets, @all_are, @BMAlthouse, and many other amazing colleagues.
Read 15 tweets
Jan 13
How fast will #Omicron drop after peaking? Turns out, it's not so obvious. A thread on the shape of epidemics. 1/25
You might think that if an epidemic curve goes up quickly, then it will come down quickly. We (@LHDnets, @all_are, & me) did too. And, it can! For example, replacing sick workers can drive accelerating disease spread and decline. 2/25 nature.com/articles/nphys…
Our intuition is that this worker replacement effect is a BIG deal for the isolation time debate. The tl;dr of the @NaturePhysics paper above is that the local social network matters A LOT & how exactly we replace workers matters A LOT. More soon on this. 3/25
Read 25 tweets
Jan 12
Last week I told the @BostonGlobe models showed a #COVID19 peak in 1-2 weeks (i.e. later this week or next). The data are consistent with a peak happening now, but, the Globe picked a different forecast for their headline. 🤦‍♂️ 1/6 bostonglobe.com/2022/01/12/nat…
Wastewater data are peaking in Boston. However, as @davidlazer mentions we’re still *way* above record highs & hospitalizations will continue rising after cases peak. So things will get worse healthcare-wise. Masking & testing are vital now. #wastebeforecase @BiobotAnalytics 2/6
Cases are falling in DC, but because of surging hospitalizations that will continue to rise, the mayor has rightly implemented new emergency measures. 3/6 nbcwashington.com/news/coronavir…
Read 6 tweets

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