Sam Abbott
@seabbs.bsky.social
1.4K followers 690 following 620 posts
Real-time infectious disease modelling. Developing methods for outbreak response, surveillance, and pandemic preparedness. samabbott.co.uk Come join me on the epinowcast forum: https://community.epinowcast.org/latest
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Reposted by Sam Abbott
adamjkucharski.bsky.social
Want to build an interactive dashboard so others can explore epidemic scenarios? For COVID, @ngdavies.bsky.social spearheaded a great drag-and-drop approach, which made use of the JavaScript-based nature of RShiny... 1/
Reposted by Sam Abbott
jmschreiber91.bsky.social
Now that I'm settled in at @umasschan.bsky.social, I'm hiring at all levels: grad students, post-docs, and software engineers/bioinformaticians!

The goal of my lab is to understand the regulatory role of every nucleotide in our genomes and how this changes across every cell in our bodies.
seabbs.bsky.social
This is really encouraging as I thought my 6 month turn around time for email was just a little slow but clearly I am above average!
seabbs.bsky.social
One of the fun things about being in the redundancy process at LSHTM is they put you on the redeployment register.

Currently, I am getting a strong message I am suited to a project management role.
Reposted by Sam Abbott
seabbs.bsky.social
here I specifically mean in pandemic prep stuff etc that I work on
seabbs.bsky.social
For a long time I thought this would be a place where the "effective" funders would step in as the potential for massive leverage is so obvious but they really do not seem interested (probably need to rebrand to AI safety)
seabbs.bsky.social
(why does no one fund software properly... cry whine sad face sit in the corner and sulk)
Reposted by Sam Abbott
rmcelreath.bsky.social
Are we doing simulations wrong? This paper convinced me we are. doi.org/10.1098/rstb... Usually we run 2 sets of "worlds" w and w-out intervention. Gives large uncertainties that include negative (harm) effects of interventions that are actually always positive (beneficial)!
Figure 5. Time series showing cumulative number of cases averted at each time caused by the intervention calculated using our method (single-world) and a
standard method. Shaded regions denote 90% confidence intervals. Note that there is more variation in the middle of the epidemic, so it may seem as though the
number of cases averted is large during those times. (Online version in colour.)
Reposted by Sam Abbott
dchodge.bsky.social
Just launched an interactive Bayesian epidemic modelling platform that runs entirely in your browser!

No downloads, no installations, no expensive software licenses. Just open the link and start modelling disease dynamics with real-time parameter estimation.

>> widget-bayesian-sir.davidhodgson.me
Interactive Bayesian Epidemic Modelling
widget-bayesian-sir.davidhodgson.me
seabbs.bsky.social
There is definitely a deployment of it somewhere they are using for teaching but you know Imperial
seabbs.bsky.social
Also either you or your LLM is much too cheery for me! I have been liking sonnet 4.5 its terse grumpiness is much more me
seabbs.bsky.social
Given their developer shake up I also don't know what the status of this project is
seabbs.bsky.social
No live version I can find. They have coded it to need a server for pulling the models form (i.e. so it can do any model) and then its in the browser but it feels like they missed a trick to make a self contained deployable one with static models like you have.
seabbs.bsky.social
Yes, using webR and a similar stack from what I can tell. I saw it at the workshop earlier this year - they have got great feedback using it for teaching so I definitely see the value especially for the serology stuff which is hard to get without playing.
seabbs.bsky.social
This is really cool @dchodge.bsky.social - how does it compare to the wasm stuff they have been doing with ODIN do you think? I would be keen to read a blog post along those lines...
seabbs.bsky.social
This is today at 3pm uk time. As a change of pace I think there will be a fairly heavy #julialang component
seabbs.bsky.social
For this weeks #epinowcast seminar at 3pm UK time online we have Sandra Montes speaking about dynamic survival analysis and optimal control policy for infectious disease modelling.

www.epinowcast.org/seminars/202...
Sandra Montes - Optimisation and Dynamic Survival Analysis: Towards a Toolkit for Epidemic Preparedness – Epinowcast
Epinowcast community site
www.epinowcast.org
Reposted by Sam Abbott
dchodge.bsky.social
🚀 New tool: Reversible Jump MCMC running in your browser!
Built an interactive widget for fitting mixture distributions when you don't know how many components you need.

Check it out: dchodge.github.io/rjmc-widget-...
Dynamic Mixture Model Analysis
dchodge.github.io
Reposted by Sam Abbott
adrianhill.de
Perfect timing! If you are in Paris for @juliacon.bsky.social on Friday, join us for our talk on Automatic Sparse Differentiation at 11:30.

If you can't make it, check out both the paper and our introductory ICLR blog post: iclr-blogposts.github.io/2025/blog/sp...
seabbs.bsky.social
that I’m aware of
seabbs.bsky.social
This is mostly a joke I don’t have paywalled work.