iiinova — where your digital self keeps evolving

Joseph Lemaitre @josephlemaitre.bsky.social · 22/01/2026

Really neat bit on Rt confidence (also loving the blog write-up, more edible than skimming the full paper)

Joseph Lemaitre @josephlemaitre.bsky.social · 14/11/2025

NHSN and other epi datasources back again. I imagine there is quite some work under the scene, thanks CDC folks we've been missing you.

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Sam Abbott @seabbs.bsky.social · 17/10/2025

#epinowcast 0.4.0 is out! This release has been a long time coming and contains work from many contributors. It includdes new features, better better and clearer documentation. package.epinowcast.org/news/index.h...

package.epinowcast.org

Changelog

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Joseph Lemaitre @josephlemaitre.bsky.social · 12/08/2025

just learnt that vs code recently added native git blame decorations with setting: "git.blame.editorDecoration.enabled": true good bye complex extensions, goodbye gitlens 👋

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Joseph Lemaitre @josephlemaitre.bsky.social · 15/07/2025

I've been sneaking on that course (by Sam Abbott, Thomas Robacker, Nick Reich) for the past few days on github (did not see the deployed version) and it is really good learning material for learning epi forecasting: nfidd.github.io/sismid/

nfidd.github.io

Nowcasting and forecasting infectious disease dynamics - SISMID – NFIDD SISMID

Nowcasting and forecasting infectious disease dynamics - SISMID

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Joseph Lemaitre @josephlemaitre.bsky.social · 11/07/2025

James does really great science ! This is a great job

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Dorothy Bishop @deevybee.bsky.social · 10/07/2025

Wow. This is an amazing project with a huge amount of work behind it. Even if you aren't into drosophila, it's worth a look

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Mark A. Hanson @hansonmark.bsky.social · 10/07/2025

But in fact, fly immunity is highly reproducible! 🎊 ~80% of claims could be verified. Moreover, some challenged claims just reflect the field advancing its knowledge/tools. The lesson: if the tools are good and the research largely exempt from direct translation pressures, science works. 3.5/n

A chart depicting the track of claims into verified, unchallenged, challenged, partially verified, or mixed.

Figure 1: Flow of the study.
Claims were first classified in five categories based on literature. 45 unchallenged claims were selected to be experimentally tested and
classified either as challenged or as verified. We further classify some unchallenged as consistent or inconsistent depending on their
consistency with current knowledge.

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Mark A. Hanson @hansonmark.bsky.social · 10/07/2025

When everything is considered together (w/ caveats), the most prestigious institutes are the most likely to produce irreproducible work. Journal tier was a more minor effect, and in fact, "high-impact" but not "trophy" journals publish the most reproducible science. But, many caveats (cont.) 4.3/n

A chart showing various factors and their odds ratios and relative contributions to irreproducibility in a multivariate mixed model.

Figure 10. Multivariable analysis of predictors of claim irreproducibility.
The forest plot reports the odds ratio and the 94% highest density interval of each covariate effect on
a claim becoming challenged.

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Richard Sever @richardsever.bsky.social · 02/07/2025

more than that but right order of magnitude. I always say $10^1 for preprint; $10^3 for journal article; $10^5 for research. most costs are staff not tech because of responsible screening, customer service, etc.

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Joseph Lemaitre @josephlemaitre.bsky.social · 30/06/2025

This opinion (LLMs have no world model) is repeated at every AI track in IDD conferences, and while it's true for a narrow definition of world model, I am sure it does not square with audience experience. Contrary to what Gary says, LLMs play good (1'800 ELO) chess: dynomight.net/more-chess/.

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Sam Abbott @seabbs.bsky.social · 07/05/2025

Which academic communities have a good record of sharing domain-specific open source tools? Bioinformatics and geospatial analysis comes to mind. I am trying to think about if they are examples to follow or if there is some difference in the domain (to Infectious disease modelling).

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Michael "Shapes Dude" Betancourt @betanalpha.bsky.social · 28/05/2025

Earlier this month I gave a workshop on Bayesian methods in epidemiology. With my hosts I developed a pretty elaborate, demonstrative analysis for the workshop which I am happy to share publicly here. HTML: betanalpha.github.io/assets/chapt... PDF: betanalpha.github.io/assets/chapt...

betanalpha.github.io

Bayes-by Shower

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Sam Abbott @seabbs.bsky.social · 29/01/2025

Note that one of these projects is about delay estimation (described by one 5 year old as double extra boring) but critical to get right for most/all downstream modelling use cases.

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Sam Abbott @seabbs.bsky.social · 22/01/2025

For a few years, I have been paying out of pocket for the epinowcast forum as I thought it was important to have a venue for people to collab. There is some great stuff kicking off at the moment which is lovely to see. community.epinowcast.org/t/include-a-...

community.epinowcast.org

Include a simple reference model

Baselines considered: no correction baseline (naïve but not realistically what epi colleagues would expect) cut off last few weeks and repeat the previous week(s) (i.e. thinking that the data will b...

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Joseph Lemaitre @josephlemaitre.bsky.social · 17/01/2025

This is a very interesting talk by @scarpino.bsky.social continuing the exploration of the predictability of an influenza season using fundamental and practical methods www.youtube.com/live/8RslYIn...

youtube.com

YouTube

Share your videos with friends, family, and the world

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Joseph Lemaitre @josephlemaitre.bsky.social · 07/01/2025

The deadline for the Epidemics special issue on Artificial Intelligence for Infectious Disease Dynamics has been extended to 30 April 2025, so there is still time to submit your paper 📝 Feel free to contact me or another guest editor for more information 😊 www.sciencedirect.com/journal/epid...

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Joseph Lemaitre @josephlemaitre.bsky.social · 06/12/2024

The studies informing stratified parameters in IDD models often have partitions (e.g age group) different from the model partitions. Most papers takes the median/mean estimates, but a correct solution exists: see this great paper/R pkg (C. Pearson, @lucygoodfellow.bsky.social @mert0248.bsky.social)

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Joseph Lemaitre @josephlemaitre.bsky.social · 19/11/2024

Very interesting write up on OWD pandemic work. In general, it’s always surprising how small most teams doing important thing are.

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Joseph Lemaitre @josephlemaitre.bsky.social · 14/11/2024

Just discovered this excellent book on genomics from Tanja Stadler et al. Free pdf offered here: decodinggenomes.org. The chapters I've read hit a biology/statistics sweet spot for me and probably other IDD researchers.

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