A big thanks to @vcolizza.bsky.social and all co-authors @paolobosetti.bsky.social @lullaopatowski.bsky.social and Chiara Sabbatini. Happy to see this work finally out!
28.01.2026 17:34
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A big thanks to @vcolizza.bsky.social and all co-authors @paolobosetti.bsky.social @lullaopatowski.bsky.social and Chiara Sabbatini. Happy to see this work finally out!
These findings support synthetic matrices as a reliable, flexible, cost-effective operational tool for real-time epidemic modeling, and highlight the need for routine collection of age-stratified mobility data to improve pandemic response.
The model using synthetic matrices provided the best fit to hospital and serological data. The weekly update of synthetic matrices enabled smoother reconstructions of hospitalization trends during transitional phases, while empirical matrices required strong assumptions between survey waves.
While both sources captured similar temporal trends in contacts, empirical matrices recorded 3.4 times more contacts for individuals under 19 than synthetic matrices during school-open periods.
In this study, we systematically evaluate synthetic and empirical age-stratified contact matrices in France from March 2020 to May 2022, comparing contact patterns and their ability to reproduce observed epidemic dynamics.
Mobility-based synthetic contact matrices offer a promising alternative for real-time pandemic response modeling. How do they compare with traditional empirical contact matrices?
We address this question in our latest study, now published in Nature Communications ⬇️
doi.org/10.1038/s414...
Our work about extending contact matrices beyond age, accounting for socio-economic dimensions, is finally published! Here, we analyse social contact data in Switzerland. Happy to see this output from my research period at @ispm.unibe.ch w/ @calthaus.bsky.social
www.nature.com/articles/s43...
Our analysis of modelling practices, data use, and science-policy interactions during the COVID-19 pandemic is out on @eurosurveillance.org this week.
www.eurosurveillance.org/content/10.2...
Wonderful collaborative effort conducted in the context of mood-h2020.eu
Read the thread below 👇
Really great to see that our paper is now officially published in the latest #Eurosurveillance. As it was accepted with only minor edits, this earlier post still captures the key messages: tiny.cc/036u001.
📣 Call for Abstracts! 📣
Join us at BehEpi Satellite, part of CCS 2025 in Siena, Italy (Sept 3–5).
We’re exploring how human behavior influences epidemic dynamics.
🔗 More info and submission at: www.epicx-lab.com/behepi-satel...
📅 Deadline: June 13, 2025
#CCS25
Thank you! :)
Thank you for the interest in our work! We didn't have socioeconomic data for the contacts but only for the survey participants - that is why in the paper we develop a method to leverage this partial info and build a set of "candidate" expanded contact matrices
As the COVID-19 pandemic emergency receded, we systematically reviewed modeling practices, data provisioning, and sharing among the modeling teams in the MOOD European consortium
Our pre-print is finally out
www.medrxiv.org/content/10.1...
Check out the thread by @esthervk.bsky.social below👇
We have a new pre-print out, extending traditional age-stratified contact matrices using Swiss data, w/ Martina Reichmuth and @calthaus.bsky.social
"Individual-based and neighbourhood-based socio-economic factors relevant for contact behaviour and epidemic control" www.medrxiv.org/content/10.1...
Great work about synthetic contact matrices derived from mobility data by @lauradidomenico.bsky.social @paolobosetti.bsky.social @vcolizza.bsky.social and coauthors www.medrxiv.org/content/10.1...