Francesco Di Lauro

Oh io dovrei pure essere in patria, quasi quasi

I have been going through the same path and outcome for an early career grant, so I feel you 100%.

Its diet consists of fruit, plants, small woodland animals, large woodland animals, woodlands, fruit groves, fruit farmers, and small cities.

Every time I fly back home

The network is bipartite (only heterosexuals people were interviewed) and the enrolled partners were not asked to nominate their partners, but just to enumerate them, so I am afraid the observations stop there.

Community structure could be looked at instead, as we ask where people live.

Thanks! 🙏

The data comes from a sexual health questionnaire + some contact tracing, where they tried to enroll as many contacts of the indexes as possible. These people were also given the same sex questionnaire.

The questionnaire asks about sexual behaviour, number of partners over a year, risky behaviour..

I have individual-level data on people + their sexual contacts.
It is easy to look at age/sex mixing. But from a network perspective,I can also study assortativity in number of reported partners.

Anything else that I can check? Thinking of excess degree distribution and age/sex dynamics consistency

Congratulazioni 🎉

Thank you 🙏

UCL – University College London UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).

Belated intro post: Hi, I'm Liz, interested in social influences on infectious disease dynamics, particularly in sexual health and always in the interests of health equity. We are looking for an ID modeller postdoc to work on co-production of epidemic models: join us! tinyurl.com/24ze4x5c

Position with @mert0248.bsky.social and me in modelling the potential impact of next generation flu vaccines: iddjobs.org/jobs/modelli...

I am followed by so many infectious disease modellers that I am now afraid of even using the word SIR, in any context 😅

A list of bands in order of efficacy:

3. Placebo
2. The Cure
1. Prevention

🇮🇹 Da oggi comincia l'avventura di @comunelab.bsky.social e il nostro modello predittivo per #influenza A/B/ILI 🦠🧪 su dati ISS, come parte dell'hub nazionale #influcast🇮🇹: influcast.org

Congratulazioni a @tommasobertola.bsky.social per questo 1° significativo traguardo del suo progetto.

1/

Static network structure cannot stabilize cooperation among Large Language Model agents Large language models (LLMs) are increasingly used to model human social behavior, with recent research exploring their ability to simulate social dynamics. Here, we test whether LLMs mirror human beh...

Manlio, this went out literally now 🤣

"Are LLMs about to emulate human behavior in cooperative dilemmas on networks? These results highlight a crucial gap: LLMs struggle to emulate the nuanced, adaptive social strategies humans deploy in fixed networks"

arxiv.org/abs/2411.10294

Utilizing large language models in infectious disease transmission modelling for public health preparedness OpenAI's ChatGPT, a Large Language Model (LLM), is a powerful tool across domains, designed for text and code generation, fostering collaboration, esp…

www.sciencedirect.com/science/arti...

arxiv.org/abs/2307.04986

There is also some code to it

github.com/bear96/GABM-...

There's already a number of papers on arxiv showing that it "kind of" works. I personally think that there's a number of big problems to address

1) reproducibility
2) the need of "small" language models if you have one specific population (culture/religion...)
3) scalability
4) what do you "fit"?

Tangential to this: when using agent-based models, e.g. to simulate epidemics, would you replace a set of simple, mechanistic rules that you coded/control yourself, with a set of LLM agents that exhibit much more complex behaviour? (let's forget about the reproducibility issue with LLM for now)

Following up on this because it is quite fascinating

Wooooooow ben ritrovata!

I wonder why it is centered around a 1000, and if it has moved in the last few months.

If you have the feeling that @bsky.app is different, maybe you are right.

The current migration is breaking the typical rich-get-richer effect wrt other platforms #scaling

Data:

Twitter: 10.9M users
BlueSky (Mar 2024): 4.1M users, 🙏 @andreajpg.bsky.social
Mastodon: 3.8M users, 🙏 @tiago.skewed.de

1/ Hello, BSky community! 👋
I’m an incoming Wellcome Trust Early Career Fellow & Group Leader at the University of Oxford. My research focuses on the molecular evolution of pathogens, especially viruses with pandemic potential. You can find out more about our work here: users.ox.ac.uk/~univ4613

"The first lesson of all was the basic trust that he could learn. It is shocking to find how many people do not believe they can learn, and how many more believe learning to be difficult"

Sono più nell'infectious disease modelling che nell'epi applicata, ma consiglierei questo starter pack qui

bsky.app/profile/scau...

Quando ero meno applied, in un paper avevamo usato l'idea che la dinamica di un SIR/SIS a livello di popolazione "somiglia" a un birth death process per fare inferenza, quindi quando è uscito l'articolo abbiamo aperto una discussione sui limiti e le proprietà di tale approssimazione...

Sì faceva strano anche a me, credo sia un miscuglio del fatto che parecchi articoli nel campo più applied usino metodi molto standard, quindi è interessante mostrare i risultati e discuterne le implicazioni. Articoli "meno applied" spesso si basano invece su una intuizione interessante da spiegare

Is it difficult to check for assortativity? I would expect it to be low, IIRC...

Preliminary #scaling of the number of followers vs the number of follows in @bsky.app from a random sample of about 20,000 users.

This is ~linear (provided this sample is representative), while it was very different for Twitter, or am I wrong? @emilioferrara.bsky.social @estebanmoro.bsky.social

Based on rich gets richer I ma surprised, it doesn't seem to work too well on here? I wonder what's the size of the network at which a similar effect is expected to happen...

A me a questo giro pare davvero definitiva la cosa. Nel campo mio (net science/infectious disease modelling/complex systems) oramai son qua le discussioni.

Comunque non c'è ancora la massa critica quello no.

(Ma se non altro non ci sono troppi asini che si sentono superiori e senza capire nulla)