# Updated preprint: Bayesian workflow for disease transmission

**URL:** <https://discourse.mc-stan.org/t/updated-preprint-bayesian-workflow-for-disease-transmission/20706>\
**Category:** Publicity\
**Created:** [February 9, 2021, 3:42pm UTC](https://discourse.mc-stan.org/t/updated-preprint-bayesian-workflow-for-disease-transmission/20706 "2021-02-09T15:42:55Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![charlesm93](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/charlesm93/32/4634_2.png) [@charlesm93](https://discourse.mc-stan.org/u/charlesm93)\
**Post date:** [February 9, 2021, 3:42pm UTC](https://discourse.mc-stan.org/t/updated-preprint-bayesian-workflow-for-disease-transmission/20706/1 "2021-02-09T15:42:55Z")

</div>

Dear Stan Community,  
I’m excited to share an updated version of the Bayesian workflow for disease transmission case study we wrote last year, co-authored by @LeoGrin, @Elizaveta_Semenova, @jriou and myself. We’ve polished the existing material and added a section on a model which uses Covid-19 data, the many potential pitfalls when building such models – and some strategies to overcome them.

> **[Bayesian workflow for disease transmission modeling in Stan](https://arxiv.org/abs/2006.02985)**
>
> This tutorial shows how to build, fit, and criticize disease transmission
> models in Stan, and should be useful to researchers interested in modeling the
> SARS-CoV-2 pandemic and other infectious diseases in a Bayesian framework.
> Bayesian modeling...

---

<div class="post-metadata">

**Author:** ![JimBob](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/jimbob/32/19329_2.png) [@JimBob](https://discourse.mc-stan.org/u/JimBob)\
**Post date:** [February 9, 2021, 4:37pm UTC](https://discourse.mc-stan.org/t/updated-preprint-bayesian-workflow-for-disease-transmission/20706/2 "2021-02-09T16:37:21Z")

</div>

Thanks @charlesm93 - looking forward to digging into it and seeing how these sort of models are developed