Name: Modeling infectious disease
Start: 2023-04-22T12:00:00-04:00
End: 2023-04-22T14:00:00-04:00

**R-Ladies NYC & R-Ladies Rome** are coming together for a joint event.

In this talk, we will delve into the fascinating world of modeling diseases with R using both deterministic and Bayesian methods while exploring the exciting insights that each approach has to offer.

At the heart of our discussion is the well-known SIR (susceptible-infected-recovered) model. This model can help us understand how an epidemic might unfold and what measures can be taken to prevent its spread.

So, do not miss this fascinating talk about modeling infectious diseases. Whether you are a student of science, a healthcare professional, or simply someone who wants to understand more about how to use R for modeling diseases, this talk promises to be insightful!

**Schedule of the event:**

* Introduction presentation of the Chapters and [R-Ladies Global](https://www.linkedin.com/notifications/?filter=all#) action
* SIR model with R - quick intro assessment (Speaker [Federica Gazzelloni](https://www.linkedin.com/notifications/?filter=all#))
* Bayesian workflow for disease transmission (Speaker [Jacqueline Buros Novik](https://www.linkedin.com/notifications/?filter=all#))
* Q&A session

\-\-\-\-
Si parla di malattie infettive. In questo talk, approfondiremo l'affascinante mondo del modeling delle malattie, ed esploreremo le entusiasmanti intuizioni che questo campo ha da offrire. Al centro della nostra discussione c'è il noto modello SIR, questo modello può aiutarci a capire come potrebbe evolve un'epidemia, discuteremo su possibili modi di calibrare i modelli, e quali misure possono essere prese per prevenirne la diffusione.
Quindi, non perdere questo meetup! Che tu sia uno studente di scienze, un professionista sanitario o semplicemente qualcuno che vuole capire di più su come usare R per applicare i modelli per le malattie infettive.

Jacki Buros

R-Ladies Global

Dorota Rizik

R-Ladies New York

R-Ladies

Technology

Open Source

Women Programmers

Education & Technology

Data Analytics

Data Visualization

Computer Programming

Big Data

Data

**Jacqueline** is an applied Bayesian statistician who has been working in biostatistics and bioinformatics for over 15 years. She is not an infectious disease specialist, however she has a keen interest in Bayesian analysis and making model results interpretable. Her career starting in cardiology research at the TIMI Study Group at Harvard Medical School before working in Alzheimer’s Disease genetics at Boston University and in biomarker discovery for cancer immunotherapies at the Hammer Lab and at the Institute for Next Generation Health Care at Mount Sinai. She is the author of the survivalstan package and a contributor to the rstanarm package. She is currently Head of Data and Analytics at Generable, Inc.

Meet **Federica**, a statistician and actuary who works as an independent researcher. She is interested in infectious diseases and spatial data with R. Author of the package **Oregonfrogs** where she shares her insights and experiences on data analysis and visualization. She is also working on an insightful book about **Health metrics and the spread of infectious diseases with machine learning applications and spatial model analysis** which include a packaged namely **infectious**. Eventually, she has reviewed various articles in her field. She is always open to learning new insights about data visualization and is an enthusiast of the R programming language.

**R-Ladies is dedicated to providing a harassment-free experience for everyone. We do not tolerate harassment of participants in any form. Please take a moment to review the R-Ladies Global code of conduct (particularly if this is your first time attending): [https://rladies.org/code-of-conduct](https://rladies.org/code-of-conduct). For questions regarding accessibility, please email nyc@[rladies.org](http://rladies.org/).**

R-Ladies New York

Modeling infectious disease

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