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EAU’s disease modelling lab is hosting it’s first workshop of mathematical modelling, specifically on infectious diseases. The NYU team will be conducting an engaging and comprehensive 3 day workshop on mathematical modeling, delving into various aspects of disease outbreaks. The workshop commenced with a thorough exploration of disease outbreak data, emphasizing the significance of understanding real-world scenarios. Participants will be introduced to scientific computing, honing their skills in using R and Python. A substantial portion of the workshop will focus on the modeling process itself, with hands-on exercises employing the SI and SIR models. Mathematical properties of the SIR model will be meticulously discussed, accompanied by exercises that allow participants to explore the model's behavior and comprehend the basic reproductive number. The NYU team will also guide participants through fitting models to real-world data, providing valuable insights into the practical implementation of theoretical concepts. The workshop will further address counterfactuals and interventions, allowing participants to model treatment scenarios using the SIR model. Additionally, the team will offer diverse topics for individual or group projects to present as posters at the end off the 3 day workshop. The topics include paper-writing, extending SIR models to include more details, modeling other diseases like malaria, introducing stochasticity and randomness, and exploring advanced model fitting techniques. The workshop fosters an environment of collaborative learning, enabling participants to acquire a comprehensive understanding of mathematical modeling in the context of disease outbreaks.

Dates: February 2nd-February 4th

Times: Friday start time is 9:00am, Saturday and Sunday start time is 10:00am.

Registration deadline: January 29th 2024

How to register: Send an email to with your full name

Cost: Free

Biography - Professor Anna Bershteyn

Anna Bershteyn is an Associate Professor of Population Health at the NYU Grossman School of Medicine in New York City. Her lab uses simulation science to inform public health decision-making at the interface of infectious diseases and other high-burden health risks. She collaborates with local public health agencies, health authorities in several countries (eSwatini, Kenya, Malawi, South Africa, Tanzania, Zambia, Zimbabwe), and international agencies such as the World Health Organization.

Biography - Daniel Citron

Daniel Citron is a senior research scientist at NYU Grossman School of Medicine. He specializes in mathematical models of infectious disease dynamics, with a current primary focus on using agent-based modeling tools to produce long-term forecasts of the HIV epidemic in sub-Saharan Africa. His prior work includes mathematical models of spatial transmission of malaria, and measuring epidemiological mixing patterns using mobile phone app data.