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12th Annual Workshop To Increase Diversity In Mathematical Modeling & Public Health

March 4 @ 8:00 am - March 5 @ 5:00 pm

Hosted by the Center for Communicable Disease Dynamics (CCDD) at Harvard T.H. Chan School of Public Health and MIDAS Coordination Center at the University of Pittsburgh

 

The Workshop to Increase Diversity in Mathematical Modeling and Public Health is an annual event for undergraduates or students in a post baccalaureate program from underrepresented groups who have an interest in public health and/or mathematical modeling, and are studying quantitative disciplines and/or public health at their home institutions. See eligibility requirements link below.

Infectious disease modeling is an exciting field whose practitioners study the mechanisms by which diseases spread, to predict future outbreaks, track current outbreaks, and evaluate methods to control an epidemic. Currently, CCDD and MIDAS members are using infectious disease modeling in the fight against the COVID-19 pandemic, including predicting the trajectory of the disease and communicating findings to policymakers and the public about strategies to slow disease spread, and illustrating how inequities result in increased risk and severity of disease, and strategies for promoting health equity across a population. Hear from some of the top experts in the field and their experiences during the pandemic!

During the workshop students get a brief introduction to the existing possibilities in mathematical modeling. Sessions will include introductions to computational tools, and scientific talks from public health researchers and trainees who use infectious disease epidemiology and mathematical modeling to solve problems in public health(They will also engage in professional development and networking opportunities, and participate in hands-on activities to practice the concepts and skills they are learning, including activities using the R programming language.

 

Eligibility Criteria:

This workshop exists to increase diversity in the fields of mathematical modeling and public health.

 

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