Developing mechanistic models of infectious disease transmission
Emma Knox
Undergraduate Researcher
Epidemiology Major (School of Public Health)
Ana Bento
Faculty Mentor
Ana Bento (School of Public Health)
Project Description
This will entail training in developing the mathematical models and learning to code them either in R, python or C. Also training in visualization and data driven analysis of cases reports. The students will learn how to develop such mechanistic models calibrated with real data. They will also have hands in training in coding these models for simulations and fitting models to data. Also students will develop skills in data visualization. This will be to work either on shistosomiasis (Senegal project) or COVID-19 related projects. Also some projects looking at the consequences of covid -19 on other vaccine preventable diseases (eg. mumps measles and whooping cough).
Technology or Computational Component
All the work in the lab is computational. Students will learn theory behind the nature of the models and also coding skills to run simulation studies. There will be a component of data science in which students will be taught to clean data and explore paralel data streams including epidemiological data, movement data, genomic data and sócio demographic spatial data. Students with some knowledge of r, python or c will have an easier start, although it’s not required