Projects

Allocative efficiency in child nutrition


Optima Nutrition is a mathematical model of child nutrition written in the computer programming language Python.

The model tracks cohorts of children from birth to five years of age. It incorporates health effects including the incidence of diarrhoea, breastfeeding, and stunting due to poor nutrition.

Cost and coverage data for interventions targeting nutritional health are incorporated in the model to derive an optimal allocation of funding for the various intervention programs.

This project will involve applying the Optima model to a specific area of research or development, for example application in a specific country.

This research will require quantitative data analysis from a range of sources. For example, when applying the model in a country setting, the available data is often incomplete or may contain errors which must be identified and accounted for.

There will be opportunities to conduct mathematical and statistical analysis using Python.

The student may learn to write code to perform analyses to address research questions. They will interpret and present results, usually in the form of figures and tables.

There will also be opportunities to contribute to the general code base, and/or to the underlying mathematical model, as well as to produce policy documents and present findings.

Prospective students will be expected to have skills in quantitative data analysis as well as good communication skills.

A keen interest in developing mathematical modelling and programming skills is essential. Some background in applied mathematics, physics, computer science, economics, or public health is preferred.

Program

Staff Member

Contact Details

For any general enquiries relating to this project, please contact:

Burnet Institute

communications@burnet.edu.au

Telephone

+61392822111

Email

communications@burnet.edu.au