Using mathematical models to reduce malnutrition among children

Malnutrition is responsible for over three million child deaths each year with 36 countries carrying the bulk of the burden. There are proven community-based interventions to target malnutrition; however, resources are limited, so funds must be allocated to programs that achieve the maximum impact. Optima Nutrition is an allocative efficiency model that quantifies the benefits of providing nutrition-based interventions to children under-five. The model incorporates risk factors for malnutrition including the incidence of diarrhoea, breastfeeding, stunting, wasting and anaemia. 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 prefe