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Home - Mathematics for Environment and Sustainability

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Welcome to our showcase of assignments by University of Exeter students who are studying ‘Mathematics for Environment and Sustainability’. You can see examples of past students’ work, and what students are up to now, on the following webpages:

The below information provides details on what is likely to be covered within our module:

Infectious Diseases

The ongoing COVID-19 pandemic has brought the study of infectious diseases to the forefront of public perception.

This theme will explore fundamental topics in infectious disease epidemiology using differential equation and network based models of disease transmission. This will be used to investigate the influence of transmission, recovery and mortality rates on the spread of infectious diseases, and the effects of public health interventions such as social distancing, quarantining and vaccination on the outbreak of epidemics.

Social and Ecological Systems

Individual opinions on various societal challenges are formed within social networks. Opinions spread and can heavily influence how communities develop solutions for these challenges. Also, the outcome of an individual’s decisions will depend on the decisions of others. Depending on the circumstances, this can lead to either competitive or cooperative behaviours.

Similarly, competitive and cooperative behaviours emerge in ecology as a result of natural selection.

This theme explores mathematical modelling (e.g., agent-based models/ game theoretic models) in the context of social and ecological systems, and applies these to understand and simulate social network behaviours and or cooperation and competition in an ecological setting.

Optimisation in the Renewable Energy Economy

The renewable energy economy necessary to address the climate emergency contains large upfront and maintenance costs. Faced with depleting non renewable resources, it is important to invest now in energy infrastructure to provide clean energy for many decades to come. In this theme, mathematical optimisation is applied to optimal decision making in this context.

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