# Epidemics: emergence, elimination, seasonality

• Applications accepted all year round
• Awaiting Funding Decision/Possible External Funding

## Project Description

The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2016 (funded students) or at any point in the academic year (self-funded students).

In an SIR epidemic model, an infectious disease spreads through a population where each individual is either susceptible, infective or recovered. The population is represented by a network (graph) of contacts, where the vertices correspond to individuals and the edges correspond to potential infectious contacts. Different individuals have different patterns of activity, leading to different numbers of contacts. The degree of a vertex is the number of contacts of the corresponding individual. The basic reproductive ratio is the key quantity for such a model, calculated from the model parameters such as the transmission rate, recovery rate, and the average number of contacts of an individual. It is the average number of secondary cases resulting from one case of a disease and determines the speed of epidemic progression in the early stages.

Emergence of new diseases and elimination of existing diseases is a key public health issue. In an SIR epidemic model and other types of mathematical models of epidemics, such phenomena involve the process of infections and recoveries passing through a critical threshold where the basic reproductive ratio is 1. For example, a pathogen mutation can increase the transmission rate and make a previously ‘subcritical’ disease (i.e. not infectious enough to cause a large outbreak) into a ‘supercritical’ one, where a large outbreak may occur. A closely related issue is seasonality of certain diseases (e.g. malaria), and how the basic reproductive ratio increases above 1 at certain times of the year, and then decreases below 1 during others. Various interventions (e.g. mosquito spraying in the context of malaria or dengue fever) can also affect the basic reproductive ratio in similar ways.

This project will explore mathematical models of disease emergence, elimination and seasonality. This project would be supervised jointly by Jamie Griffin and Malwina Luczak.

Further details can be found in the project abstract: http://www.maths.qmul.ac.uk/sites/default/files/phd%20projects%202015/Prob/PhDproject-3.pdf

The application procedure is described on the School website. For further enquiries please contact Prof. Malwina Luczak ().

This project is eligible for several sources of full funding for the 2016/17 academic year, including support for 3.5 years’ study, additional funds for conference and research visits and funding for relevant IT needs. Applicants interested in the full funding will have to participate in a highly competitive selection process. The best candidates will be eligible to receive a prestigious Ian Macdonald Postgraduate Award of £1000, for which you will be considered alongside your application. The application deadline for full funding is January 31st 2016.

There is also 50% funding scheme available for students who are able to find the matching 50 % of the cost of their studies. Competition for these half-funded slots will be less intensive, and eligible students should mention their willingness to be considered for them in their application. The application deadline for 50 % funding is January 31st 2016.

This project can be also undertaken as a self-funded project, either through your own funds or through a body external to Queen Mary University of London. Self-funded applications are accepted year-round.

## Funding Notes

If you wish to apply, please visit the application website and mention that you wish to work on the “Epidemics: emergence, elimination, seasonality” project.

School website: View Website

## How good is research at Queen Mary University of London in Mathematical Sciences?

FTE Category A staff submitted: 34.80

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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