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Post-doctoral Researchers

Dr Helen McAneney


Dr Helen McAneney

Helen McAneney

Academic background

MSci Mathematics, Queens University of Belfast, 2001.

PhD (Theoretical Physics within the area of Quantum Information Theory), Queens University of Belfast, 2005.

Complexity Summer School, The University of York, 2009.

Research Fellow (Medicine), 2005 - Present

Associate member of the Institute of Physics, a member of International Network for Social Network Analysis and the UK Social Network Analysis and sits on the Centre of Excellence for Public Health (NI) Knowledge Brokerage committee.


Area of research

Co-investigator on the recently awarded NPRI Research Grant, Physical Activity and the Rejuvenation of Connswater (the PARC Study).


Network Analysis for Public Health Research and Knowledge Transfer

*The techniques of social network analysis allow the user to observe and investigate the role of actors (nodes) given their connections (ties) within a given system. For instance, questions such as ‘who is the most central/important person in the network?’ can be addressed. This can have important public health implications, for instance in the spread of a contagion or the transfer of knowledge within an organisational structure.


*In collaboration with Jim McCann, Lindsay Prior, Jane Wilde and Frank Kee, work has been carried out on the internal and external connections and relationships within the Centre of Excellence for Public Health based at Queen’s University, Belfast to address the need to build capacity in public health research and to ensure better mechanisms for translating evidence into practice. Using results obtained from 98 respondents from 44 organizations and research clusters we have been able to assess the expectations, goals, and network connections of the respondents. Analysis of data on participant expectations and personal goals suggest that the academic members of the network were more likely to expect the work of the Centre to produce new knowledge as compared to non-academics, but less likely to expect the Centre to generate health interventions and influence health policy. Academics were also less strongly oriented than non-academics to knowledge transfer as a personal goal, though more confident that research findings would be diffused beyond the immediate network. A social network analysis of our data suggests that a central core of around 5 nodes is crucial to overall configuration of the regional public health network in Northern Ireland, and that whilst the overall network structure is fairly robust, the connections between some component parts of the network need to be addressed and worked upon.


Infection and Epidemic

*The control of infection is a major challenge in Public Health: hospital-acquired infection and flu epidemics, for example. But how should we intervene to inhibit the growth and transmission of infection? Helen McAneney, in collaboration with Frank Kee and Jim McCann has developed mathematical and computational tools that simulate the complex evolution of infection within a social network. Mathematical models are not new; the pioneering work of Kermack and McKendrick in 1927, showed how a set of nonlinear differential equations could explain the onset of epidemics. However, these simple models of infection neglect the random nature of infection transmission, immunity, and the interactions within a social group by assuming homogeneous mixing. This implies is that each person in the population can with equal probability infect another person, regardless of any spatial aspects of how infection can spread. This unrealistic assumption was required because of the lack of computational power to crunch the numbers. Modern techniques, such as Agent-Based models, allow us to simulate the dynamic of infection where the full complexity of the process can be included.


*As an example of our techniques in action, consider an acute-care hospital ward and the control of MRSA and C. diff. In our model, we take into account infection reservoirs (contamination of the physical environment) and infection vectors (contact with staff and visitors) as well as the risk profile of the patients. Part of our work is to study the significance of hygiene, patient screening, and isolation in the containment/elimination of hospital-acquired infection. This is only one example. This type of modelling procedure can be generalised to other infectious diseases in which one wishes to consider the spatial aspects of infection spread.


Chief Investigators

Frank Kee, Lindsay Prior, Jim McCann & Jane Wilde