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Infectious Disease Dynamics: Mathematical Modelling For Public Health
Isaac Newton Institute Open for Business Event - 5 June 2014 - Isaac Newton Institute, Cambridge

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Background

Infectious diseases have a major impact on society through ill health and associated economic and social disruption. Mathematical modelling however plays an increasingly important role in helping to guide the most high impact and cost-effective means of achieving public health goals.

Public health programmes are usually implemented over a long period of time with broad benefits to many in the community. Clinical trials are seldom large enough to capture these effects. Observational data may be used to evaluate a programme after it is underway, but have limited value in helping to predict the future impact of a proposed policy. Furthermore, public health decision-makers are often required to respond to new threats, for which there is little previous data. Computational and mathematical models can help to assess potential threats and impacts early in the process, and later aid in interpreting data from complex and multi-factorial systems. Models can also be used to guide new policy for old diseases, such as when a new vaccine becomes available. As such, models can be critical tools in guiding public health action across a range of areas. However, there are a number of challenges in achieving a successful interface between modelling and public health.


Objectives

This Open for Business half day event was part of a programme of events held at the Isaac Newton Institute during the 2013/14 Programme on Epidemic Modelling.

This workshop aimed to highlight fundamental problems inherent in modelling specific diseases and their public health impact. It brought together mathematicians, statisticians, epidemiologists, biologists and ecologists as well as policy makers/government, health managers, NGOs, funding agencies and industry.

Talks explored various models to inform public health decisions and to help analyse where and why models fail in their predictions. There was also an overview of potential future research and the main challenges both in understanding and public health needs and in methodology.

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