Despite major advances due to vaccination, hygiene and pharmaceutical interventions, infectious diseases continue to pose a serious threat to public health. Notable examples of epidemics during recent decades include the HIV epidemic, the SARS outbreak in 2002-04, the 2009 H1N1 influenza pandemic, and more recently Ebola. It is of utmost importance to understand how infectious diseases spread through populations, how the population structure influences the spread, and what disease control measures are effective.
The main themes were:
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Spread of epidemics on dynamic networks
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Near-critical epidemics
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Persistence of epidemics
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Spread of information and opinions
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Connecting mathematical models to real-life epidemics through data fitting
Mathematically, models of disease and information spread have a wealth of interesting features, and understanding them better will advance the field. Currently, health systems in developed nations are struggling under pressure caused by ageing populations and resource limitations. It is therefore imperative to reduce the economic and human burden of infectious diseases as efficiently as possible, and modelling can play a key role in this optimisation
