In order to do so, it is important to take into account not only the biology of infectious agents, but also many other aspects of disease transmission such as networks of human social contacts and global travel, and the adaptation of bacteria and viruses to treatment.
Mathematical models of epidemics have recently been instrumental in reducing incidence and eradicating several serious diseases. In 2007, for example, extensive mathematical modeling, performed by the UK's Health Protection Agency, led to the introduction of a preemptive HPV (human papilloma virus) vaccine against cervical cancer for 12-year old girls. A large number of mathematical simulations had shown this to be the most effective way to minimize the transmission of HPV and the occurrence of cervical cancer.
An international workshop on the Mathematical Modelling of Epidemics will be hosted by the University of Bristol on the 15th and 16th September, bringing together world experts on using mathematical methods to model the dynamics of infectious diseases.
They will discuss state-of-the-art techniques currently being developed and used to analyse the dynamics of various emerging infections, as well as the development of appropriate measures for treatment and containment of such diseases.
The organiser, Dr Konstantin Blyuss from the University of Bristol, said: "To fight infections in the 21st century, we have to use all available resources. Mathematical models of epidemics provide that extra power to help in this fight. I am delighted to be able to host a meeting on such an important and topical issue."
The topics to be covered by the workshop include:
- Emerging Infections: things we know and things we don't know about the dynamics of HIV and influenza, presented by Professor Angela McLean, FRS, Director of the Institute for Emergent Infections of Humans, University of Oxford
- The H1N1 (swine flu) pandemic in the UK presented by Dr Marc Baguelin, Health Protection Agency
- A range of talks on the mathematical modelling of the spread of infectious diseases in social networks