We are currently entering a new technological era in which we are able
to build systems whose performance is limited by quantum physical
effects and in which it may be possible to exploit non-classical
phenomena in novel ways. This is reflected in the considerable recent
interest in engineering quantum systems and at the heart of this is the
development of a quantum control theory dedicated to extending classical
control to the quantum domain. Examples already utilising control of
one sort or another include quantum electromechanical systems, quantum
dots, cooper-pair boxes, superconducting interference devices, ion
traps, as well as a large selection of optical devices.

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.