The problems of understanding and controlling disease raise a range of
challenging mathematical and statistical research topics, from broad
theoretical issues to specific practical ones. In particular, recent i
nterest in acquired immune deficiency syndrome has stimulated much pro
gress in diverse areas of epidemic modelling, particularly with regard
to the treatment of heterogeneity, both between individuals and in mi
xing of subgroups of the population. At the same time better data and
data analysis techniques have become available, and there have been ex
citing developments in relevant theory, ranging from random graphs and
spatial stochastic processes to the structural stability of differenc
e and differential equations. This progress in specific areas is now b
eing matched by interdisciplinary co-operation aimed at elucidating re
lationships between the widely varying types of model that have been f
ound useful, to determine their strengths and limitations in relation
to basic aims such as understanding, prediction, and evaluation and im
plementation of control strategies. Such interdisciplinary work can be
expected to make major contributions to the modelling of a wide range
of human, animal and plant diseases, as well as to general statistica
l and biomathematical theory.