J. Gani - Böcker

This general introduction to the ideas and techniques required for the mathematical modelling of diseases begins with an outline of some disease statistics dating from Daniel Bernoulli's 1760 smallpox data. The authors then describe simple deterministic and stochastic models in continuous and discrete time for epidemics taking place in either homogeneous or stratified (non-homogeneous) populations. Several techniques for constructing and analysing models are provided, mostly in the context of viral and bacterial diseases of human populations. These models are contrasted with models for rumours and vector-borne diseases like malaria. Questions of fitting data to models, and their use in understanding methods for controlling the spread of infection, are discussed. Exercises and complementary results at the end of each chapter extend the scope of the text, which will be useful for students taking courses in mathematical biology who have some basic knowledge of probability and statistics.

Like many other scientists, I have long been interested in history. I enjoy reading about the minutiae of its daily unfolding: the coinage, food, clothes, games, literature and habits which characterize a people. I am carried away by the broad sweep of its major events: the wars, famines, migrations, reforms, political swings and scientific advances which shape a society. I know that historians value autobiographical accounts as part of the basic material from which the stuff of history is distilled; this should apply no less to statistical than to political or social history. Modem statistics is a relatively young science; it was while pondering this fact sometime in 1980 that I realized that many of the pioneers of our field could still be called upon to tell their stories. If, however, biographical material about these eminent statisticians was not gathered, then one might lose the chance to gain insight into the origins of many an important statistical development. The remarkable experience of these colleagues could not be readily duplicated. Fired by these thoughts, I took it upon myself to plan the framework of this book. In it, eminent statisticians (probabilists are included under this title) would be invited to sketch their lives, explain how they had become interested in probability and· statistics, give an account of their major contributions, and possibly hazard some predictions about the future of the subject.

This book brings together the personal accounts and reflections of nineteen mathematical model-builders, whose specialty is probabilistic modelling. The reader may well wonder why, apart from personal interest, one should commission and edit such a collection of articles. There are, of course, many reasons, but perhaps the three most relevant are: (i) a philosophicaJ interest in conceptual models; this is an interest shared by everyone who has ever puzzled over the relationship between thought and reality; (ii) a conviction, not unsupported by empirical evidence, that probabilistic modelling has an important contribution to make to scientific research; and finally (iii) a curiosity, historical in its nature, about the complex interplay between personal events and the development of a field of mathematical research, namely applied probability. Let me discuss each of these in turn. Philosophical Abstraction, the formation of concepts, and the construction of conceptual models present us with complex philosophical problems which date back to Democritus, Plato and Aristotle. We have all, at one time or another, wondered just how we think; are our thoughts, concepts and models of reality approxim&tions to the truth, or are they simply functional constructs helping us to master our environment? Nowhere are these problems more apparent than in mathematical model­ ling, where idealized concepts and constructions replace the imperfect realities for which they stand.