Epidemics: the Fitting of the First Dynamic Models to Data

摘要

Mathematical infectious disease epidemiology uses dynamic models with interpretable parameters like contact rates and recovery rates to describe individual epidemics and their periodicities. There is a vast literature, scattered in mathematical and recently also in physical journals, which is concerned with the stability of equilibrium points and the identification of threshold parameters for bifurcations. Most of these papers contain no empirical data at all. But for an applied science it is important to make predictions, which can be tested against observations. In view of my historic interests I shall concentrate on the first models, which have the advantage of being still simple while incorporating all the essential elements. Serfling (1952) concludes his historical review of epidemic theory as follows: "However, advance in epidemic theory depends also upon tests of hypotheses and a crucial test must be based on concrete and accurate data. In the past, these have been inadequate".