During the past decade epidemiology has developed beyond the simple desrip tion of ecological factors affecting disease. Population dynamics has become a major item of research, which in turn has prompted new approaches and philosophy. Though basically an empirical science, epidemiology has of necessity veered towards mathematical methods and modeling. The growing importance of epidemiology was acknowledged by the organizers of the 2nd International Congress of Plant Pathology, held in Minneapolis in September 1973. One of the symposia was devoted to a discussion of the role of mathematics and modeling in the analysis of epidemics. The speakers considered that it would be valuable to expand their contributions for publication. The following chapters give an outline of the record of achievement to date in the use of mathematical analysis and computer techniques in the study of epidemics of plant diseases; at the same time they seek to indicate the greatly enlarged possibilities, still in the early stage~ of investigation, of constructive work on this basis used in the field of epidemiology. A good beginning has been made in clarifying the very complex and sometimes confusing data by means of mathematical models and equations, and later by computer simulations. In this book practical procedures, such as experiments in coding techniques, reduction of data, computer programs, the particular scope of multiple regression analysis in the study of the progress of epidemics, disease increase and severity, disease cycles and crop losses, are variously discussed.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Dateigröße
ISBN-13
978-3-642-96220-2 (9783642962202)
DOI
10.1007/978-3-642-96220-2
Schweitzer Klassifikation
References.- I The Role and Scope of Mathematical Analysis and Modeling in Epidemiology..- 1. Introductory Remarks.- 2. Measurement in Epidemiology.- 3. Analysis of Population Parameters and Effects.- 4. Analysis of Changes in Populations.- 5. Prediction of Epidemic Events and Control Measures.- 6. Classification.- 7. Some Remarks on Stochastic Models in Epidemiology.- References.- II Automatic Data Processing in Analyses of Epidemics.- 1. Introduction.- 2. What Kind of Experiments in Quantitative Epidemiology ?.- 3. What Kind of Questionnaire for Field Experiments?.- 4. Automatic Data Acquisition Systems.- 5. What Kind of Data?.- 6. How to Reduce the Data?.- 7. Computer Programing and Availability of Software.- References.- III Multiple Regression Analysis in the Epidemiology of Plant Diseases.- 1. Introduction.- 2. The Nature of Multiple Regression Analysis in Epidemiology.- 3. The Execution of Multiple Regression Analysis.- 4. The Interpretation of Relationships Exposed by Multiple Regression Analysis.- 5. The Applications of Multiple Regression Analysis in Epidemiology.- 6. Conclusions: The Place of Multiple Regression in Current Approaches to Epidemic Analysis.- References.- IV Non-linear Disease Progress Curves.- 1. Introduction.- 2. Linear, Non-linear and Linearizable Models.- 3. The Derivation of Models from Differential Equations.- 4. Differential Equations and Ecology.- 5. Logistic Models of Epidemics.- 6. Application of the Logistic Model to Spore Count Data.- 7. Other Suggested Growth Models.- 8. Epidemic Models for Animal Populations.- 9. Computer Simulation Models.- 10. Pollen Count Data-an Alternative Model.- 11. Summary and Conclusions.- References.- V Simulation of Epidemics.- 1. Introduction.- 2. An Introductory Example.- 3. Experimenting to Build aSimulator.- 4. Some Simulators.- 5. Another Sort of Simulator.- 6. Difficulties Outstanding.- 7. Use of Simulators.- References.
