Epidemic Models: Their Structure and Relation to DataDenis Mollison Cambridge University Press, 13.07.1995 - 424 Seiten The problems of understanding and controlling disease present a range of mathematical challenges, from broad theoretical issues to specific practical ones, making epidemiology one of the most vibrant branches of applied biology. Progress in this field requires collaboration among leading researchers with a wide range of mathematical expertise and close involvement in applied fields across the social, medical and biological sciences. This volume surveys the current state of epidemic modeling in relation to basic aims such as understanding, prediction, and evaluation and implementation of control strategies. The book is divided into five parts, covering the conceptual framework, three major problem areas (space, nonlinearity, heterogeneity), and the direct relation of models to data. The contributors discuss a wide range of methodological issues, e.g. comparing different approaches to the modeling of heterogeneity and relations among different types of model; and different data analytic approaches, together with the availability and quality of the data they require. |
Inhalt
Preface | 5 |
Contributors | xv |
Klaus Dietz Some problems in the theory of infectious disease | xviii |
Denis Mollison The structure of epidemic models | 17 |
Frank Ball Coupling methods in epidemic theory | 34 |
Ingemar Nåsell The threshold concept in deterministic | 71 |
Mart de Jong Odo Diekmann and Hans Heesterbeek How does | 84 |
Odo Diekmann Hans Metz and Hans Heesterbeek The legacy | 95 |
Henry Daniels A perturbation approach to nonlinear | 202 |
Lynne Billard P W A Dayananda and Zhen Zhao Epidemic plant | 215 |
NONLINEAR TIME AND SPACETIME DYNAMICS | 229 |
Bryan Grenfell Ben Bolker and Adam Kleczkowski Seasonality | 248 |
Niels Becker Statistical challenges of epidemic data | 339 |
Andrew Cairns Primary components of epidemic models | 350 |
Hans Remme Soumbey Alley and Anton Plaisier Estimation | 372 |
Ira Longini Elizabeth Halloran and Michael Haber | 394 |
Andrew Cliff Incorporating spatial components into models | 119 |
Hans Metz and Frank van den Bosch Velocities of epidemic spread | 150 |
Richard Durrett Spatial epidemic models | 187 |
Norman Bailey Operational modelling of HIVAIDS | 404 |
Problem areas | 417 |
Andere Ausgaben - Alle anzeigen
Epidemic Models: Their Structure and Relation to Data Denis Mollison,Mollison Denis Keine Leseprobe verfügbar - 1995 |
Häufige Begriffe und Wortgruppen
AIDS analysis Anderson Appl approach approximation assortative mixing assumption asymptotic average b₁ Bailey basic reproductive rate behaviour Biol Biosci Bosch branching process chaos contact rate den Bosch density depend deterministic deterministic models Diekmann Dietz distribution Durrett effects endemic epidemic models epidemiological equation equilibrium estimate example exponential Figure function graph Grenfell Heesterbeek heterogeneity Hethcote immunity incidence infected individuals infectious diseases infectious period initial ivermectin Jacquez Lefèvre linear log-linear model Lyapunov exponents malaria Math mathematical matrix measles methods Metz Mollison nonlinear number of infectives onchocerciasis parameters parasite Picard population predictions prevalence Primary Components Prob probability problem proportional pseudo mass-action random variables reproduction number reproduction ratio Reykjavík Section seroprevalence sexual simple simulation SIS model spatial spread stochastic epidemic stochastic models Stochastic Processes structure subgroups theorem theory threshold tion transmission true mass-action vaccination values vector control wave