Models for Infectious Human Diseases
Their Structure and Relation to Data
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Models for Infectious Human Diseases by Valerie Isham
Book DescriptionInfectious disease accounts for more death and disability globally than either non-infectious disease or injury. This book contains a breadth of different quantitative approaches to understanding the patterns of infectious diseases in populations, and the design of control strategies to lessen their effect. The contributors bring a great variety of mathematical expertise (including deterministic and stochastic modelling and statistical data analysis) and involvement in a wide range of applied fields across the spectrum of biological, medical and social sciences. The aim is to increase interaction between specialities by describing research on many of the infectious diseases that affect humans, including both viral diseases like measles and AIDS and tropical parasitic infections. The papers are divided into groups dealing with problems relating to transmissible diseases, vaccination strategies, the consequences of treatment interventions, the dynamics of immunity, heterogeneity of populations, and prediction.
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Book DetailsISBN: 9780521453394
(228mm x 152mm x 33mm)
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 29-Mar-1996
Country of Publication: United Kingdom
Books By Author Valerie Isham
Mixed Effects Models for Complex Data, Hardback (November 2009)
Reviews incomplete data problems in mixed-effects models for longitudinal studies and discusses various approaches, including some commonly used simple methods, EM algorithms, and multiple imputation methods. This work also covers other models for longitudinal data, such as marginal models with missing values.
Models for Infectious Human Diseases, Paperback (February 2008)
Vital resource in infectious diseases, will especially appeal to workers in epidemiology, public health and biology.
Statistical Methods for Spatio-Temporal Systems, Hardback (October 2006)View all books by Valerie Isham
Presents statistical research issues on spatio-temporal data modeling that promotes advances in research and an understanding between the mechanistic and the statistical modeling communities. This book offers a variety of statistical methods, including likelihood-based, nonparametric smoothing, Fourier, wavelet, and Markov chain Monte Carlo.
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