Predicting and Controlling Disease

Marcus Hutber
Petcare Limited Director, Winchester, Hampshire, England

Series: Public Health in the 21st Century
BISAC: MED078000



Volume 10

Issue 1

Volume 2

Volume 3

Special issue: Resilience in breaking the cycle of children’s environmental health disparities
Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick


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This book has primarily been aimed at epidemiologists working with empirical data for both human and veterinary diseases. The final paragraph of this preface is probably the most important paragraph of the book, and if epidemiologists or healthcare or veterinary administrators are converted to the concept outlined in the last paragraph, then the book will have served a useful purpose: twenty-five years of epidemiological research culminated in the concept described in this paragraph.

This book introduces second generation epidemiological modelling. Second generation modelling uses directly measurable biomodels that do not require estimates for their quantitative values. Biomodels encompass multiple model factors that would otherwise have to be estimated, and as such biomodels are directly correlated with disease prevalence and epidemic duration. This correlation enables biomodels to accurately predict the future course of an epidemic before it unfolds, whilst concurrently directing healthcare administrators where to target manpower and financial resources for optimal disease control.

Whereas first generation modelling remains a useful tool for pedagogical or teaching purposes, second generation modelling [in the form of biomodels] allows healthcare administrators to cope with the demands of immediate and rapid disease control during periods of disease epidemics. Biomodels should be developed for important infectious diseases during periods of epidemiological ‘peacetime’, when manpower and resources are not held at a premium.

Few non-fictional books are read cover-to-cover. To accommodate the selective reader, some of the most important concepts in this volume [such as biofactors, biomodels, subclinical disease and predictive accuracy] are repeated within relevant chapters.

National and regional disease contingency planning should incorporate biomodels as useful tools when planning future disease control measures. (Imprint: Nova Biomedical)



Section A - Predicting Disease Spread

Chapter 1 - Predicting the Future with Epidemiological Models (pp. 5-50)

Chapter 2 - Second Generation Modelling (pp. 51-104)

Section B - Biofactors and Biomodels

Chapter 3 - Directly Measurable Factors - Subclinical Disease (pp. 107-116)

Chapter 4 - A Disease Template (pp. 117-142)

Section C - Disease Control

Chapter 5 - Future Models (pp. 145-166)


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