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Mathematical models can be very helpful to understand the transmission dynamics of infectious diseases. This book presents examples of epidemiological models and modeling tools that can assist policymakers to assess and evaluate disease control strategies. Contents: Development and Analysis of Models for Infectious Diseases; Application of Models to Real Disease Data; User-Friendly Modeling Tools for Public Health Policymakers. Readership: Researchers in mathematical biology, mathematical modeling, infectious diseases and complex systems.

Public health surveillance. --- Health risk assessment --- Communicable diseases --- Epidemiology --- Contagion and contagious diseases --- Contagious diseases --- Infectious diseases --- Microbial diseases in human beings --- Zymotic diseases --- Diseases --- Infection --- Epidemics --- Assessment, Health risk --- Health hazard appraisal --- Health hazard assessment --- Health risk appraisal --- HRA (Public health) --- Human risk assessment --- Medicine, Preventive --- Public health --- Risk assessment --- Environmental health --- Population surveillance (Public health) --- Surveillance, Public health --- Government policy. --- Mathematical models.

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The book is a comprehensive, self-contained introduction to the mathematical modeling and analysis of disease transmission models. It includes (i) an introduction to the main concepts of compartmental models including models with heterogeneous mixing of individuals and models for vector-transmitted diseases, (ii) a detailed analysis of models for important specific diseases, including tuberculosis, HIV/AIDS, influenza, Ebola virus disease, malaria, dengue fever and the Zika virus, (iii) an introduction to more advanced mathematical topics, including age structure, spatial structure, and mobility, and (iv) some challenges and opportunities for the future. There are exercises of varying degrees of difficulty, and projects leading to new research directions. For the benefit of public health professionals whose contact with mathematics may not be recent, there is an appendix covering the necessary mathematical background. There are indications which sections require a strong mathematical background so that the book can be useful for both mathematical modelers and public health professionals. .

Biomathematics. --- Probabilities. --- Mathematical models. --- Physiological, Cellular and Medical Topics. --- Probability Theory and Stochastic Processes. --- Mathematical Modeling and Industrial Mathematics. --- Models, Mathematical --- Simulation methods --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Biology --- Epidemiology