Dynamic Models of Infectious Diseases

1. Front Matter

   Pages i-xii

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2. Control of Infectious Diseases: Dynamics and Informatics

   • V. Sree Hari Rao, M. Naresh Kumar

   Pages 1-30

3. Percolation Methods for SEIR Epidemics on Graphs

   • Alberto Gandolfi

   Pages 31-58

4. Dynamics of Tuberculosis in a Developing Country: Nigeria as a Case Study

   • Daniel Okuonghae, Andrei Korobeinikov

   Pages 59-78

5. Two-Component Signalling Systems of M. tuberculosis: Regulators of Pathogenicity and More

   • Ruchi Agrawal, Vignesh H. Narayan, Deepak Kumar Saini

   Pages 79-109

6. Mycobacterium tuberculosis: Evolution, Host–Pathogen Interactions, and Implications for Tuberculosis Control

   • Marcos Burgos

   Pages 111-146

7. Trends in HIV Transmission According to Differences in Numbers of Sexual Partnerships Among Men Who Have Sex with Men in China

   • Lei Zhang, Eric P. F. Chow, David P. Wilson

   Pages 147-176

8. The Impact of Cryptococcus gattii with a Focus on the Outbreak in North America

   • Carla J. Walraven, Maximillian Jahng, Gregory C. Davenport, Hallie Rane, Samuel A. Lee

   Pages 177-203

9. Evaluating the Evolutionary Dynamics of Viral Populations

   • Lars Steinbrück, Alice Carolyn McHardy

   Pages 205-225

10. Modeling the Spread and Outbreak Dynamics of Avian Influenza (H5N1) Virus and Its Possible Control

    • V. Sree Hari Rao, Ranjit Kumar Upadhyay

    Pages 227-250

11. Back Matter

    Pages 251-259

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Though great advances in public health are witnessed world over in recent years, infectious diseases, besides insect vector-borne infectious diseases remain a leading cause of morbidity and mortality. Control of the epidemics caused by the non-vector borne diseases such as tuberculosis, avian influenza (H5N1) and cryptococcus gattii, have left a very little hope in the past. The advancement of research in science and technology has paved way for the development of new tools and methodologies to fight against these diseases. In particular, intelligent technology and machine-learning based methodologies have rendered useful in developing more accurate predictive tools for the early diagnosis of these diseases. In all these endeavors the main focus is the understanding that the process of transmission of an infectious disease is nonlinear (not necessarily linear) and dynamical in character. This concept compels the appropriate quantification of the vital parameters that govern these dynamics. This book is ideal for a general science and engineering audience requiring an in-depth exposure to current issues, ideas, methods, and models. The topics discussed serve as a useful reference to clinical experts, health scientists, public health administrators, medical practioners, and senior undergraduate and graduate students in applied mathematics, biology, bioinformatics, and epidemiology, medicine and health sciences.

• infectious diseases
• Systems Biology

• Foundation for Scientific Research and Technological Innovation, Hyderabad, India

  V. Sree Hari Rao

• University of New Mexico School of Medicine, Albuquerque, USA

  Ravi Durvasula

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