| Description |
1 online resource |
| Contents |
Front Cover; A Historical Introduction to Mathematical Modeling of Infectious Diseases; Copyright; Dedication; Contents; Introduction; Motivation and short history (of this book); Structure and suggested use of the book; Target audience; Mathematical background; Miscellaneous remarks; References; Acknowledgments; 1 D. Bernoulli: A pioneer of epidemiologic modeling (1760); 1.1 Bernoulli and the speckled monster -- 1.1.1 1 through 4: Preamble; 1.1.2 5 through 6: Mathematical foundation; 1.1.3 7 through 9: Table 1; 1.1.4 11 & 12: Table 2 |
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1.1.5 13: Closed form solution for the counterfactual survivorsAppendix 1.A Answers; Appendix 1.B Supplementary material; References; 2 P.D. En'ko: An early transmission model (1889); 2.1 Introduction; 2.2 Assumptions; 2.3 The model; 2.4 Simulation model; 2.4.1 Start of the simulation; 2.4.2 Discussion of Table 1 and Figures; 2.4.3 An important detail: The period; Appendix 2.A Answers; Appendix 2.B Supplementary material; References; 3 W.H. Hamer (1906) and H. Soper (1929): Why diseases come and go; 3.1 Introduction; 3.2 Hamer: Variability and persistence; 3.2.1 A tortuous introduction |
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3.2.2 Characteristic of periodic measles epidemics3.2.3 The case of influenza; 3.3 Soper: Periodicity in disease prevalence; Regeneration of the population; Law of infection -- Mass action; 3.3.1 Infection dynamics; 3.3.2 The simulated epidemic; 3.3.3 Periods; 3.3.4 Considerations of seasonal factors and model fit to Glasgow data; Appendix 3.A ; The discussion; Appendix 3.B Answers; Appendix 3.C Supplementary material; References; 4 W.O. Kermack and A.G. McKendrick: A seminal contribution to the mathematical theory of epidemics (1927); 4.1 Introduction |
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4.2 General theory: (2) through (7)4.2.1 (2): The infection process in discrete time; 4.2.2 (3): The infection process in continuous time; 4.2.3 (6): The proportion infected ; 4.3 Special cases: (8) through (13); 4.3.1 (10): The Kermack & McKendrick model -- 4.3.2 (12): Extension to vector-borne diseases; Appendix 4.A ; Appendix 4.B Answers; Appendix 4.C Supplementary material; References; 5 R. Ross (1910, 1911) and G. Macdonald (1952) on the persistence of malaria; 5.1 Introduction; 5.2 Ross: What keeps malaria going?; 5.2.1 Laws which Regulate the Amount of Malaria in a Locality |
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5.2.2 Final remarks on Ross's modeling contributions5.3 George Macdonald: Malaria equilibrium beyond Ross; 5.3.1 A linear model; 5.3.2 The basic reproduction rate of malaria -- 5.3.3 Comparing Ross's-implicit-and Macdonald's R0 for malaria; Appendix 5.A Answers; References; 6 M. Bartlett (1949), N.T. Bailey (1950, 1953) and P. Whittle (1955): Pioneers of stochastic transmission models; 6.1 Introduction: Stochastic transmission models; 6.2 Bailey: A simple stochastic transmission model; 6.2.1 Deterministic approach; 6.2.2 Stochastic approach |
| Notes |
Includes index |
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Print version record |
| Subject |
Communicable diseases -- Transmission -- Mathematical models
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HEALTH & FITNESS -- Diseases -- General.
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MEDICAL -- Clinical Medicine.
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MEDICAL -- Diseases.
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MEDICAL -- Evidence-Based Medicine.
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MEDICAL -- Internal Medicine.
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Communicable diseases -- Transmission -- Mathematical models
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| Form |
Electronic book
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| ISBN |
0128024992 |
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9780128024997 |
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