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Advances in Disease Epidemiology.

By: Contributor(s): Material type: TextTextPublisher: Hauppauge : Nova Science Publishers, Incorporated, 2009Copyright date: ©2009Edition: 1st edDescription: 1 online resource (309 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781617287664
Subject(s): Genre/Form: Additional physical formats: Print version:: Advances in Disease EpidemiologyDDC classification:
  • 614.4
LOC classification:
  • RA652.2.M3 -- A33 2009eb
Online resources:
Contents:
Intro -- ADVANCES IN DISEASEEPIDEMIOLOGY -- CONTENTS -- PREFACE -- AN AVIAN INFLUENZA MODEL AND ITS FITTO HUMAN AVIAN INFLUENZA CASES -- 1. The Ecology and Epidemiology of Avian Influenza -- 1.1. The Role ofWild Birds -- 1.2. The Role of Domestic Birds -- 1.3. Transmission to Humans and Control Measures -- 1.4. Epidemiological Models of Avian Influenza -- 1.5. Structure and Organization of This Article -- 2. The Model -- 2.1. Description -- 2.2. Summary of Simplifying Assumptions -- 2.3. Differential Equations -- 3. Basic Mathematical Properties of the Model -- 3.1. Persistence of LPAI and HPAI in the Full Model -- 3.2. Avian Influenza in the Domestic Bird-Human System -- 3.3. Invasion of HPAI. The Case m = 0 -- 4. Fitting Model to Data -- 4.1. General Method -- 4.2. Specific MATLAB Code -- 4.3. Results from the Fitting. Extending the Fit -- 5. Discussion -- Acknowledgments -- References -- GENDER DIFFERENCES IN HETEROSEXUALTRANSMISSION OF HIV IN URBAN AND RURALPOPULATIONS -- 1. Introduction -- 2. The Model -- 3. Analysis -- Approximation 3.1. -- Approximation 3.2. -- Approximation 3.3. -- 4. Numerical Simulations -- 4.1. The Choice of Parameter Values -- 4.2. Numerical Results -- 4.3. Long-Term Behaviour and a Second Steady State -- 5. Intervention Strategies -- 5.1. Modelling Intervention Strategies -- 5.2. Strategy Comparison -- 5.3. The Effect of Gender Differences -- 5.4. Redefining "Success" -- 6. Conclusion -- Appendix -- Acknowledgments -- References -- A PARTNERSHIP NETWORK SIMULATIONTHE SPREAD OF SEXUALLY TRANSMITTEDINFECTIONS IN RUSSIA -- 1. Introduction -- 1.1. HIV/AIDS -- 1.2. Gonorrhea -- 1.3. Previous STI Models -- 1.4. Ordinary Differential Equation Modeling -- 1.5. Pair Formation Models -- 1.6. Network Modeling -- 1. Core groups: -- 2. Loops: -- 3. Degree distribution: -- 1. Infection status: -- 2. Exclusively monogamous:.
3. Serial monogamists: -- 4. Risky behavior: -- 5. Basic reproductive number: -- 1.7. Other Considerations -- 1.8. Data Sources Used -- 1.9. Chapter Objectives and Outline -- 2. Model Description -- 2.1. Birth/Death Rates -- 2.2. Age Groups -- 2.3. Partnership Dynamics -- 2.3.1. Derivation of a Simple Model -- 2.4. Distribution of Number of Partners per Person in Survey -- 2.5. Calculating -- 2.6. Core Group -- 2.7. Simulating Matchmaker -- 2.8. Relationship Duration -- 2.9. Mean Number of Oartners -- 2.10. Condom Users -- 2.11. Epidemiological Parameters -- 2.12. Probability of HIV Transmission per Coital Act -- 2.13. Probability of Gonorrhea Transmission per Coital Act -- 2.14. Probability of Coital Act per Day -- 3. Results -- 3.1. HIV Prevalence in Population -- 3.2. Gonorrhea Prevalence -- 3.3. Interaction between Gonorrhea and HIV -- 3.4. Age Structure of Infected Population -- 3.5. Simulation Results for "experimental" Parameters -- 3.6. Influence of Percentage of Condom Users in Population -- 3.6.1. A Simple Model for Prevention Strategies -- 3.7. Influence of the Size of Core Group in Spread of HIV -- 4. Discussion -- 5. Conclusions -- References -- MALARIA CONTROL:THE ROLE OF LOCAL COMMUNITIES AS SEENTHROUGH A MATHEMATICAL MODELIN A CHANGING POPULATION - CAMEROON -- 1. Introduction -- 2. The Mathematical Model -- 2.1. The Differential Equations -- 3. Analysis -- 3.1. Non-dimensionalization -- 3.2. Parameter Space -- Proposition 1. -- 3.3. Boundedness and Positivity of Solutions -- Theorem 2. -- 3.4. Disease-Free Equilibrium (DFE) and the Basic Reproductive NumberR0 -- 3.4.1. Stability of the DFE -- Theorem 3. -- 3.5. Endemic Equilibrium -- 4. Simulation and Results -- 4.1. Quantification of the Impact Increasing the Recovery RateWill Haveon Malaria Dynamics.
4.2. Quantification of the Impact the Contact Rates have on Malaria Prevalenceand on Initial Disease Transmission -- 4.3. Sensitivity Analyses -- 4.3.1. Effects of the Recovery Rate and Contact Rates on R0 -- on the EquilibriumInfectious Host Proportion -- and on the Maximum Infectious Host Proportion -- Effects on R0 : -- Effects on the maximum infectious human population proportion: -- Effects on the equilibrium infectious human population: -- 4.3.2. Effects of Recruitment Rate on R0, on the Equilibrium Infectious Human Proportion,and on the Maximum Infectious Human Proportion -- 5. Conclusion -- Acknowledgement -- Appendix: Jacobian Matrix and the Characteristic Polynomial atthe Endemic Steady State -- References -- APPLICATION OF OPTIMAL CONTROLTO THE EPIDEMIOLOGYOF HIV-MALARIA CO-INFECTION -- 1. Introduction -- 2. Model Formulation -- 2.1. Analysis of the HIV-Malaria Model -- 2.1.1. Invariant Regions -- Lemma 1. -- 2.1.2. Analysis of the Sub-models -- HIV-only Model -- Stability of the Disease-Free Equilibrium (DFE) -- Lemma 2. -- Malaria-only Model -- Stability of the Disease-Free Equilibrium (DFE) -- Lemma 3. -- 2.2. Local Stability of the DFE of the HIV-Malaria Model -- Lemma 4. -- 3. Analysis of Optimal Control -- 3.1. Existence of Optimal Control -- Theorem 1. -- 3.2. Characterization of Optimal Controls -- Theorem 2. -- 4. Numerical Results -- Appendix -- References -- TWO STRAIN HIV/AIDS MODELAND THE EFFECTS OF SUPERINFECTION -- 1. Introduction -- 2. Two Strain HIV/AIDS Model without Superinfection -- Theorem 1. -- 2.1. Existence and Uniqueness of Solutions -- Theorem 2. -- 2.2. Disease-Free Equilibrium and Stability -- Lemma 2. -- 2.4. Global Stability of Disease-Free Equilibrium -- Theorem 3 -- Lemma 3. -- 2.5. Exclusive Endemic Equilibrium and Stability -- Lemma 4. -- Theorem 4. -- Theorem 5.
3. Two Strain HIV/AIDS Model with Superinfection -- Theorem 6. -- 3.1. Existence and Uniqueness of Solutions -- Theorem 7. -- 3.2. Reproduction Numbers and Equilibria -- Theorem 8. -- 3.3. Invasion Reproduction Numbers -- 4. Numerical Simulations -- 4.1. The Model without Superinfection -- 4.2. The Progression of the Infective Population with Time for Model (29) -- References -- MODELLING THE TRANSMISSION OFMULTIDRUG-RESISTANT AND EXTENSIVELYDRUG-RESISTANT TUBERCULOSIS -- 1. Introduction -- 2. Model Description -- 2.1. Basic Properties -- Lemma 1. -- Theorem 2.1. -- Theorem 2.2. -- Theorem 2.3. -- 2.2. Disease-Free Equilibrium and Stability Analysis -- Theorem 2.4. -- Lemma 2. -- Theorem 2.5. -- 2.3. Identification and Analysis of the Endemic Equilibria -- 2.3.1. Extensively Drug Resistant Equilibrium Only -- Lemma 3. -- Theorem 2.6. -- Computations of and b. -- Theorem 2.7. -- 2.3.2. Multidrug-Resistant TB Endemic Equilibrium Only -- 2.3.3. Drug Sensitive TB Endemic Equilibrium Only -- 2.3.4. Co-existence of the Drug Sensitive and Multidrug-Resistant TB EndemicEquilibrium Only -- 2.3.5. Co-existence of the Drug Sensitive and Extensively Drug-Resistant TB EndemicEquilibrium Only -- 2.3.6. Co-existence of the Extensively Drug-Resistant and Multidrug-Resistant TBEndemic Equilibrium Only -- 2.3.7. Coexistence of the Drug Sensitive, Multidrug Resistant and Extensively DrugResistant Strains Endemic Equilibrium -- 2.4. Analysis of the Reproduction Number -- Case 1: No intervention and case detection for all TB strains -- Case 2: Only latent and active forms of drug sensitive TB cases are detectedand treated -- Case 3: Only intervention for drug resistant cases (MDR and XDR) -- 3. Numerical Simulations -- 4. Summary and Concluding Remarks -- Acknowledgements -- References.
HIV/AIDS AND THE USE OF MATHEMATICALMODELS IN THE THEORETICAL ASSESSMENTOF INTERVENTION STRATEGIES: A REVIEW -- 1. Introduction -- 2. HIV/AIDS Interventions -- 3. Mathematical Modelling of Epidemics -- 4. Modelling HIV/AIDS and Interventions -- 5. Conclusion -- References -- A MODEL FOR THE SPREAD OF HIV/AIDS IN A TWOSEX POPULATION -- Abstract -- 1. Introduction -- 2. Mathematical Model -- 2.1. Male Susceptible Individuals, S1(t) -- 2.2. Male HIV Infected Individuals, I1(t) -- 2.3. Male Individuals with Clinical AIDS, A1(t) -- 2.4. Female Susceptible Individuals, S2(t) -- 2.5. Female HIV Infected Individuals, I2(t) -- 2.6. Female Individuals with Clinical AIDS, A2(t) -- 3. Stability Analysis -- 3.1. Equilibria of the Model -- 3.2. Local Stability of the Equilibria -- 3.3. Global Stability of the Endemic Equilibrium -- Lemma 1. -- Theorem 1. -- 4. Numerical Simulation and Discussion -- 5. Conclusion -- Appendix -- Proof of Theorem 1. -- References -- FITTING PROCEDURE FOR HOST-PARASITE SYSTEMS -- 1. Introduction -- 2. Host-Parasite Models Utilities -- 3. Structure of Host-Parasite Models -- 3.1. Host-macroparasite Model -- 4. Statistical Criteria for Parameter Estimation through DirectMinimization -- 5. Knowledge-Based Fitting Technique -- 6. Analysis of Residuals -- 7. Comparison of Fitting by Direct Minimization and KnowledgeBased Fitting -- 8. Summary -- 9. Conclusion -- 9.1. Recommendations Directed to the Fitting Mechanistic Models -- 9.2. Recommendations in Terms of Management and Making Policies -- Appendix -- References -- INDEX.
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Intro -- ADVANCES IN DISEASEEPIDEMIOLOGY -- CONTENTS -- PREFACE -- AN AVIAN INFLUENZA MODEL AND ITS FITTO HUMAN AVIAN INFLUENZA CASES -- 1. The Ecology and Epidemiology of Avian Influenza -- 1.1. The Role ofWild Birds -- 1.2. The Role of Domestic Birds -- 1.3. Transmission to Humans and Control Measures -- 1.4. Epidemiological Models of Avian Influenza -- 1.5. Structure and Organization of This Article -- 2. The Model -- 2.1. Description -- 2.2. Summary of Simplifying Assumptions -- 2.3. Differential Equations -- 3. Basic Mathematical Properties of the Model -- 3.1. Persistence of LPAI and HPAI in the Full Model -- 3.2. Avian Influenza in the Domestic Bird-Human System -- 3.3. Invasion of HPAI. The Case m = 0 -- 4. Fitting Model to Data -- 4.1. General Method -- 4.2. Specific MATLAB Code -- 4.3. Results from the Fitting. Extending the Fit -- 5. Discussion -- Acknowledgments -- References -- GENDER DIFFERENCES IN HETEROSEXUALTRANSMISSION OF HIV IN URBAN AND RURALPOPULATIONS -- 1. Introduction -- 2. The Model -- 3. Analysis -- Approximation 3.1. -- Approximation 3.2. -- Approximation 3.3. -- 4. Numerical Simulations -- 4.1. The Choice of Parameter Values -- 4.2. Numerical Results -- 4.3. Long-Term Behaviour and a Second Steady State -- 5. Intervention Strategies -- 5.1. Modelling Intervention Strategies -- 5.2. Strategy Comparison -- 5.3. The Effect of Gender Differences -- 5.4. Redefining "Success" -- 6. Conclusion -- Appendix -- Acknowledgments -- References -- A PARTNERSHIP NETWORK SIMULATIONTHE SPREAD OF SEXUALLY TRANSMITTEDINFECTIONS IN RUSSIA -- 1. Introduction -- 1.1. HIV/AIDS -- 1.2. Gonorrhea -- 1.3. Previous STI Models -- 1.4. Ordinary Differential Equation Modeling -- 1.5. Pair Formation Models -- 1.6. Network Modeling -- 1. Core groups: -- 2. Loops: -- 3. Degree distribution: -- 1. Infection status: -- 2. Exclusively monogamous:.

3. Serial monogamists: -- 4. Risky behavior: -- 5. Basic reproductive number: -- 1.7. Other Considerations -- 1.8. Data Sources Used -- 1.9. Chapter Objectives and Outline -- 2. Model Description -- 2.1. Birth/Death Rates -- 2.2. Age Groups -- 2.3. Partnership Dynamics -- 2.3.1. Derivation of a Simple Model -- 2.4. Distribution of Number of Partners per Person in Survey -- 2.5. Calculating -- 2.6. Core Group -- 2.7. Simulating Matchmaker -- 2.8. Relationship Duration -- 2.9. Mean Number of Oartners -- 2.10. Condom Users -- 2.11. Epidemiological Parameters -- 2.12. Probability of HIV Transmission per Coital Act -- 2.13. Probability of Gonorrhea Transmission per Coital Act -- 2.14. Probability of Coital Act per Day -- 3. Results -- 3.1. HIV Prevalence in Population -- 3.2. Gonorrhea Prevalence -- 3.3. Interaction between Gonorrhea and HIV -- 3.4. Age Structure of Infected Population -- 3.5. Simulation Results for "experimental" Parameters -- 3.6. Influence of Percentage of Condom Users in Population -- 3.6.1. A Simple Model for Prevention Strategies -- 3.7. Influence of the Size of Core Group in Spread of HIV -- 4. Discussion -- 5. Conclusions -- References -- MALARIA CONTROL:THE ROLE OF LOCAL COMMUNITIES AS SEENTHROUGH A MATHEMATICAL MODELIN A CHANGING POPULATION - CAMEROON -- 1. Introduction -- 2. The Mathematical Model -- 2.1. The Differential Equations -- 3. Analysis -- 3.1. Non-dimensionalization -- 3.2. Parameter Space -- Proposition 1. -- 3.3. Boundedness and Positivity of Solutions -- Theorem 2. -- 3.4. Disease-Free Equilibrium (DFE) and the Basic Reproductive NumberR0 -- 3.4.1. Stability of the DFE -- Theorem 3. -- 3.5. Endemic Equilibrium -- 4. Simulation and Results -- 4.1. Quantification of the Impact Increasing the Recovery RateWill Haveon Malaria Dynamics.

4.2. Quantification of the Impact the Contact Rates have on Malaria Prevalenceand on Initial Disease Transmission -- 4.3. Sensitivity Analyses -- 4.3.1. Effects of the Recovery Rate and Contact Rates on R0 -- on the EquilibriumInfectious Host Proportion -- and on the Maximum Infectious Host Proportion -- Effects on R0 : -- Effects on the maximum infectious human population proportion: -- Effects on the equilibrium infectious human population: -- 4.3.2. Effects of Recruitment Rate on R0, on the Equilibrium Infectious Human Proportion,and on the Maximum Infectious Human Proportion -- 5. Conclusion -- Acknowledgement -- Appendix: Jacobian Matrix and the Characteristic Polynomial atthe Endemic Steady State -- References -- APPLICATION OF OPTIMAL CONTROLTO THE EPIDEMIOLOGYOF HIV-MALARIA CO-INFECTION -- 1. Introduction -- 2. Model Formulation -- 2.1. Analysis of the HIV-Malaria Model -- 2.1.1. Invariant Regions -- Lemma 1. -- 2.1.2. Analysis of the Sub-models -- HIV-only Model -- Stability of the Disease-Free Equilibrium (DFE) -- Lemma 2. -- Malaria-only Model -- Stability of the Disease-Free Equilibrium (DFE) -- Lemma 3. -- 2.2. Local Stability of the DFE of the HIV-Malaria Model -- Lemma 4. -- 3. Analysis of Optimal Control -- 3.1. Existence of Optimal Control -- Theorem 1. -- 3.2. Characterization of Optimal Controls -- Theorem 2. -- 4. Numerical Results -- Appendix -- References -- TWO STRAIN HIV/AIDS MODELAND THE EFFECTS OF SUPERINFECTION -- 1. Introduction -- 2. Two Strain HIV/AIDS Model without Superinfection -- Theorem 1. -- 2.1. Existence and Uniqueness of Solutions -- Theorem 2. -- 2.2. Disease-Free Equilibrium and Stability -- Lemma 2. -- 2.4. Global Stability of Disease-Free Equilibrium -- Theorem 3 -- Lemma 3. -- 2.5. Exclusive Endemic Equilibrium and Stability -- Lemma 4. -- Theorem 4. -- Theorem 5.

3. Two Strain HIV/AIDS Model with Superinfection -- Theorem 6. -- 3.1. Existence and Uniqueness of Solutions -- Theorem 7. -- 3.2. Reproduction Numbers and Equilibria -- Theorem 8. -- 3.3. Invasion Reproduction Numbers -- 4. Numerical Simulations -- 4.1. The Model without Superinfection -- 4.2. The Progression of the Infective Population with Time for Model (29) -- References -- MODELLING THE TRANSMISSION OFMULTIDRUG-RESISTANT AND EXTENSIVELYDRUG-RESISTANT TUBERCULOSIS -- 1. Introduction -- 2. Model Description -- 2.1. Basic Properties -- Lemma 1. -- Theorem 2.1. -- Theorem 2.2. -- Theorem 2.3. -- 2.2. Disease-Free Equilibrium and Stability Analysis -- Theorem 2.4. -- Lemma 2. -- Theorem 2.5. -- 2.3. Identification and Analysis of the Endemic Equilibria -- 2.3.1. Extensively Drug Resistant Equilibrium Only -- Lemma 3. -- Theorem 2.6. -- Computations of and b. -- Theorem 2.7. -- 2.3.2. Multidrug-Resistant TB Endemic Equilibrium Only -- 2.3.3. Drug Sensitive TB Endemic Equilibrium Only -- 2.3.4. Co-existence of the Drug Sensitive and Multidrug-Resistant TB EndemicEquilibrium Only -- 2.3.5. Co-existence of the Drug Sensitive and Extensively Drug-Resistant TB EndemicEquilibrium Only -- 2.3.6. Co-existence of the Extensively Drug-Resistant and Multidrug-Resistant TBEndemic Equilibrium Only -- 2.3.7. Coexistence of the Drug Sensitive, Multidrug Resistant and Extensively DrugResistant Strains Endemic Equilibrium -- 2.4. Analysis of the Reproduction Number -- Case 1: No intervention and case detection for all TB strains -- Case 2: Only latent and active forms of drug sensitive TB cases are detectedand treated -- Case 3: Only intervention for drug resistant cases (MDR and XDR) -- 3. Numerical Simulations -- 4. Summary and Concluding Remarks -- Acknowledgements -- References.

HIV/AIDS AND THE USE OF MATHEMATICALMODELS IN THE THEORETICAL ASSESSMENTOF INTERVENTION STRATEGIES: A REVIEW -- 1. Introduction -- 2. HIV/AIDS Interventions -- 3. Mathematical Modelling of Epidemics -- 4. Modelling HIV/AIDS and Interventions -- 5. Conclusion -- References -- A MODEL FOR THE SPREAD OF HIV/AIDS IN A TWOSEX POPULATION -- Abstract -- 1. Introduction -- 2. Mathematical Model -- 2.1. Male Susceptible Individuals, S1(t) -- 2.2. Male HIV Infected Individuals, I1(t) -- 2.3. Male Individuals with Clinical AIDS, A1(t) -- 2.4. Female Susceptible Individuals, S2(t) -- 2.5. Female HIV Infected Individuals, I2(t) -- 2.6. Female Individuals with Clinical AIDS, A2(t) -- 3. Stability Analysis -- 3.1. Equilibria of the Model -- 3.2. Local Stability of the Equilibria -- 3.3. Global Stability of the Endemic Equilibrium -- Lemma 1. -- Theorem 1. -- 4. Numerical Simulation and Discussion -- 5. Conclusion -- Appendix -- Proof of Theorem 1. -- References -- FITTING PROCEDURE FOR HOST-PARASITE SYSTEMS -- 1. Introduction -- 2. Host-Parasite Models Utilities -- 3. Structure of Host-Parasite Models -- 3.1. Host-macroparasite Model -- 4. Statistical Criteria for Parameter Estimation through DirectMinimization -- 5. Knowledge-Based Fitting Technique -- 6. Analysis of Residuals -- 7. Comparison of Fitting by Direct Minimization and KnowledgeBased Fitting -- 8. Summary -- 9. Conclusion -- 9.1. Recommendations Directed to the Fitting Mechanistic Models -- 9.2. Recommendations in Terms of Management and Making Policies -- Appendix -- References -- INDEX.

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