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Disease modelling and public health. Part A /
Disease Modelling and Public Health, Part A, Volume 36 addresses new challenges in existing and emerging diseases with a variety of comprehensive chapters that cover Infectious Disease Modeling, Bayesian Disease Mapping for Public Health, Real time estimation of the case fatality ratio and risk fact...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam, Netherlands :
North Holland is an imprint of Elsevier,
2017.
|
| Colección: | Handbook of statistics (Amsterdam, Netherlands) ;
v. 36. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Disease modelling and public health. |n Part A / |c edited by Arni S.R. Srinivasa Rao, Saumyadipta Pye, and C.R. Rao. |
| 264 | 1 | |a Amsterdam, Netherlands : |b North Holland is an imprint of Elsevier, |c 2017. | |
| 264 | 4 | |c �2017 | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Handbook of statistics ; |v volume 36 | |
| 500 | |a Includes index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (ScienceDirect, viewed October 20, 2017). | |
| 505 | 0 | |a Front Cover -- Disease Modelling and Public Health -- Copyright -- Contents -- Contributors -- Preface -- Section I: Introduction and Disease Modeling -- Chapter 1: Fundamentals of Mathematical Models of Infectious Diseases and Their Application to Data Analyses -- 1. Introduction: Fundamentals of Infectious Disease Dynamical Models -- 1.1. Population Dynamics of Biological Populations -- 1.2. Infectious Disease Spread Models, or Theoretical Epidemiology -- 1.3. Important Concepts in Infectious Disease Epidemiology | |
| 505 | 8 | |a 1.4. Important Concepts From Dynamical Models of Infectious Diseases2. Analyses of Whole Population: Macroscopic Analyses -- 2.1. Data Description -- 2.2. Simple Regression Analysis -- 2.3. The Effect of School Closure -- 2.4. Incorporating Exposed Phase: SEIR Model -- 2.5. Distributions of Latent and Infectious Periods -- 2.6. Multiple Subgroups and Generation Matrix -- 3. Stochastic Model of Infectious Disease Spread: Microscopic Model Considering Each Class -- 3.1. Analyses for Counted Data -- 3.2. Modeling the Reporting Delay | |
| 505 | 8 | |a 3.3. Modeling the Transition of Infectious Diseases3.4. Reconstruction of the Values of State Variables of the System -- 3.5. Analysis and Simulation, and the Validity of the Model -- 4. An Analysis of Spatial Distribution -- 4.1. Location of Schools -- 4.2. Estimating Transition Kernel -- 4.3. Influence of the Network of Transmission -- 5. Conclusion -- References -- Further Reading -- Chapter 2: Dynamic Risk Prediction for Cardiovascular Disease: An Illustration Using the ARIC Study -- 1. Introduction -- 2. Landmarking -- 2.1. The Landmarking Method | |
| 505 | 8 | |a 2.2. Dynamic Prediction3. Joint Models -- 3.1. Model Specification -- 3.2. Estimation -- 3.3. Dynamic Prediction -- 4. Assessing Predictive Performance -- 4.1. Area Under the Receiver Operating Characteristic Curve -- 4.2. Brier Score -- 5. Example: The ARIC Study -- 6. Discussion -- Acknowledgments -- References -- Chapter 3: Statistical Models for Selected Infectious Diseases -- 1. Common Cold and Asthma Exacerbation -- 2. Influenza -- 2.1. Surveillance and Estimates of the Center for Disease Control and Prevention | |
| 505 | 8 | |a 2.2. Influenza and Respiratory Syncytial Virus in the United States2.3. Measles and Influenza Outbreaks -- 2.4. SIRS and Hierarchical Bayesian Models -- 2.5. Autoregressive and Bayesian Models for the Spread of Influenza -- 2.6. Correlation of Surveillance Systems and Information Environment -- 2.7. The Delphi System -- 3. Tuberculosis -- 3.1. Statistical Models for TB Incidence, Prevalence, and Mortality Estimates -- 3.2. Mathematical Models -- 3.3. Regression and Bayesian Models -- 3.4. Statistical Relational Models for Structured Epidemiological Characteristics | |
| 520 | |a Disease Modelling and Public Health, Part A, Volume 36 addresses new challenges in existing and emerging diseases with a variety of comprehensive chapters that cover Infectious Disease Modeling, Bayesian Disease Mapping for Public Health, Real time estimation of the case fatality ratio and risk factor of death, Alternative Sampling Designs for Time-To-Event Data with Applications to Biomarker Discovery in Alzheimer's Disease, Dynamic risk prediction for cardiovascular disease: An illustration using the ARIC Study, Theoretical advances in type 2 diabetes, Finite Mixture Models in Biostatistics, and Models of Individual and Collective Behavior for Public Health Epidemiology. | ||
| 650 | 0 | |a Epidemiology |x Statistical methods. | |
| 650 | 0 | |a Diseases |x Statistical methods. | |
| 650 | 2 | |a Epidemiology |x statistics & numerical data |0 (DNLM)D004813Q000706 | |
| 650 | 6 | |a �Epid�emiologie |x M�ethodes statistiques. |0 (CaQQLa)000268239 | |
| 650 | 6 | |a Maladies |0 (CaQQLa)201-0078919 |x M�ethodes statistiques. |0 (CaQQLa)201-0373903 | |
| 650 | 7 | |a MEDICAL |x Forensic Medicine. |2 bisacsh | |
| 650 | 7 | |a MEDICAL |x Preventive Medicine. |2 bisacsh | |
| 650 | 7 | |a MEDICAL |x Public Health. |2 bisacsh | |
| 650 | 7 | |a Diseases |x Statistical methods |2 fast |0 (OCoLC)fst00895199 | |
| 650 | 7 | |a Epidemiology |x Statistical methods |2 fast |0 (OCoLC)fst00914109 | |
| 700 | 1 | |a Srinivasa Rao, Arni S. R., |e editor. | |
| 700 | 1 | |a Pyne, Saumyadipta, |e editor. | |
| 700 | 1 | |a Rao, C. Radhakrishna |q (Calyampudi Radhakrishna), |d 1920-2023, |e editor. | |
| 776 | 0 | 8 | |i Print version: |t Disease modelling and public health. Part A. |d Amsterdam, Netherlands : North Holland is an imprint of Elsevier, 2017 |z 0444639683 |z 9780444639684 |w (OCoLC)978590133 |
| 830 | 0 | |a Handbook of statistics (Amsterdam, Netherlands) ; |v v. 36. | |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/handbooks/01697161/36 |z Texto completo |