Applications of Epidemiological Models to Public Health Policymaking
The Role of Heterogeneity in Model Predictions
Nonfiction, Science & Nature, Mathematics, Applied, Health & Well Being, Health, Health Care Issues
| Author: | Zhilan Feng | ISBN: | 9789814522366 |
| Publisher: | World Scientific Publishing Company | Publication: | April 8, 2014 |
| Imprint: | WSPC | Language: | English |
| Author: | Zhilan Feng |
| ISBN: | 9789814522366 |
| Publisher: | World Scientific Publishing Company |
| Publication: | April 8, 2014 |
| Imprint: | WSPC |
| Language: | English |
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:
-
Mathematical Modeling in Epidemiology:
- Epidemic Models
- Endemic Models
-
Applications to Public Health Policymaking:
- Applications of Models to Evaluations of Disease Control Strategies
- Development of Interactive Tools to Assist Public Health Policymaking
Readership: Researchers in mathematical biology, mathematical modeling, infectious diseases and complex systems.
Key Features:
- Development of modeling tools that are user-friendly to policymakers
- Consideration of heterogeneities that are not analyzed in detail previously
- Connection of model analyses to real disease data to improve understanding
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:
-
Mathematical Modeling in Epidemiology:
- Epidemic Models
- Endemic Models
-
Applications to Public Health Policymaking:
- Applications of Models to Evaluations of Disease Control Strategies
- Development of Interactive Tools to Assist Public Health Policymaking
Readership: Researchers in mathematical biology, mathematical modeling, infectious diseases and complex systems.
Key Features:
- Development of modeling tools that are user-friendly to policymakers
- Consideration of heterogeneities that are not analyzed in detail previously
- Connection of model analyses to real disease data to improve understanding
