A spatial agent-based simulation model for malaria epidemiology : design, implementation, and applications for malaria epidemiology /: design, implementation, and applications for malaria epidemiology. (2015)

• Record Type: Book
• Further Information: Note: S.M. Niaz Arifin, Gregory R. Madey, Frank H. Collins.
• Authors: Arifin, S.M. Niaz; Madey, Gregory R; Collins, Frank H
• Contents: Preface Acknowledgements Abbreviations 1: Introduction 1.1 Overview 1.2 Malaria 1.3 Agent-Based Modeling of Malaria 1.4 Contributions 1.5 Organization 2: Malaria: A Brief History 2.1 Overview 2.2 Malaria in Human History 2.2.1 The Malarial Path: Ancient Origins 2.2.2 Naming and Key Discoveries 2.2.3 Antimalarial Drugs 2.2.4 Prevention Measures 2.3 Malaria Epidemiology: A Global View 2.3.1 The Malaria Parasite 2.3.2 Geographic Distribution 2.3.3 Types of Transmission 2.3.4 Risk Mapping and Forecasting 2.4 Malaria Control 3. Agent-Based Modeling and Malaria 3.1 Overview 3.2 Agent-Based Models (ABMs) 3.2.1 Agents 3.2.2 Environment 3.2.3 Rules 3.2.4 Software for ABMs 3.3 History and Applications 3.3.1 M&S Organizations 3.4 Advantages of ABMs 3.4.1 Emergence, Aggregation, and Complexity 3.4.2 Heterogeneity 3.4.3 Learning and Adaptation 3.4.4 Flexibility in System Description 3.4.5 Inclusion of Multiple Spaces 3.4.6 Limitations of ABMs 3.4.7 ABMs vs. Mathematical Models 3.4.8 Applicability of ABMs for Malaria Modeling 3.5 Malaria Models: A Review 3.5.1 Mathematical Models of Malaria 3.5.2 Agent-Based Models (ABMs) of Malaria 3.5.3 The Spatial Dimension of Malaria Models 3.6 Summary 4. The Biological Core Model 4.1 Overview 4.1.1 Relevant Terms of Interest 4.2 The Aquatic Phase 4.2.1 Egg (E) 4.2.2 Larva (L) 4.2.3 Pupa (P) 4.3 The Adult Phase 4.3.1 Immature Adult (IA) 4.3.2 Mate Seeking (MS) 4.3.3 Blood Meal Seeking (BMS) 4.3.4 Blood Meal Digesting (BMD) 4.3.5 Gravid (G) 4.4 Aquatic Habitats and Oviposition 4.4.1 Aquatic Habitats 4.4.2 Oviposition 4.5 Senescence and Mortality Rates 4.5.1 Senescence 4.5.2 Mortality Models: Basic Mathematical Formulation 4.6 Mortality in the Core Model 4.6.1 Aquatic (Immature) Mortality Rates 4.6.2 Adult Mortality Rates 4.7 Discussion 4.7.1 An Extendible Framework for Other Anopheline Species 4.7.2 Weather, Seasonality, and Other Factors 4.7.3 Mortality Rates 4.8 Summary 5. The Agent-Based Model (ABM) 5.1 Overview 5.2 Model Architecture 5.2.1 Object-Oriented Programming (OOP) Terminology 5.2.2 Agents 5.2.3 Environments 5.2.4 Event-Action-List Diagram 5.3 Mosquito Population Dynamics 5.4 Model Features 5.4.1 Processing Steps Ordering 5.4.2 Model Assumptions 5.4.3 Simulations 5.5 Summary 6. The Spatial ABM 6.1 Overview 6.2 The Spatial ABM 6.2.1 De_nition of Terms 6.2.2 Landscapes 6.2.3 Landscape Generator Tools 6.3 Resource Clustering 6.4 Flight Heuristics for Mosquito Agents 6.5 Simulation Results 6.5.1 Model Veri_cation 6.5.2 Landscape Patterns 6.5.3 Relative Sizes of Resources 6.5.4 Resource Density 6.5.5 Combined Habitat Capacity 6.6 Spatial Heterogeneity 6.7 Summary 7. Verification, Validation, Replication, and Reproducibility 7.1 Overview 7.2 Verification and Validation (V&V) 7.2.1 Quality Assurance (QA) . 7.2.2 Verification and Validation (V&V) 7.3 Replication and Reproducibility (R&R) 7.4 Summary 8. Verification and Validation (V&V) of ABMs 8.1 Overview 8.2 Verification and Validation (V&V) of ABMs 8.3 Phase-wise Docking 8.3.1 Assumptions for the ABMs 8.3.2 Phase-wise Docking Results 8.4 Compartmental Docking 8.4.1 Implementations of the ABMs 8.4.2 Assumptions for the ABMs 8.4.3 Compartmental Docking Results 8.5 Summary 9. Replication and Reproducibility (R&R) of ABMs 9.1 Overview 9.1.1 Simulation Stochasticity 9.1.2 Boundary Types 9.2 Vector Control Interventions 9.2.1 Larval Source Management (LSM) 9.2.2 Insecticide-Treated Nets (ITNs) 9.2.3 Population Profiles for ITNs 9.2.4 Coverage Schemes for ITNs 9.2.5 Applying LSM in Isolation 9.2.6 Applying ITNs in Isolation 9.2.7 Applying LSM and ITNs in Combination 9.3 Simulation Results 9.3.1 Simulation Stochasticity 9.3.2 LSM in Isolation 9.3.3 Impact of Boundary Types 9.3.4 ITNs in Isolation 9.3.5 LSM and ITNs in Combination 9.4 Replication and Reproducibility (R&R) Guidelines 9.5 Discussion 9.6 Summary 10. A Landscape Epidemiology Modeling Framework 10.1 Overview 10.2 GIS in Public Health 10.3 The Study Area and the ABM 10.3.1 Features of the Spatial ABM 10.3.2 Vector Control Intervention Scenarios 10.4 The Geographic Information System (GIS) 10.4.1 The GIS-ABM Workflow 10.4.2 GIS Processing of Data Layers 10.4.3 Feature Counts 10.5 Simulations and Spatial Analyses 10.5.1 Output Indices 10.5.2 Hot Spot Analysis 10.5.3 Kriging Analysis 10.6 Results 10.6.1 Mosquito Abundance 10.6.2 Oviposition Count per Aquatic Habitat 10.6.3 Blood Meal Count per House 10.7 Discussion 10.7.1 Stochasticity and Initial Conditions 10.7.2 Model Calibration and Parameterization 10.7.3 Emergence 10.7.4 Complexity 10.7.5 Data Resolution (Granularity) 10.7.6 Spatial Analyses 10.7.7 Habitat-based Interventions 10.7.8 Miscellaneous Issues 10.8 Conclusions 11. The EMOD Individual-Based Model 11.1 Overview 11.1.1 Motivation: Modeling of Malaria Eradication 11.1.2 Questions that Arise in the Context of Malaria Eradication 11.1.3 Spatial Heterogeneity and Metapopulation Effects 11.1.4 Implications for Model Structure 11.1.4.1 Modeling Individuals and Infections 11.1.4.2 Modeling Mosquitoes 11.1.4.3 Modeling Campaign Elements 11.2 Model Structure 11.2.1 Human Demographics and Synthetic Population 11.2.2 Vector Ecology 11.2.3 Vector Transmission 11.2.4 Within-Host Disease Dynamics 11.2.5 Human Migration and Spatial Effects 11.2.6 Stochastic Ensembles 11.3 Results 11.3.1 Single-Village Simulations 11.3.2 Spatial Simulations: Garki District 11.3.3 Madagascar 11.4 Discussion APPENDIX A: Enzyme Kinetics Model A.1 Overview A.2 Stochastic Thermodynamic Models A.3 Poikilothermic Development Models A.3.1 Log-linear Models A.3.2 The Arrhenius Model A.3.3 The Eyring Equation A.3.4 The Gibbs Free Energy, Entropy and Enthalpy A.3.5 Incorporating Entropy and Enthalpy into Eyring Equation A.4 The Sharpe and DeMichele Model A.4.1 Energy States A.4.2 Exponential Distribution of Transition Times A.4.3 Probability Calculations A.5 The Schoolfield et al. Mod
• Edition: 1st
• Publisher Details: Hoboken : John Wiley & Sons
• Publication Date: 2015
• Extent: 1 online resource
• Subjects: 362.1969362; Malaria -- Research -- Mathematical models; Multiscale modeling
• Languages: English
• ISBNs: 9781118964361
• Related ISBNs: 9781118964378
• Notes: Note: Description based on CIP data; resource not viewed.
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