Contents Chapter 1 Basic concept of epidemic-logistics 1 1.1 Basic knowledge of epidemic dynamics 1 1.1.1 Adequate contact rate and incidence 2 1.1.2 Basic reproduction number 3 1.2 Epidemics control and logistics operations 4 1.2.1 Preparedness 4 1.2.2 Outbreak investigation 5 1.2.3 Response 6 1.2.4 Evaluation 7 1.3 Future directions for epidemic-logistics research 8 References 10 Chapter 2 Epidemic dynamics modeling and analysis 13 2.1 Epidemic dynamics in anti-bioterrorism system 13 2.1.1 Introduction 13 2.1.2 SIQRS epidemic diffusion model 15 2.1.3 SEIQRS epidemic diffusion model 19 2.1.4 Computational experiments and result analysis 21 2.2 Epidemic dynamics modeling for influenza 24 2.2.1 Introduction 24 2.2.2 SEIRS model with small world network 25 2.2.3 Emergency demand base on epidemic diffusion model 29 2.2.4 Numerical test 30 2.3 Epidemic dynamics considering population migration 33 2.3.1 Introduction 33 2.3.2 Epidemic model with population migration 34 2.3.3 Model analysis 35 2.3.4 Numerical test 40 References 43 Chapter 3 Mixed distribution mode for emergency resources in anti-bioterrorism system 47 3.1 Introduction 47 3.2 Literature review 48 3.2.1 Literature related to epidemic prevention and control 49 3.2.2 Literature related to emergency distribution 50 3.3 Demand forecasting based on epidemic dynamics 51 3.3.1 SEIQRS model based on small-world network 51 3.3.2 Demand for emergency resources 52 3.4 Model formulations 53 3.4.1 Point-to-point distribution mode with no vehicle constraints 53 3.4.2 The multi-depot, multiple traveling salesmen distribution mode with vehicle constraints 54 3.4.3 The mixed-collaborative distribution mode 56 3.5 Solution procedures 58 3.5.1 Operating instructions for genetic algorithms 58 3.5.2 The solution procedure 59 3.6 Computational experiments and result analysis 60 3.6.1 Comparison and analysis for each stockpile depot 61 3.6.2 Comparison and analysis for total distance and timeliness 63 3.7 Conclusions 64 References 64 Chapter 4 Epidemic logistics with demand information updating—ModelⅠ: Medical resource is enough 67 4.1 Introduction 67 4.2 Literature review 68 4.2.1 Epidemic diffusion modeling 68 4.2.2 Medical resource allocation modeling 69 4.3 The mathematical model 70 4.3.1 SEIRS epidemic diffusion model 71 4.3.2 The forecasting model for the time-varying demand 73 4.3.3 Time-space network of the medicine logistics 74 4.4 Solution methodology 77 4.5 Numerical tests 78 4.5.1 A numerical example 78 4.5.2 Model comparison 81 4.5.3 Sensitivity analysis 83 4.6 Conclusions 84 References 85 Chapter 5 Epidemic logistics with demand information updating—ModelⅡ: Medical resource is limited 88 5.1 Introduction 88 5.2 Epidemic diffusion analysis and demand forecasting 91 5.2.1 Influenza diffusion analysis 91 5.2.2 Demand forecasting 93 5.3 The dynamic medical resources allocation model 95 5.3.1 Model specification 95 5.3.2 Notation 96 5.3.3 Model formulation 96 5.3.4 Solution procedure 97 5.4 Numerical example and discussion 97 5.4.1 Numerical example 97 5.4.2 Comparison and discussion 100 5.4.3 A short sensitivity analysis 102 5.5 Conclusions 102 References 103 Chapter 6 Integrated optimization model for two-level epidemic-logistics network 106 6.1 Introduction 106 6.2 Problem description 107 6.2.1 SEIR epidemic diffusion model 108 6.2.2 Forecasting model for the time-varying demand 109 6.2.3 Forecasting model for the time-varying inventory 111 6.3 Optimization model and solution methodology 111 6.3.1 The integrated optimization model 111 6.3.2 Solution methodology 113 6.4 A numerical example and implications 117 6.4.1 A numerical example 117 6.4.2 A short sensitivity analysis 122 6.5 Conclusions 123 References 124 Chapter 7 Integrated optimization model for three-level epidemic-logistics network 125 7.1 Introduction 125 7.2 Problem description 127 7.2.1 Model framework 127 7.2.2 Time-varying forecasting method for the dynamic demand 128 7.2.3 Dynamic demand and inventory for the UHD 129 7.3 Optimization model and solution procedure 129 7.3.1 Optimization model 129 7.3.2 Solution procedure 131 7.4 Numerical example 132 7.5 Conclusions 136 References 137 Chapter 8 A novel FPEA model for medical resources allocation in an epidemic control 139 8.1 Introduction 139 8.2 The mathematical model 141 8.2.1 Forecasting phase 142 8.2.2 Planning phase 144 8.2.3 Execution phase 150 8.2.4 Loop closed 150 8.3 Numerical example 152 8.3.1 Test for forecasting phase 152 8.3.2 Test for logistic planning phase 153 8.3.3 Test for adjustment phase 157 8.4 Conclusions 159 References 159 Chapter 9 Integrated planning for public health emergencies: A modified model for controlling H1N1 pandemic 162 9.1 Introduction 162 9.2 Literature review 163 9.3 Model formulation 166 9.3.1 Epidemic compartmental model 166 9.3.2 Resource allocation model 169 9.3.3 Model solution 170 9.4 Case study 171 9.4.1 Background and parameters setting 171 9.4.2 Test results 173 9.4.3 Discussion 175 9.5 Conclusions 177 References 179 Chapter 10 Logistics planning for hospital pharmacy trusteeship under a hybrid of uncertainties 182 10.1 Introduction 182 10.2 Literature review 184 10.2.1 VMI in hospital 184 10.2.2 Logistics planning with different influence factors 185 10.3 Time-space network model 187 10.3.1 Network structure 187 10.3.2 Deterministic planning model 190 10.3.3 Stochastic planning model 192 10.4 Solution algorithms and evaluation methods 195 10.4.1 Solution method for DPM 195 10.4.2 Solution method for SPM 196 10.4.3 Evaluation method 197 10.5 Numerical tests 197 10.5.1 Data setting 197 10.5.2 Test results 197 10.5.3 Sensitivity analysis 200 10.6 Conclusions 202 References 203 Chapter 11 Medical resources order and shipment in community health service centers 206 11.1 Introduction 206 11.2 Literature review 207 11.3 Modeling approach 208 11.3.1 Network structure 209 11.3.2 The deterministic model (DM) 210 11.3.3 The stochastic model (SM) 211 11.4 Solution procedure and evaluation method 212 11.4.1 Solution procedure 212 11.4.2 Evaluation method 213 11.5 Numerical tests 214 11.5.1 Parameters setting 214 11.5.2 Test results 214 11.5.3 Sensitivity analysis 215 11.6 Conclusions 217 References 218 Chapter 12 Three short time-space network models for medicine management 220 12.1 ModelⅠ: A basic time-space network model 220 12.1.1 Introduction 220 12.1.2 The time-space network model 221 12.1.3 Solution algorithm 224 12.1.4 Numerical tests 224 12.1.5 Conclusions 226 12.2 Model Ⅱ: An improved time-space network model 227 12.2.1 Introduction 227 12.2.2 Model formulation 228 12.2.3 The solution procedure 232 12.2.4 Numerical tests 233 12.2.5 Conclusions 236 12.3 Model Ⅲ: A chance-constrained programming model based on time-space network 237 12.3.1 Introduction 237 12.3.2 Model formulation 237 12.3.3 The solution procedure 240 12.3.4 Numerical tests 241 12.3.5 Conclusions 244 References 244 Chapter 13 Epidemic-logistics network considering time windows and service level 246 13.1 Emergency materials distribution with time windows 246 13.1.1 Introduction 246 13.1.2 SIR epidemic model 248 13.1.3 Emergency materials distribution network with time windows 248 13.1.4 Numerical tests 250 13.1.5 Discussion 253 13.1.6 Conclusions 255 13.2 An improved location-allocation model for emergency logistics network design 255 13.2.1 Introduction 256 13.2.2 Model formulation 257 13.2.3 Solution procedure 260 13.2.4 Numerical test 260 13.2.5 Conclusions 263 References 263 Appendix A 266 Appendix B 268 B1 Model validation 268 B2 Optimization results with different budget sizes 270 B3 Impact of different intervention starting dates 271 Reference 272
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