Modelling Parasite Transmission and Control (eBook)

EDWIN MICHAEL is currently a Senior Lecturer in infectious disease epidemiology at Imperial College London, UK, with a research focus on modelling the transmission and control of tropical parasitic and infectious diseases. His main interest lies in developing a system dynamics approach to gaining a better understanding of parasite transmission, immunology, genetics and economics, in order to develop integrated mathematical models of pathogen transmission as a tool for aiding the rational design, monitoring and evaluation of large-scale intervention programmes, ranging from vector control, chemotherapy to vaccinations. He has worked extensively in Africa (primarily East Africa), India, Vietnam and Papua New Guinea, particularly over the past decade (in partnership with international (WHO, World Bank) and national institutions), in translating research on disease population biology, spatial dynamics and public health decision-making for developing reliable model-based spatial decision support tools to aid the design, surveillance and evaluation of ecologically resilient and sustainable intervention programmes against parasitic diseases of major public health importance in developing countries. His current interest is in extending this work to developing integrated ecological, economic and social systems approaches for investigating interactions between climate change, ecosystem dynamics and the socio-ecology of disease transmission in vulnerable communities. ROBERT C. SPEAR is an engineer by training, having received the BS and MS degrees in Engineering Science and Mechanical Engineering, respectively, from the University of California at Berkeley and the PhD degree in Control Engineering from Cambridge University in 1968. After several years in the aerospace industry his interests turned to environmental issues and he returned to Berkeley in 1970 to take up a post-doctoral position in this field in the School of Public Health. He was appointed to a faculty position in 1971 and is now Professor of the Graduate School at Berkeley. His research interests focus on the assessment and quantification of human exposures to toxic and hazardous agents in the environment. His early work concerned the exposure of agricultural workers to pesticides. In more recent years his work has concerned applications of mathematical and statistical techniques in the assessment and control of exposures to both chemical and biological agents. For the past 15 years his work has been increasingly focused on determinants of the prevalence and control of the parasitic disease schistosomiasis in the mountainous regions of Sichuan Province in southwestern China.

Title Page 3
Copyright Page 4
DEDICATION 5
PREFACE 6
ABOUT THE EDITORS... 12
ABOUT THE EDITORS... 13
PARTICIPANTS 14
Table of Contents 16
ACKNOWLEDGEMENTS 21
Chapter 1 Progress in Modelling Malaria Transmission 22
Modelling Malaria Transmission, a Historical Introduction 22
Transmission Intensity and Its Estimations 25
Preferential Biting and Uneven Exposure 27
Immunity and the Infectious Reservoir 29
Malaria Transmission in Real Populations 30
Conclusion 31
References 31
Chapter 2 Vector Transmission Heterogeneity and the Population Dynamics and Control of Lymphatic Filariasis 34
Introduction 34
Lymphatic Filariasis Disease and Parasite Life Cycle 36
Mosquito Vectors of Lymphatic Filariasis 36
Vector-Parasite Infection Relationships 36
Quantifying the Mf-L3 Functional Response in Vector Populations 37
Derivation of Vector-Specific Models of Lymphatic Filariasis Transmission 39
Impact of Vector-Specific Infection Processes on Parasite System Stability, Persistence and Extinction 41
System Equilibria, Transitions and Stable States 41
System Resilience to Perturbations 43
System Hysteresis 44
Impact of Vector-Specific Infection Processes on Age Patterns of Infection 46
The Impact of Vector Genus on the Dynamics of Filariasis Control 47
Conclusion 47
References 50
Chapter 3 Modelling Multi-Species Parasite Transmission 53
Introduction 53
Simple Models for Multispecies Parasite Dynamics 53
Structure and Parameters of Models 54
Invasion Criteria 56
The Model without Direct Interactions 57
Competition among Parasites 60
Parasite Fertility Depending on Available Resources 60
Normal Approximations 63
Competition at Establishment. No Induced Mortality 64
Competition Acting on Parasite Fertility 65
Competition and Host Heterogeneity 66
Conclusion 69
References 70
Chapter 4 Metapopulation Models in Tick-Borne Disease Transmission Modelling 72
Introduction 72
Methods 73
Metapopulation Modelling 73
Variations within Patches 74
Patch Connectivity 74
Variations in the Surrounding Environment 74
Boundary Effects 74
Description of the Mathematical Model 74
Variations within Patches 75
Patch Connectivity 79
The Surrounding Environment 81
Boundary Effects 81
Conclusion 84
References 85
Chapter 5 Modelling Stochastic Transmission Processes in Helminth Infections 87
Introduction 87
Infection in a Single Host 88
Clumped Infection and Parasite-Induced Mortality 88
Explicit Solution of the Model 89
When Can This Type of Model Be Solved Explicitly? 90
Effect of Clumping and Parasite-Induced Mortality on Aggregation 90
Moment Closure 91
Acquired Immunity 91
Host Heterogeneity 92
Mating Probability and Population Genetics 92
Competition between Parasite Species 92
Infection among Multiple Hosts 93
Hybrid Models 93
Deterministic Models with Parasite Aggregation 94
Moment Closure for the Variance 95
Fully Stochastic Models 95
Mating Probability 96
Population Genetics and Antihelminthic Resistance 96
Stability and Population Cycles 96
Conclusion 97
References 97
Chapter 6 Modelling Environmentally-Mediated Infectious Diseases of Humans: Transmission Dynamics of Schistosomiasis in China 100
Introduction 100
Modelling Schistosome Transmission 102
The Model 102
Modelling Cercariae-Environment Interactions 104
Modelling Snail-Environment Interactions 106
Modelling Ova-Environment and Miracidia-Environment Interactions 109
Model Parameters 110
Environmental Data 112
Model Dynamics 112
Modelling Spatial Connectivity 114
Extending the Modelling Framework 114
Conclusion 116
References 116
Chapter 7 Parameter Estimation and Site-Specific Calibration of Disease Transmission Models 120
Introduction 120
Local Data 121
A Calibration Example 123
The Posterior Parameter Space 126
Bayesian Melding 129
Conclusion 131
References 132
Chapter 8 Modelling Malaria Population Structure and Its Implications for Control 133
Introduction 133
Adding Realism to the Basic Framework of the Ross-MacDonald Models 135
Heterogeneity in Biting Rates and Susceptibility 135
Superinfection 136
Incorporating Immunity 136
Modelling the Effects of Parasite Population Structure 138
Implications of Antigenic Diversity for Control 139
Emergence and Maintenance of Strain Structure 140
Sequence-Based Analysis of Population Structure of Malaria Parasite Antigens 141
Conclusion 143
References 145
Chapter 9 Mathematical Modelling of the Epidemiology of Tuberculosis 148
Introduction 148
TB Natural History 148
Mathematical Models of TB Transmission Dynamics 150
Modelling the Natural History of TB 150
Latent Period 150
Exogenous Reinfection 150
Active Disease 151
Recovery from TB Disease 151
Vaccination 152
Population Age Structure 152
Interactions with HIV 153
Contact Patterns 153
The Basic and Effective Reproductive Numbers of TB 153
Modelling Strains of TB 154
Inference of Tuberculosis Transmission Patterns from DNA Fingerprinting Data 154
Drug Resistance 154
Host Genetic Factors and Within-Host Modelling 155
TB-Control Strategies 156
Conclusion 157
References 157
Chapter 10 Modelling Trachoma for Control Programmes 162
Introduction 162
Disease Pathogenesis and Epidemiology 163
Antibiotic-Based Control Programmes 164
Methods 165
A First Mathematical Model of Trachoma 165
Recovery Rate 167
Infectivity 168
Parameter Estimation 168
Data 168
Prevalence of Disease Sequelae with Age 168
Disease Sequelae and Prior Infection Number 168
A Second Model Including an Active-Disease Class 169
Fitting the Model to Data 169
Results 170
Fitting the First Model to Static Infection and Disease Sequelae Data 170
Simulating Control Scenarios 171
The Effect of Mass Treatment on the Prevalence of Infection by Age 171
Age-Targeted Treatment 172
The Effect of Treatment on Active Disease 173
Conclusion 174
References 175
Chapter 11 Transmission Models and Management of Lymphatic Filariasis Elimination 178
Introduction 178
Transmission Models and Decisions in Parasite Management 179
Models and Quantifying Intervention Endpoint Targets 179
Quantifying Parasite Breakpoint Thresholds in the Human Population 179
Vector Infection Thresholds: Theory and Empirical Data 182
Models and Design of Optimal Filariasis Intervention Strategies 185
Modelling for Choosing Optimal Strategies 185
Choosing an Optimal Strategy Under Uncertainty 188
Models and Design of Monitoring Programs 189
Conclusion 190
References 191
Chapter 12 Disease Transmission Models for Public Health Decision-Making: Designing Intervention Strategies for Schistosoma japonicum 193
Introduction 193
Model Framework 194
A Crude Estimate of R0 for S. japonicum Based on Macdonald’s Model 197
Control Needed to Terminate S. japonicum Transmission Based on Macdonald’s Model 197
Problems Inherent in the Macdonald Model Assumptions 198
Modelling Control Dynamics 198
New Model Developments: Incorporating Population Heterogeneity and Connectivity 199
Conclusion 201
References 203
Chapter 13 Modelling Climate Change and Malaria Transmission 205
Introduction 205
Mathematical Model Development 206
Functional Forms for Incorporating Temperature and Rainfall Effects and the Derivation of R0 207
Vector Population Dynamics 210
Invasion Dynamics 212
Implications for R0 and Mapping Risk 216
Conclusion 218
References 219
Chapter 14 Modelling the Transmission of Trypanosoma cruzi: The Need for an Integrated Genetic Epidemiological and Population Genomics Approach 221
Introduction 221
Trypanosoma cruzi, World Champion of Pathogens for PopulationGenetics 222
The Isoenzyme Saga 222
The Molecular Biology Wave 223
The Sequencing, Genomic and Postgenomic Era 223
Is T. cruzi a “Good” Species? 223
The Population Structure of T. cruzi: Sex or No Sex? 223
The Second Actor: The Vector 226
The Host 227
The Future 228
Field Studies 228
Experimental Evolution 229
Conclusion 229
References 229
Index 233