Table of Contents

From the preface to the first edition xii

From the preface to the second edition xiii

Preface to the third edition xiv

1 The development of veterinary medicine 1

Historical perspective 1

Domestication of animals and early methods of healing 1

Changing concepts of the cause of disease 2

Impetus for change 4

Quantification in medicine 10

Contemporary veterinary medicine 11

Current perspectives 11

The fifth period 16

Recent trends 16

2 The scope of epidemiology 22

Definition of epidemiology 22

The uses of epidemiology 23

Types of epidemiological investigation 25

Epidemiological subdisciplines 26

Components of epidemiology 28

Qualitative investigations 28

Quantitative investigations 28

Epidemiology’s locale 32

The interplay between epidemiology and other sciences 32

The relationship between epidemiology and other diagnostic disciplines 32

Epidemiology within the veterinary profession 33

3 Causality 34

Philosophical background 34

Causal inference 35

Methods of acceptance of hypotheses 36

Koch’s postulates 37

Evans’ rules 37

Variables 38

Types of association 38

Confounding 40

Causal models 40

Formulating a causal hypothesis 42

Methods of deriving a hypothesis 43

Principles for establishing cause: Hill’s criteria 44

4 Describing disease occurrence 46

Some basic terms 46

Basic concepts of disease quantification 49

The structure of animal populations 50

Contiguous populations 50

Separated populations 52

Measures of disease occurrence 53

Prevalence 53

Incidence 53

The relationship between prevalence and incidence rate 56

Application of prevalence and incidence values 57

Mortality 57

Survival 58

Example of calculation of prevalence, incidence, mortality, case fatality and survival 60

Ratios, proportions and rates 61

Displaying morbidity and mortality values and demographic data 65

Mapping 65

Geographic base maps 67

Geographical information systems 69

5 Determinants of disease 75

Classification of determinants 75

Host determinants 78

Genotype 78

Age 79

Sex 79

Species and breed 80

Other host determinants 81

Agent determinants 82

Virulence and pathogenicity 82

Gradient of infection 85

Outcome of infection 86

Microbial colonization of hosts 87

Environmental determinants 88

Location 88

Climate 88

Husbandry 90

Stress 91

Interaction 92

Biological interaction 93

Statistical interaction 94

The cause of cancer 95

6 The transmission and maintenance of infection 98

Horizontal transmission 98

Types of host and vector 98

Factors associated with the spread of infection 100

Routes of infection 103

Methods of transmission 105

Long-distance transmission of infection 106

Vertical transmission 110

Types and methods of vertical transmission 110

Immunological status and vertical transmission 110

Transovarial and trans-stadial transmission in arthropods 110

Maintenance of infection 111

Hazards to infectious agents 111

Maintenance strategies 112

7 The ecology of disease 116

Basic ecological concepts 116

The distribution of populations 116

Regulation of population size 120

The niche 123

Some examples of niches relating to disease 124

The relationships between different types of animals and plants 126

Ecosystems 130

Biotope 130

Types of ecosystem 130

Landscape epidemiology 132

Nidality 132

Objectives of landscape epidemiology 133

8 Patterns of disease 137

Epidemic curves 137

The Reed–Frost model 140

Kendall’s waves 142

Trends in the temporal distribution of disease 144

Short-term trends 144

Cyclical trends 144

Long-term (secular) trends 145

True and false changes in morbidity and mortality 146

Detecting temporal trends: time series analysis 146

Trends in the spatial and temporal distribution of disease 150

Spatial trends in disease occurrence 150

Space–time clustering 151

9 The nature of data 152

Classification of data 152

Scales (levels) of measurement 153

Composite measurement scales 155

Data elements 156

Nomenclature and classification of disease 156

Diagnostic criteria 157

Sensitivity and specificity 158

Accuracy, refinement, precision, reliability and validity 159

Bias 160

Representation of data: coding 161

Code structure 162

Numeric codes 162

Alpha codes 163

Alphanumeric codes 164

Symbols 165

Choosing a code 165

Error detection 166

10 Surveillance 168

Some basic definitions and principles 168

Definition of surveillance 168

Goals of surveillance 169

Types of surveillance 169

Some general considerations 171

Sources of data 173

Mechanisms of surveillance 179

Surveillance networks 179

Surveillance in developing countries: participatory epidemiology 179

Techniques of data collection 184

Strengths and weaknesses of participatory epidemiology 186

Some examples of participatory epidemiology 186

11 Data collection and management 188

Data collection 188

Questionnaires 188

Quality control of data 195

Data storage 196

Database models 196

Non-computerized recording techniques 197

Computerized recording techniques 198

Data management 201

Changing approaches to computing 201

The Internet 203

Veterinary recording schemes 204

Scales of recording 204

Veterinary information systems 205

Some examples of veterinary databases and information systems 207

12 Presenting numerical data 214

Some basic definitions 214

Some descriptive statistics 215

Measures of position 216

Measures of spread 216

Statistical distributions 217

The Normal distribution 217

The binomial distribution 218

The Poisson distribution 218

Other distributions 218

Transformations 219

Normal approximations to the binomial and Poisson distributions 219

Estimation of confidence intervals 220

The mean 220

The median 221

A proportion 221

The Poisson distribution 221

Some epidemiological parameters 222

Other parameters 223

Bootstrap estimates 223

Displaying numerical data 224

Monitoring performance: control charts 224

13 Surveys 228

Sampling: some basic concepts 228

Types of sampling 229

Non-probability sampling methods 230

Probability sampling methods 230

What sample size should be selected? 232

Estimation of disease prevalence 232

Detecting the presence of disease 238

The cost of surveys 242

Calculation of confidence intervals 242

14 Demonstrating association 247

Some basic principles 247

The principle of a significance test 247

The null hypothesis 248

Errors of inference 248

One- and two-tailed tests 248

Independent and related samples 249

Parametric and non-parametric techniques 249

Hypothesis testing versus estimation 249

Sample size determination 250

Statistical versus clinical (biological) significance 250

Interval and ratio data: comparing means 252

Hypothesis testing 252

Calculation of confidence intervals 252

What sample size should be selected? 253

Ordinal data: comparing medians 254

Hypothesis testing 254

Calculation of confidence intervals 257

What sample size should be selected? 258

Nominal data: comparing proportions 258

Hypothesis testing 258

Calculation of confidence intervals 261

What sample size should be selected? 261

E2 test for trend 262

Correlation 263

Multivariate analysis 264

Statistical packages 265

15 Observational studies 266

Types of observational study 266

Cohort, case-control and cross-sectional studies 266

Ecological studies 269

Measures of association 269

Relative risk 269

Odds ratio 270

Attributable risk 272

Attributable proportion 273

Interaction 274

The additive model 275

Bias 276

Controlling bias 278

What sample size should be selected? 281

Calculating the power of a study 282

Calculating upper confidence limits 283

Multivariate techniques 284

The logistic model 284

16 Clinical trials 289

Definition of a clinical trial 289

Design, conduct and analysis 291

The trial protocol 291

The primary hypothesis 291

The experimental unit 293

The experimental population 294

Admission and exclusion criteria 294

Blinding 294

Randomization 295

Trial designs 296

What sample size should be selected? 297

Losses to `follow-up’ 298

Compliance 298

Terminating a trial 299

Interpretation of results 299

Meta-analysis 300

Goals of meta-analysis 300

Components of meta-analysis 301

Sources of data 301

Data analysis 302

17 Diagnostic testing 305

Serological epidemiology 305

Assaying antibodies 306

Methods of expressing amounts of antibody 306

Quantal assay 307

Serological estimations and comparisons in populations 308

Antibody prevalence 308

Rate of seroconversion 309

Comparison of antibody levels 309

Interpreting serological tests 311

Refinement 311

Accuracy 312

Evaluation and interpretation of diagnostic tests 313

Sensitivity and specificity 313

Predictive value 316

Likelihood ratios 318

ROC curves 321

Aggregate-level testing 323

Multiple testing 323

Diagnostic tests in import risk assessment 325

Guidelines for validating diagnostic tests 327

Agreement between tests 327

Practical application of diagnostic tests 329

18 Comparative epidemiology 331

Types of biological model 331

Cancer 332

Monitoring environmental carcinogens 332

Identifying causes 333

Comparing ages 334

Some other diseases 336

Diseases with a major genetic component 336

Some non-infectious diseases 337

Diseases associated with environmental pollution 337

Reasoning in comparative studies 338

19 Modelling 340

Types of model 341

Modelling approaches 341

Deterministic differential calculus modelling 341

Stochastic differential calculus modelling 344

Empirical simulation modelling 345

Process simulation modelling 346

Monte Carlo simulation modelling 347

Matrix population modelling 349

Network population modelling 351

Systems modelling 352

The rational basis of modelling for active disease control 352

Available knowledge, and the functions of models 352

From theory to fact 353

Model-building 354

20 The economics of animal disease 357

Popular misconceptions 357

Economic concepts and principles 358

Disease as an economic process 359

Assessing the economic costs of disease 361

Optimum control strategies 361

Cost–benefit analysis of disease control 363

Partial farm budgets 363

Social cost–benefit analysis 364

21 Health schemes 368

Private health and productivity schemes 368

Structure of private health and productivity schemes 368

Dairy health and productivity schemes 370

Pig health and productivity schemes 372

Sheep health and productivity schemes 373

Beef health and productivity schemes 375

National schemes 378

Accredited/attested herds 378

Health schemes 378

Companion-animal schemes 379

22 The control and eradication of disease 384

Definition of `control’ and `eradication’ 384

Strategies of control and eradication 385

Important factors in control and eradication programmes 393

Outbreak investigation 398

Cause known: foot-and-mouth disease 398

Cause unknown: chronic copper poisoning 400

Veterinary medicine in the 21st century 401

Livestock medicine 401

Companion-animal medicine 402

General reading 404

Appendices 406

References 503

Index 593

About the Author

Mike Thrusfield is at the University of Edinburgh, Scotland, UK.