Full Description
This successful book, now in its third edition, continues to provide a comprehensive introduction to the role of epidemiology in veterinary medicine.
Since the publication of the second edition there has been considerable expansion in the application of veterinary epidemiology: more quantitative methods are available, challenges such as the epidemic of foot-and-mouth disease in Europe in 2001 have required epidemiological investigation, and epidemiological analyses have taken on further importance with the emergence of evidence-based veterinary medicine.
In this edition:
Completely revised and expanded chapters;
Increased attention given to the principles and concepts of epidemiology, surveillance, and diagnostic-test validation and performance;
Many examples are drawn from both large and small animal medicine, and from the developing as well as the developed world
This paperback edition includes a new section on risk analysis.
Veterinary Epidemiology is an invaluable reference source for veterinary general practitioners, government veterinarians, agricultural economists and members of other disciplines interested in animal disease. It will also be essential reading for undergraduate and intermediate-level postgraduate students of epidemiology.
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
Ê2 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
