Veterinary Epidemiology (eBook)
John Wiley & Sons (Verlag)
978-1-118-28026-3 (ISBN)
A comprehensive introduction to the role of epidemiology in veterinary medicine
This fully revised and expanded edition of Veterinary Epidemiology introduces readers to the field of veterinary epidemiology. The new edition also adds new chapters on the design of observational studies, validity in epidemiological studies, systematic reviews, and statistical modelling, to deliver more advanced material.
This updated edition begins by offering an historical perspective on the development of veterinary medicine. It then addresses the full scope of epidemiology, with chapters covering causality, disease occurrence, determinants, disease patterns, disease ecology, and much more.
Veterinary Epidemiology, Fourth Edition:
? Features updates of all chapters to provide a current resource on the subject of veterinary epidemiology
? Presents new chapters essential to the continued advancement of the field
? Includes examples from companion animal, livestock, and avian medicine, as well as aquatic animal diseases
? Focuses on the principles and concepts of epidemiology, surveillance, and diagnostic-test validation and performance
? Includes access to a companion website providing multiple choice questions
Veterinary Epidemiology is an invaluable reference for veterinary general practitioners, government veterinarians, agricultural economists, and members of other disciplines interested in animal disease. It is also essential reading for epidemiology students at both the undergraduate and postgraduate levels.
MICHAEL THRUSFIELD is Professor of Veterinary Epidemiology at the Royal (Dick) School of Veterinary Studies in the University of Edinburgh in Edinburgh, UK.
ROBERT CHRISTLEY is Professor of Epidemiology and One Health at the Institute of Infection and Global Health and the Institute of Veterinary Science in the University of Liverpool in Liverpool, UK.
A comprehensive introduction to the role of epidemiology in veterinary medicine This fully revised and expanded edition of Veterinary Epidemiology introduces readers to the field of veterinary epidemiology. The new edition also adds new chapters on the design of observational studies, validity in epidemiological studies, systematic reviews, and statistical modelling, to deliver more advanced material. This updated edition begins by offering an historical perspective on the development of veterinary medicine. It then addresses the full scope of epidemiology, with chapters covering causality, disease occurrence, determinants, disease patterns, disease ecology, and much more. Veterinary Epidemiology, Fourth Edition: Features updates of all chapters to provide a current resource on the subject of veterinary epidemiology Presents new chapters essential to the continued advancement of the field Includes examples from companion animal, livestock, and avian medicine, as well as aquatic animal diseases Focuses on the principles and concepts of epidemiology, surveillance, and diagnostic-test validation and performance Includes access to a companion website providing multiple choice questions Veterinary Epidemiology is an invaluable reference for veterinary general practitioners, government veterinarians, agricultural economists, and members of other disciplines interested in animal disease. It is also essential reading for epidemiology students at both the undergraduate and postgraduate levels.
MICHAEL THRUSFIELD is Professor of Veterinary Epidemiology at the Royal (Dick) School of Veterinary Studies in the University of Edinburgh in Edinburgh, UK. ROBERT CHRISTLEY is Professor of Epidemiology and One Health at the Institute of Infection and Global Health and the Institute of Veterinary Science in the University of Liverpool in Liverpool, UK.
Title Page 5
Copyright 6
Contents 9
Contributors 20
From the preface to the first edition 21
From the preface to the second edition 22
From the preface to the third edition 23
Preface to the fourth edition 24
About the companion website 26
Chapter 1 The development of veterinary medicine 27
Historical perspective 27
Domestication of animals and early methods of healing 27
Changing concepts of the cause of disease 28
Impetus for change 31
Quantification in medicine 36
Contemporary veterinary medicine 38
Current perspectives 38
The fifth period 45
Recent trends 46
Further reading 51
Chapter 2 The scope of epidemiology 54
Definition of epidemiology 54
The uses of epidemiology 55
Types of epidemiological investigation 58
Epidemiological subdisciplines 59
Components of epidemiology 61
Qualitative investigations 61
Quantitative investigations 62
Epidemiology´s locale 65
The interplay between epidemiology and other sciences 65
The relationship between epidemiology and other diagnostic disciplines 66
Epidemiology within the veterinary profession 66
Further reading 67
Chapter 3 Causality 68
Philosophical background 68
Causal inference 69
Methods of acceptance of hypotheses 70
Koch´s postulates 71
Evans´ rules 71
Variables 72
Types of association 72
Non-statistical association 72
Statistical association 72
Confounding 75
Causal models 76
Formulating a causal hypothesis 79
Methods of deriving a hypothesis 79
Principles for establishing cause: Hill´s criteria 81
Further reading 82
Chapter 4 Describing disease occurrence 84
Some basic terms 84
Basic concepts of disease quantification 87
The structure of animal populations 88
Contiguous populations 88
Separated populations 91
Measures of disease occurrence 93
Prevalence 93
Incidence 93
The relationship between prevalence and incidence rate 96
Application of prevalence and incidence values 98
Mortality 98
Survival 99
Example of calculation of prevalence, incidence, mortality, case fatality and survival 101
Ratios, proportions and rates 102
Mapping 106
Geographic base maps 106
Further reading 110
Chapter 5 Determinants of disease 112
Classification of determinants 112
Host determinants 115
Genotype 115
Age 116
Sex 117
Species and breed 118
Behaviour 119
Other host determinants 119
Agent determinants 120
Virulence and pathogenicity 120
Gradient of infection 123
Outcome of infection 124
Microbial colonization of hosts 126
Environmental determinants 127
Location 127
Climate 127
Husbandry 130
Stress 131
Interaction 132
Biological interaction 134
Statistical interaction 135
The cause of cancer 136
Further reading 138
Chapter 6 The transmission and maintenance of infection 141
Horizontal transmission 141
Types of host and vector 141
Factors associated with the spread of infection 144
Routes of infection 147
Methods of transmission 149
Long-distance transmission of infection 151
Vertical transmission 155
Types and methods of vertical transmission 155
Immunological status and vertical transmission 155
Transovarial and trans-stadial transmission in arthropods 156
Maintenance of infection 157
Hazards to infectious agents 157
Maintenance strategies 158
Transboundary diseases 161
Further reading 162
Chapter 7 The ecology of disease 164
Basic ecological concepts 165
The distribution of populations 165
Regulation of population size 168
The niche 174
Some examples of niches relating to disease 176
The relationships between different types of animals and plants 178
Ecosystems 181
Types of ecosystem 182
Landscape epidemiology 184
Nidality 185
Objectives of landscape epidemiology 187
Landscape characteristics determining disease distribution 190
Further reading 191
Chapter 8 Patterns of disease 194
Epidemic curves 194
Kendall´s Threshold Theorem 194
Basic reproductive number (R0) 195
Dissemination rate 198
Common-source and propagating epidemics 198
The Reed–Frost model 199
Kendall´s waves 201
Trends in the temporal distribution of disease 203
Short-term trends 203
Cyclical trends 204
Long-term (secular) trends 205
True and false changes in morbidity and mortality 206
Detecting temporal trends: time series analysis 206
Trends in the spatial and temporal distribution of disease 212
Spatial trends in disease occurrence 212
Space–time clustering 212
Further reading 213
Chapter 9 Comparative epidemiology 215
Types of biological model 215
Cancer 217
Monitoring environmental carcinogens 217
Identifying causes 218
Comparing ages 219
Some other diseases 222
Diseases with a major genetic component 222
Some non-infectious diseases 223
Diseases associated with environmental pollution 224
Reasoning in comparative studies 225
Further reading 225
Chapter 10 The nature of data 227
Classification of data 227
Scales (levels) of measurement 227
Composite measurement scales 230
Data elements 231
Nomenclature and classification of disease 231
Diagnostic criteria 233
Sensitivity and specificity 234
Accuracy, refinement, precision, reliability and validity 235
Bias 236
Representation of data: coding 236
Code structure 237
Numeric codes 238
Alpha codes 239
Alphanumeric codes 240
Symbols 241
Choosing a code 241
Error detection 242
Further reading 243
Chapter 11 Data collection and management 245
Data collection 245
Questionnaires 245
Quality control of data 254
Data storage 255
Database models 255
Non-computerized recording techniques 257
Computerized recording techniques 258
Veterinary recording schemes 258
Scales of recording 258
Veterinary information systems 260
Some examples of veterinary databases and information systems 263
Geographical information systems 270
Further reading 274
Chapter 12 Presenting numerical data 277
Some basic definitions 277
Some descriptive statistics 278
Measures of position 279
Measures of spread 280
Statistical distributions 280
The Normal distribution 280
The binomial distribution 281
The Poisson distribution 281
Other distributions 282
Transformations 282
Normal approximations to the binomial and Poisson distributions 283
Estimation of confidence intervals 283
The mean 283
The median 284
A proportion 284
The Poisson distribution 285
Some epidemiological parameters 286
Other parameters 287
Bootstrap estimates 287
Displaying numerical data 288
Displaying qualitative data 288
Displaying quantitative data 289
Monitoring performance: control charts 292
Further reading 295
Chapter 13 Surveys 296
Sampling: some basic concepts 296
Types of sampling 298
Non-probability sampling methods 298
Probability sampling methods 298
What sample size should be selected? 301
Estimation of disease prevalence 301
Detecting the presence of disease 310
The cost of surveys 316
Calculation of confidence intervals 316
Further reading 320
Chapter 14 Demonstrating association 322
Some basic principles 322
The principle of a significance test 322
The null hypothesis 323
Errors of inference 323
Multiple significance testing 324
One- and two-tailed tests 324
Independent and related samples 325
Parametric and non-parametric techniques 325
Hypothesis testing versus estimation 326
Sample-size determination 326
Statistical versus clinical (biological) significance 326
Interval and ratio data: comparing means 328
Hypothesis testing 328
Calculation of confidence intervals 329
What sample size should be selected? 330
Ordinal data: comparing medians 330
Hypothesis testing 330
Calculation of confidence intervals 334
What sample size should be selected? 335
Nominal data: comparing proportions 335
Hypothesis testing 336
Calculation of confidence intervals 339
What sample size should be selected? 340
?2 test for trend 340
Correlation 342
Multivariate analysis 343
Statistical packages 344
Further reading 344
Chapter 15 Observational studies 345
Types of observational study 345
Cohort, case-control and cross-sectional studies 345
Measures of association 347
Relative risk 347
Odds ratio 349
Attributable risk 351
Attributable proportion 353
Interaction 354
The additive model 354
Bias 356
Controlling bias 358
What sample size should be selected? 361
Calculating the power of a study 362
Further reading 364
Chapter 16 Design considerations for observational studies 365
Descriptive observational studies 365
Analytical observational studies 366
Design of cohort studies 366
Design of case-control studies 372
Design of cross-sectional analytical studies 378
Overview of other study designs 380
Further reading 385
Chapter 17 Clinical trials 387
Definition of a clinical trial 387
Design, conduct and analysis 390
The trial protocol 390
The primary hypothesis 390
The experimental unit 393
The experimental population 394
Admission and exclusion criteria 394
Blinding 395
Randomization 395
Trial designs 396
What sample size should be selected? 398
Losses to follow-up 399
Compliance 399
Terminating a trial 400
Interpretation of results 400
Meta-analysis 401
Goals of meta-analysis 402
Components of meta-analysis 403
Sources of data 403
Data analysis 404
Further reading 406
Chapter 18 Validity in epidemiological studies 409
Types of epidemiological error 409
Accuracy, precision and validity in epidemiological studies 410
Background factors 411
Interpretation bias 411
Selection bias 412
Information bias 416
Examples of information biases 416
Statistical interaction and effect-measure modification 418
Confounding 418
Criteria for confounding 419
Confounding and causal diagrams 420
Controlling confounding 420
Errors in analysis 421
Communication bias 421
Further reading 422
Chapter 19 Systematic reviews 423
Evidence synthesis 423
Overview of systematic reviews 423
Differences between systematic reviews and narrative reviews 424
Questions that are suitable for systematic reviews 424
Types of review questions suitable for systematic reviews 425
Extensive search of the literature 425
Assessment of risk of bias in a systematic review 426
Steps of a systematic review 426
Step 1: Define the review question and the approach to conduct of the review (i.e., create a protocol) 428
Step 2: Comprehensive search for studies 429
Step 3: Select relevant studies from the search results 432
Step 4: Collect data from relevant studies 433
Step 5: Assess the risk of bias in relevant studies 435
Step 6: Synthesize the results 438
Step 7: Presenting the results 442
Step 8: Interpret the results and discussion 445
Further reading 445
Chapter 20 Diagnostic testing 447
Serological epidemiology 447
Assaying antibodies 447
Methods of expressing amounts of antibody 447
Quantal assay 449
Serological estimations and comparisons in populations 450
Antibody prevalence 450
Rate of seroconversion 451
Comparison of antibody levels 452
Interpreting serological tests 453
Refinement 453
Accuracy 455
Evaluation and interpretation of diagnostic tests 456
Sensitivity and specificity 456
Youden´s index 459
Diagnostic odds ratio 460
Predictive value 460
Likelihood ratios 462
ROC curves 467
Aggregate-level testing 469
Multiple testing 470
Diagnostic tests in import risk assessment 472
Guidelines for validating diagnostic tests 473
Validating diagnostic tests when there is no gold standard 474
Agreement between tests 476
Practical application of diagnostic tests 482
Further reading 482
Chapter 21 Surveillance 483
Some basic definitions and principles 483
Definition of surveillance 483
Goals of surveillance 484
Types of surveillance 485
Some general considerations 487
Sources of data 490
Mechanisms of surveillance 497
Surveillance networks 501
Surveillance in less-economically-developed countries: participatory epidemiology 501
Principles of participatory epidemiology 503
Techniques of data collection 504
Strengths and weaknesses of participatory epidemiology 507
Some examples of participatory epidemiology 509
Companion-animal surveillance 509
Wildlife surveillance 511
Aquatic-animal surveillance 511
Assessing the performance of surveillance systems 512
Improving the performance of surveillance: risk-based surveillance 512
Further reading 514
Chapter 22 Statistical modelling 518
Simple linear regression models 518
Key assumptions of linear regression models 521
Modelling more than one input variable 525
Handling categorical input variables 526
Non-linear modelling of quantitative input variables 528
Additive models 528
Categorization of the input variable 528
Transformation of the input and/or output variable 530
Piece-wise regression 530
Modelling interactions 531
Model selection 532
Modelling binary outcomes 535
Generalized linear models 537
The multiple logistic regression model 537
Model selection for logistic regression models 538
Diagnostic checking of logistic regression models 539
Generalized additive models 540
Modelling clustered data 540
Further reading 545
Chapter 23 Mathematical modelling 546
Types of model 547
Modelling approaches 547
Deterministic differential calculus modelling 547
Stochastic differential calculus modelling 551
Empirical simulation modelling 552
Process simulation modelling 553
Monte Carlo simulation modelling 554
Matrix population modelling 556
Network population modelling 558
Contact-network modelling 559
Systems modelling 560
The rational basis of modelling for active disease control 560
Available knowledge, and the functions of models 560
From theory to factThis section may be considered as a logical continuation of Chapter . Moreover, it is applicable to all ... 561
Model building 562
Further reading 564
Chapter 24 Risk analysis 566
Definition of risk 566
Risk analysis and the ‘precautionary principle’ 569
Risk analysis in veterinary medicine 569
Components of risk analysis 571
Hazard identification 572
Risk assessment 572
Risk management 574
Risk communication 577
Qualitative or quantitative assessment? 577
Semi-quantitative risk assessment 577
Qualitative risk analysis 578
Framework for qualitative risk assessment 578
Qualitative risk assessment during epidemics 580
Quantitative risk analysis 582
Framework for quantitative risk assessment 582
What level of risk is acceptable? 586
Further reading 589
Chapter 25 Economics and veterinary epidemiology 591
General economic concepts 591
Production functions 591
Disease and animal production functions 592
Value and money 593
Money and prices 593
Opportunity cost 594
Technical and economic efficiency 594
Positive and normative economics 595
Levels of aggregation 595
Disease contained at farm level 595
Disease not contained at farm level 596
Zoonotic disease 596
Disease at international level 597
Evaluating disease-control policies 601
Components of disease costs 602
Optimum control strategies 603
Partial budgets 605
Social cost–benefit analysis (CBA) 605
Summary of methods 608
Further study 608
Further reading 610
Chapter 26 Health schemes 612
Private health and productivity schemes 612
Structure of private health and productivity schemes 612
Dairy health and productivity schemes 614
Pig health and productivity schemes 617
Sheep health and productivity schemes 618
Beef health and productivity schemes 620
National schemes 623
Accredited/attested herds 623
Health schemes 624
Companion-animal schemes 625
Further reading 629
Chapter 27 The control and eradication of disease 630
Definition of ‘control’ and ‘eradication’ 630
Strategies of control and eradication 631
Important factors in control and eradication 642
Outbreak investigation 649
Cause known: foot-and-mouth disease 649
Cause unknown: chronic copper poisoning 651
The epidemiological approach to investigation of outbreaks 652
Veterinary medicine in the 21st century 654
Livestock medicine 654
Companion-animal medicine 655
Further reading 656
General reading 659
Books 659
Proceedings 659
Journals 660
Appendices 661
Appendix I Glossary of terms 662
Appendix II Basic mathematical notation and terms 667
Summation notation: ? 667
Order of calculation 668
Magnitude notation 668
Approximation notation 668
Estimation notation 668
Factorial notation: x! 668
Modulus notation: |x| 668
Appendix III Some computer software 669
Appendix IV Veterinary epidemiology on the Internet 674
Appendix V Student´s t-distribution 676
Appendix VI Multipliers used in the construction of confidence intervals based on the Normal distribution, for selected levels of con... 677
Appendix VII Values of exact 95% confidence limits for proportions (From Beyer, 1968) 678
Appendix VIII Values from the Poisson distribution for calculating 90%, 95% and 99% confidence intervals for observed numbers from 0 to 100 684
Appendix IX The ?2 distribution 686
Appendix X Technique for selecting a simple random sample 687
Appendix XI Sample sizes 689
Appendix XII The probability of detecting a small number of cases in a population (Adapted from Cannon and Roe, 1982) 695
Appendix XIII The probability of failure to detect cases in a population (From Cannon and Roe, 1982) 697
Appendix XIV Sample sizes required for detecting disease with probability, p1, and threshold number of positives 698
Appendix XV Probabilities associated with the upper tail of the Normal distribution (Derived from Beyer, 1981) 702
Appendix XVI Lower- and upper-tail probabilities for Wx, the Wilcoxon–Mann–Whitney rank-sum statistic (From Siegel and Castellan, 1988) 704
Appendix XVII Critical values of T+ for the Wilcoxon signed ranks test (From Siegel and Castellan, 1988) 709
Appendix XVIII Values of K for calculating 95% confidence intervals for the difference between population medians for two independent samples (From Altman et al., 2000) 711
Appendix XIX Values of K* for calculating 95% confidence intervals for the difference between population medians for two related samples (From Altman et al., 2000) 714
Appendix XX Common logarithms (log10) of factorials of the integers 1–999 (From Lentner, 1982) 715
Appendix XXI The correlation coefficient 717
Appendix XXII The variance-ratio (F) distribution 718
References 720
Index 867
EULA 891
| Erscheint lt. Verlag | 15.2.2018 |
|---|---|
| Co-Autor | Robert Christley |
| Sprache | englisch |
| Themenwelt | Veterinärmedizin |
| Schlagworte | Animal diseases • animal health • Causality • determinants • Diagnostic Tests • disease occurrences • ecology disease • Epidemiological studies • Epidemiologie • Epidemiologie, Gesundheitswesen u. Statistik • epidemiology • <p>Veterinary epidemiology • Observational Studies • Patterns • preventative care</p> • statistical modeling • Surveillance • Systematic reviews • Veterinärmedizin • Veterinary Epidemiology, Public Health & Statistics • Veterinary Medicine |
| ISBN-10 | 1-118-28026-1 / 1118280261 |
| ISBN-13 | 978-1-118-28026-3 / 9781118280263 |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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