Veterinary Epidemiology

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

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