Download Veterinary Epidemiology Epidemiology VM 7585 Spring Semester

Veterinary Epidemiology
Epidemiology VM 7585
Spring Semester 2017
Course coordinator Dr. David Wilson, email [email protected], cell phone (435) 760-3731
Learning objectives (in three categories):
Gaining factual knowledge (terminology, classifications, methods)
Exposed, Non-exposed, Diseased, Non-Diseased 2 x 2 tables
Relative Risk
Odds Ratio
Interpreting confidence intervals
Screening vs. diagnostic tests
Reliability - % agreement, Kappa statistic
Precision and Accuracy
Sensitivity
Specificity
Test threshold/cutpoint
Positive Predictive Value (Predictive Value of a Positive Test)
Negative Predictive Value (Predictive Value of a Negative Test)
Sampling to detect the presence or absence of disease
Sampling to estimate the prevalence/proportion of disease
Herd Sensitivity
Prevalence
Incidence
P=IxD
Cumulative Incidence
Basic reproductive number
Herd/group immunity
Vaccine efficacy
Filling blocks - some practical considerations
Power and sample size calculation
Direct sample size calculation
“What if” sample size calculation
Learning fundamental principles, generalizations, or theories
Cause vs. association
Limitations of cohort and case-control studies
Effect of prevalence on predictive values
Case definition
Isolation/quarantine
Reservoir
Transmission routes
Latent period
Incubation period
Endemic vs. epidemic disease
Is it really an outbreak?
Investigations
Analysis of data
Intervention strategy
Monitoring and records
Facilitating compliance with record keeping
Eradicable disease – characteristics
Hierarchy of types of studies/information sources regarding disease
Descriptive Studies
Experimentally induced vs. experimental study of natural disease
Selection bias
Confounding bias
Information/Methods bias
Randomized clinical trials
Completely randomized design
Completely randomized block design
Crossover design
Experimental units and independence
Things to look for when reading published study results
Learning to apply course material (to improve thinking, problem solving, and decisions)
This relates to the story problems and scenarios we have in homework and on the exams. They
are intended to help you get used to applying information to real life situations in population
disease.
Lecture 1
1/11/17
Introduction
History of epidemiology
Why do we use epidemiology?
How do we use epidemiology?
Course objectives – Understand:
Cause vs. association – the importance of biological understanding
Quantifying disease
Tests for disease – test characteristics and use
Study designs and analysis – advantages and disadvantages
Critical reading of scientific publications regarding disease in populations
Responsibilities of instructor, students
Honor policy
Contact information
Course grades
Attendance and Absences
Background of Dr. Wilson, including how got into epidemiology
The “bathtub“ graph
Cause vs. association begins
The Medieval King
Lecture 2
1/13/17
Cause vs. Association
Cause vs. association continued
Risk factors vs. causes vs. associations
Drowning and life vests example
Quantifying disease occurrence and disease risk begins
Exposed, Non-exposed, Diseased, Non-Diseased 2 x 2 tables
Relative risk
Stratified analysis – multiple 2 x 2 tables
Interpretation of Relative Risk
Lecture 3
1/18/17
Quantifying Disease Occurrence and Disease Risk
Odds Ratio
Interpreting Relative Risk and Odds Ratio
Limitations of Cohort and Case-Control Studies
Statistical Significance of Relative Risk and Odds Ratio - CI’s
Interpreting 95% CI’s
Population Attributable Risk %
Lecture 4
1/20/17
Tests for Disease
Screening vs. diagnostic tests
Reliability - % agreement, Kappa statistic/Kappa value
Precision and Accuracy
Lecture 5
1/25/17
Tests for Disease 2
Sensitivity
Specificity
Test threshold/cutpoint
Positive Predictive Value (Predictive Value of a Positive Test)
Negative Predictive Value (Predictive Value of a Negative Test)
Effect of prevalence on predictive values
Lecture 6
1/27/17
Disease Surveillance in Populations/Herds
Testing in populations/herds
Sampling a portion of populations – why?
Sampling to detect the presence or absence of disease
Sampling to estimate the prevalence/proportion of disease
Imperfect sensitivity and specificity - effect on determining status of the group
Herd Sensitivity
Herd Specificity
Testing herds/flocks/groups of unknown status
Lecture 7
2/2/17
Measures of Disease Occurrence
Prevalence
Incidence (a rate)
Case definition
P=IxD
Cumulative Incidence
Morbidity
Mortality
Estimating incidence from prevalence
Lecture 8
2/3/17
Dynamics of Infectious Disease
Basic reproductive number
Herd/group immunity
Herd/group resistance
Influence of individuals
Isolation/quarantine
Basic reproductive number between herds/groups
Lecture 9
2/8/17
Types of Disease, Transmission and Terminology
Tularemia - example disease
Reservoir
Transmission routes examples
Latent period
Incubation period
Communicable period
Levels of infection
Endemic vs. epidemic disease
Infectious, communicable and zoonotic
Transmission routes - all
Lecture 10
2/10/17
Outbreaks of Disease
Is it really an outbreak?
Case definition
Investigations
Statistically significant? (How important?)
Analysis of data
Development of a plan to stop the outbreak
Exam 1
2/15/17
(Extra time accommodation begins at 8:10 a.m. Others may come at 8:50 a.m.,
no later than 9:10 a.m., test is designed to take less than 50 minutes, ends at 10 a.m.)
Lecture 11
2/17/17
Monitoring Disease Over Time
Monitoring and records
Facilitating compliance with record keeping
Example cases
Lecture 12
2/22/17
Monitoring Disease Over Time (2)
Example cases
Critical control points
Calculating vaccine efficacy
Biosecurity
Eradicable disease – characteristics
Lecture 13
2/24/17
Disease Eradication Examples
FMD vs. Rinderpest
Lecture 14
3/1/17
Disease Eradication Examples (2)
Rinderpest
Scrapie
Lecture 15
3/3/17
Herd Health Examples (Justine Britten)
Dairy herd mastitis/milk quality
3/7/17
Epidemiology/Public Health Disaster Exercise 10:10 a.m. - 1:00 p.m.,
including lunch provided from 12 - 1 for “hot wash” discussion
Lecture 16
3/8/17
Study Designs (Dr. Bernhardt)
Descriptive Studies
Spring Break 3/13 - 3/17/17
Lecture 17
3/22/17
Study Designs (2) (Dr. Bernhardt)
Descriptive Studies 2
Exam 2
3/24/17
(Extra time accommodation begins at 8:10 a.m. Others may come at 8:50 a.m.,
no later than 9:10 a.m., test is designed to take less than 50 minutes, ends at 10 a.m.)
Lecture 18
3/29/17
Experimental Studies
Hierarchy
Experimentally induced vs. experimental study of natural disease
Selection bias, Confounding bias, Information/Methods bias
Randomized clinical trials
Lecture 19
3/31/17
Experimental Study Design
Experimental study designs - Completely randomized design (CRD), Completely
randomized block design (CRBD)
Crossover design
Experimental units and independence
Case definition
Choosing the experimental unit and analysis
Lecture 20
4/5/17
Experimental Study Design 2/Critical Journal Reading
“Filling blocks”
Some practical considerations in large and small animal studies
Power and sample size calculation
Direct sample size calculation
“What if” sample size calculation
Things to look for when reading published study results
Lecture 21
4/7/17
Dairy Practice Epidemiology (Dr. Stott)
Lecture 22
4/12/17
Poultry Practice Epidemiology (Dr. Frame)
Lecture 23
4/14/17
Molecular Epidemiology (Dr. Bernhardt)
Lecture 24
4/19/17
Critical Journal Reading (Dr. Bernhardt)
Lecture 25
4/21/17
Shelter Medicine Epidemiology (Dr. Echols)
Lecture 26
4/26/17
Beef/Small Ruminant Practice Epidemiology (Dr. Dent)
Lecture 27
4/28/17
Mink Practice Epidemiology (Dr. Lott)
Integrity is the cornerstone of the university and the veterinary profession. Collaboration with
classmates is encouraged. However, your work on examinations or in-class quizzes must be
your own. Refer to the WSU/CVM Academic Standards policy here:
http://courses.vetmed.wsu.edu/policies/; Policies and Procedures for Students at Utah State
University: http://www.usu.edu/studentservices/studentcode/.
In epidemiology class, it will be necessary, particularly for the examinations, to have a calculator
that performs addition, subtraction, multiplication, and division. It cannot be on a phone.
Homework must be turned in on time to receive credit, and must be submitted through Canvas.
Homework must be submitted as a typed Word document; the only exception to typing is when
filling numbers into tables. Each homework assignment will have two deadlines. Submission by
the first deadline is strongly encouraged; this is the deadline to receive feedback regarding any
incorrect answers, and to resubmit the homework (hopefully with all answers correct). The
second deadline is to submit homework with no further feedback. Homework submitted after the
first deadline but by the second deadline will be graded as it is. (The vast majority of all
homework final submissions in the past have received credit for all 10 points, but many of those
have needed some feedback to be entirely correct.)