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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.)