VET10170 Introduction to veterinary epidemiology

Academic Year 2020/2021

This module introduces three core elements: Epidemiology, Biostatistics and Evidenced-based Veterinary Medicine. First, it introduces the fundamentals of epidemiology (approximately 11 lectures). Epidemiology relates to the study of the distribution and determinants of outcomes in populations. As it pertains to veterinary medicine, it is most often used as a tool to study the distribution of the determinants of animal diseases. Second, given the important role of biostatistics in population sciences, its increasing prevalence in veterinary practice and its centrality to the execution and interpretation of veterinary epidemiologic research, the module also introduces bio-statistical content (approximately 5 lectures) that the graduating veterinarian should be familiar with. Finally, it introduces aspects of evidence-based veterinary medicine(approximately 6 lectures). Evidence-based veterinary medicine has been defined as the conscientious, explicit and judicious use of current best evidence in making decisions about the care of animals. In large part, this evidence is drawn from a critical understanding of the published scientific literature. Students need a sound understanding of these related subjects, as they are relevant to both veterinary clinical medicine and veterinary research.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module, students should be able to:

• Articulate the epidemiologic approach to the study of diseases and state its underlying assumptions about the occurrence of outcomes in the natural world.

• List, recognise and interpret the fundamental measures of disease frequency used in epidemiology and understand the centrality of denominators to epidemiologic inference.

• Distinguish between different measurement scales, categorical and continuous variables. Recognize the most common statistical tests used to compare categorical and and continuous variables.

• Explain what is meant by the term “risk factor” and interpret the most commonly used measures of effect in epidemiology. Explain why effect estimation is preferable to a simple determination of association.

• Interpret p-values and confidence intervals and explain why the latter provides more information to the reader than the former. Construct confidence intervals for basic epidemiologic measures.

• Understand the major issues in the application of diagnostic tests to veterinary medicine. They should be familiar with factors that affect sensitivity and specificity, why predictive values are more helpful in decision making than sensitivity and specificity, use a nomogram to make a clinical decision based in part, on the results of a diagnostic test and critically appraise literature validating a diagnostic test.

• Recognize the major epidemiologic study designs in the literature. Students should be able to describe their strengths and weaknesses and state which epidemiologic measures of effect can be estimated using each design.

• Define the major types of bias that occur in epidemiologic studies.

• How to critique articles in the scientific literature. Know how to determine which study-design flaws have greatest consequences to validity.

• Estimate and interpret vaccine efficacy. Understand the relationship between an infectious disease’s basic reproductive number, immunization and disease eradication.

Student Effort Hours: 
Student Effort Type Hours
Lectures

24

Laboratories

6

Specified Learning Activities

16

Autonomous Student Learning

66

Total

112

Approaches to Teaching and Learning:
Interactive lectures in which students are asked and encouraged to ask questions
Laboratory/Discussion classes in which students gain practice in computing epidemiologic measures.
Five short 10 minute tests 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Class Test: Continuous assessment Throughout the Trimester n/a Alternative non-linear conversion grade scale 50% No

20

Examination: Midterm Examination Week 7 No Alternative non-linear conversion grade scale 50% No

20

Examination: End of semester exam 2 hour End of Trimester Exam No Alternative non-linear conversion grade scale 50% No

60


Carry forward of passed components
No
 
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Self-assessment activities

How will my Feedback be Delivered?

Weekly (prior to assessments) • One hour is set aside for students to meet personally and privately with the instructor to get feedback on their progress and performance in the module. • During each lab/discussion class, oral feedback is provided both individually to students as well as to the whole class while in class assignments are being done. After formative assessments • After each class test is graded and results communicated, solutions will be made available to all students online. Questions that have been particularly problematic or poorly done by a high percentage of the class will be discussed during the subsequent class lecture. The same procedure will be followed for the midterm. End of semester prior to summative assessment • At the end of the semester, questions for practice are provided along with solutions. During the reading week, the instructor is available for consultation and students are encouraged to contact the instructor via e-mail with their answers. Feedback is provided in response. On occasion this feedback is made available to the whole class when it is deemed that it will be helpful to all. On these occasions all personal identifiers are removed so that the identity of the initial questioner is not revealed to the class.

Introduction to Veterinary Epidemiology by Dirk Pfeiffer. Electronic version available online (https://www.researchgate.net/publication/305279557_Introduction_to_Veterinary_Epidemiology) and within Bright Space
Name Role
Mr Maurice Kinsella Tutor