Epidemiology, Preventive Medicine and Health Policy I

Interest of the subject in Veterinary profession
This subject is included in the Module of Clinical Sciences and Animal Health. The interest of this subject in the degree is associated to the increasing importance of the Epidemiology in a professional point of view. Because of the European legislation, very restrictive on the use of drugs in animals, no only for illness treatment, but also and especially avoiding the use of antibiotic growth promoters, the Veterinary Medicine has to evolve to the Preventive Medicine, that's to say, the presence of a professional no only Veterinary Clinical, but also with epidemiological knowledge. Of face to the future of the profession, the percentage of veterinary specialised in Epidemiology will increase necessarily, as free professionals, hired by cooperatives or companies and in the future, in the Public Administration, to control illnesses of economic importance (outbreaks that suppose problems to export to other countries or that support a massive animal sacrifice) or with zoonotic impact (for example, the control of the bird flu). For his control, the most suitable people are those that have received a epidemiological training.
Another very important point is the animal welfare. At this point is very important a deep knowledge of the Epidemiology and the Preventive Medicine, to make possible a profitable exploitation, but that cover also animal comfort inside the production.

Aims of the subject
- Understand the populational concept, base in the epidemiological studies, and its extension in the space and time, to be able to generate sanitary programs allocated to the Preventive Medicine.
- Know the indicators of health and his statistical assessment, as well as the determinants of illness asi risk factors in the populations.
- Know and understand which mechanisms participate in the transmission and maintenance of the illness in a population.
- Know the sources of accessible data to veterinarians to obtain information, as well as the methodology to realise observational studies in different environmental situations. Besides, it will have to acquire the precise skills for, no only obtain, but also encode, store and analyse all the information.
- Know and comprise the contribution of the epidemiology in front of the illnesses and its possibilities of modelling and prevention, as well as its contribution to the public health.
- Acquire a suitable terminology of the subject
- Learn to design sanitary and productive control programs to get profitable farming.

This program covers three thematic sections, interactive sessions, clinical practices and one tutoring hour.
SECTION 1: Introduction and historical perspective. Basics concepts. Populations. Determinants of disease. Transmission and maintenance of the disease. Forms of the disease. Health programs and productive. Biosafety ymonitorización. Probability.
Unit 1. Historical development and future prospects. Objectives and definition of Epidemiology and Preventive Medicine. Application of epidemiology to management programs Animal Health and Production. Hours: 1 h.
Unit 2. Population concept. Causality. Concept of cause. Koch's, Hill and Evans postulates. Causal models. Necessary and sufficient causes. Determinants. Epidemiological triad. Types of disease presentation. Transmission methods. Hours: 4 h.
Unit 3. Elements and design of health programs and productive. Biosafety. Health actions. Monitoring and tracking productivity. Productivity suboptimal and causes. Hours: 3 h.
Item 4. Probability. Randomness. Probability calculation. Hours Lectures: 2 hr.

SECTION 2. Sampling. Diagnosis. Epidemiological measures. Sources, types and their production data.
Unit 5. Sampling. Sampling methods. Non-probability sampling and probabilistic. Determination of sample size. Hours: 2 hours.
Unit 6. Types of epidemiological measures: ratios, proportions and rates. Measurement of disease frequency: prevalence and incidence. Morbidity, mortality, lethality and attack. Standardization of rates. Hours: 2 hours.
Unit 7. Diagnosis. Validation of a diagnostic test. Concordance. Kappa statistic. Sensitivity. Specificity. Predictive values. Relationship with prevalence. Hours Lectures: 3 hours.
Item 8. Design of epidemiological studies. Introduction. Sources of data in epidemiology. Classification criteria. Observational studies: cross, case-control and cohort studies. Experimental studies. Hours: 3 h.
Unit 9. Development of questionnaires. Types of surveys. Variables used. Hours Lectures: 2 hours.

SECTION 3. Analysis and presentation of data.
Unit 10. Descriptive statistics. Introduction. Frequency distribution. Central and dispersion estimators. Confidence intervals. Graphs. Hours: 2 h.
Unit 11. Analytical Statistics. Introduction. Tests to detect differences. Testing for correlations. Tests to detect associations. Hours: 2 h.
Unit 12. Statistical Epidemiology. Measures of association and impact. Introduction. Estimates of risk: relative and attributable risk, etiologic fraction, odds ratio. Hours: 1 hours.
Unit 13. Confounding and interaction concept. Techniques for control of confounding. Hours: 1 hr.

Interactive and clinic sessions
Epidem. OR1 - 4 hours (Computer class).
In this session it will be explained the reasons that make the computer a fundamental tool in many of the sciences in the degree of Veterinary, and in particular, in Epidemiology and Preventive Medicine.
Then, students will receive in the platform a data file in ods format. They will use a GPL Calc and / or Gnumeric spreadsheet and the way to enter the data will be shown so that it can be entered in R. They will also learn how to make graphs and the use of formulas in spreadsheets. The software used is GPL, so that students can install it on their personal computers and repeat and improve its use autonomously.
These data will be converted to be introduced in the R statistical package (also free software, with the same purpose as the previous ones)

Epidem. C2 - 4 h (Computer class).
The most important complication of this session is that most of the students are not used to work on the terminal and writing commands to carry out the routines on their computers and they need to learn not to make mistakes in the syntax of the R language. That is why we use at first R and then RStudio, where the command editor makes it easier to use. In this session, students will learn to manage production and health data from farms and analyze them on the computers. These data will be entered into the statistical system and students will learn the concepts of object, function, command and data management in R. Initially, data management and descriptive statistics will be discussed, as well as the creation of graphs. Then we will begin the statistical analysis, with examples for the calculation representative sample size, sensitivity, specificity and the Kappa statistic. Then, a test will be carried out that will be delivered in the USC virtual platform to be evaluated (value 20 points).

Epidem. C3 - 4 h (Computer class).
In this second clínical session the fundamental commands for the realization of analytical statistics in R and RStudio will be applied.
Difference tests: Student's t and Anova
Association tests: Chi square
Relationship tests: correlation and regression

Epidem. OR2. 4 h (computer classroom).
Students will be given a full set of real data with which they will have to solve a situation, determining the necessary sample size, and sensitivity and specificity of the diagnostic tests used, and then present a report with possible solutions to be evaluated (60 points), as part of continuous assessment.

Attendance at interactive sessions and clinical practices is mandatory. Students who do not attend practices may not pass the subject in that academic year.

TUTORIALS (1 h.)
Students will have one hour of tutorials to explain the two tasks related to the topics of the teachers will be risen to be performed in Epidem. C3 and Epidem. OR2. The main part of these tutorials would be to revolve doubts in tasks before performed and then delivered to the virtual platform.

BERTHOLD, M.R.; BORGELT, C.; HÖPPNER, F.; KLAWONN, F. (2010). Guide to Intelligent Data Analysis. Springer-Verlag London Limited.
CONTRERAS, A; SÁNCHEZ, A.; CORRALES, J.C. (2001). Epidemiología veterinaria. Univ. Murcia.
DOHOO, I.; MARTIN; W., STRYHN, H. (2009). Veterinary Epidemiologic Research. Segunda edición. VER Inc., Charlottetown, Canada.
DURR, P.; GATRELL, A. (2004). GIS and spatial analysis in veterinary science.CAB International, Wallingford, Oxfordshire, UK.
GORDIS, L. (2005). Epidemiología. Tercera edición. Elsevier España, Madrid.
GREENBERG, R.S. y col. (1998). Epidemiología médica. Manual Moderno, México D.F.
HOUE, H. (2004). Introduction to Veterinary Epidemiology. BIOFOLIA.
LAST, JM. (1989). Diccionario de Epidemiología. Salvat Editores, S.A. Barcelona.
MACHIN, D., CAMPBELL, MJ., TAN, BT., TAN, SH. (2018). John Wiley & Sons Ltd, Oxford, OX4 2DQ, UK.
MORTON, E.R.; HEBEL, J.R.; McCARTER, R.J. (1993). Bioestadística y epidemiología. 2ª edición. McGraw-Hill, México, D.F.
ORTEGA, C. y col. (1995). Manual de Epidemiología aplicada para el veterinario clínico. Esteve Veterinaria, Barcelona.
PETRIE, A.; WATSON, P. (1999). Statistics for veterinary and animal science. Blackwell Science, Ltd., Oxford.
PFEIFFER, D.U. (2010). Veterinary Epidemiology. An Introduction. Wiley-Blackwell.
PFEIFFER, D.U. (2008). Spatial Analysis in Epidemiology. Oxford University Press
ROTHMAN, K.J. (2012). Epidemiology. An introduction. Second edition. Oxford University Press, New York.
ROTHMAN, K.J., GREENLAND, S.; LASH, T.L. (2008). Modern Epidemiology. Third edition. Lippincott Williams & Wilkins, Philadelphia, USA.
STUART, A. (2002). Ideas básicas de muestreo científico. Editorial A.C., Madrid.
THRUSFIELD, M. (2005). Veterinary Epidemiology. Third Edition. Blackwell Scientific Publications Ltd., Oxford.
VERZANI, J. (2011). Getting Started with RStudio. O'Reilly.

Web pages
http://aeema.vet-alfort.fr/
http://ccp.ucr.ac.cr/cursos/epidistancia/contenido/4_epidemiologia.htm
http://www.answers.com/topic/epidemiology
http://www.aphis.usda.gov/about_aphis/programs_offices/veterinary_servi…
http://www.bettycjung.net/Bite.htm
http://www.epidemio.com/epidemio.html
http://www.fao.org
http://www.woah.org/es/inicio
http://www.quadernodiepidemiologia.it/epi/HomePage.html

Recommended references (R statistical package)
http://cran.r-project.org/doc/contrib/Owen-TheRGuide.pdf
http://cran.r-project.org/doc/contrib/Paradis-rdebuts_en.pdf
http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf
http://cran.r-project.org/
http://cran.r-project.org/faqs.html
http://cran.r-project.org/doc/manuals/R-intro.pdf
http://cran.r-project.org/doc/manuals/R-data.pdf
http://cran.r-project.org/doc/manuals/R-admin.pdf
http://cran.r-project.org/doc/contrib/rdebuts_es.pdf

General Competencies
GVUSC01. Ability to learn and adapt.
GVUSC02. Capability for analysis and synthesis.
GVUSC03. General knowledge of the working area.
GVUSC04. Planning and work management.
GVUSC05. Capability to put knowledge into practice.

Specific Competencies
Disciplinary specific competencies (knowledge)
CEDVUSC 08. Knowledge and diagnosis of the various animal diseases, both individual and collective, and its prevention measures with special emphasis on zoonoses and notifiable diseases.

Specific Professional Competencies (expertise)
D1VUSC 05. Perform epidemiological studies and develop prevention, control and eradication programs on animal diseases, with a focus on compulsory notifiable diseases and zoonoses.
D1VUSC 11. Evaluate and interpret health and production parameters of an animal group, considering the economic, environmental and welfare aspects, and seeking their optimization.
D1VUSC 14. Conduct a risk assessment, including those related to environmental and biosafety, as well as assessment, management and monitoring of quality management systems.

Specific Academic Competencies (want to do)
CEAVUSC 01. Analyze, synthesize and solve problems and make decisions within the scope of the Veterinary profession.
CEAVUSC 04. Search and manage information related to veterinary practice.
CEAVUSC 08. Being aware of the need to keep professional skills and knowledge up-to-date through a process of lifelong learning.

Transversal competences
CTVUSC 01. Capacity for reasoning and argument.
CTVUSC 02. Ability to obtain adequate, diverse and updated information by various means such as literature and Internet information, and critically analyze it.
CTVUSC 03. Ability to develop and present an organized and understandable text.
CTVUSC 05. Skill in the use of ICTs.
CTVUSC 07. Ability to solve problems through the Integration and application of knowledge.

Theory lectures
Theory lectures will be expository and mandatory. It will last about 50 minutes. Theoretical material will be given prior to the exposure class through multimedia systems to introduce problems and questions to bring the students' attention on real cases that happen in everyday life on the farm. When approaching the end of a block, tests during approximately 30 minutes will be done. Class dispensation is not applicable.

Interactive sessions and clínical practises
Interactive sessions are held in the computer rooms in groups of 20 students. They will learn to manage the data and make graphs in spreadsheets, then introduced the data in R, where they will learn the basic commands for graphics, descriptive values and statistical tests. Interactive session dispensation is not applicable.

Clinical practises will be held in groups of 10 students; They will learn to extract, manage and analyze real data from farms to take decisions about animals and their diseases. Clinical practise dispensation is not applicable.

Tutorial classes
The tutorial classes would enable us to present the tasks for the students and then to correct any errors that may appear in implementation.

There will be evaluated all through the semester. Throughout the unit presentations four small tests will be done. These controls have the function to monitor attendance and assess their knowledge development. There will be around five short questions to seek possible solutions to possible situations associated with the topics covered. Total value for random tests - 20 points (4x5).
In the platform students will receive two tasks, similar to those that would be evaluated in the Epidem. C2 practice and Epidem. OR2. To perform these tasks students will receive a set of data related to a disease or disorder of an animal population from which students will have to find causation, identify which factors are influencing, statistically prove and report recommendations adequate to solve the problem. They we be delivered through the virtual platform (The value will be 20 + 60 points. Total tasks - 80 points).
Students over 50 points would have passed the subject under continuous evaluation and they do not need to attend the theory exam.
Students who have failed to pass the subject may perform another task at the end of the course to recover the parts that they could not have passed over the continuous evaluation. In case of fraudulent performance of exercises or tests, there will be applied the provisions included in “Regulations for the evaluation of the academic performance of students and the review of qualifications”.

Final qualification of the student
Students will be under continuous assessment (100%). The final exams will make it possible to recover the parts not passed through continuous evaluation. Dispensation is not applicable.

Hours:
Theory: 28 h.
Interactive sessions: 8 h.
Clinical practices: 8 h.
Tutorials: 1 hours.
Total in presence hours: 45 h.

Non-present hours:
Individual study: 37.5 h.
Task Development: 20 h.
Literature review: 2 hr.
Attendance at lectures or other recommended activities: 1 h.
Problem practice: 5 hours.
Exam (if necessary): 2 hr.
Total hours of personal work: 67.5 h.

Total hours for the student: 112.5 h.

There are really important concepts that must be taken into account when preparing the material, and also will be useful in other subjects. The possibility to do practices at home can be very useful, and also helps students to learn about computer and network, essential tools for Epidemiology. These sessions are posted on the virtual platform all through the course, including all materials (guides, data files and graphs) and can be used on any computer connected to the network, downloaded etc ...
From the point of view of the realization of the tasks, it is recommended that students not to be restrained in their comments, which may be of greater value than the resolution of a simple statistical analysis. It is important to use the knowledge they have and the common sense to evaluate the results obtained in the different tests.

It is advisable to have a basic knowledge of mathematics (secondary education prior to entry into the University) and also understand the basics of statistics, students have taken at the start of the degree. Computer knowledge can also be very useful, and more specifically on spreadsheets such as Excel or Calc (manner of operation, formulas ...) and some basic concepts about the functioning of statistical programs such as SPSS ®, or any other type of commercial statistical program (Systat ®, Statgraphics ® ...) or freee and/or open source, (OpenStat, R, MacAnova ...).
Some basic knowledge of English also favor the development of this field, since much of the literature does not have Spanish translation.