Any acadèmic

Logo UAB

One Health: Introduction, Health Policy and Epidemiological & Statistical Methods

Code: 43755 ECTS Credits: 12
2025/2026
Degree Type Year
Zoonoses and One Health OB 0

Contact

Name:
Alberto Allepuz Palau
Email:
alberto.allepuz@uab.cat

Teachers

Alberto Allepuz Palau

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

As a requirement for admission you must be in possession of any of the titles listed below:

Graduates, Graduates or Diploma in the field of Health Sciences (Veterinary Medicine, Nursing, Pharmacy, Food Science and Technology, Animal Science and Health, Biomedicine, Psychology ...) and Life Sciences (Biology, Biochemistry, Biotechnology , Zoology, Botany, Ecology, Biodiversity, Environmental Sciences, Agronomic Engineering, Forestry ...) or equivalent.


Objectives and Contextualisation

Definitions, objectives and critical knowledge of the multidisciplinary nature of the One Health concept will be provided as a strategy for solving problems, focusing on the control of health with respect to people, domestic and wild animals and in the related ecosystem.

The official bodies and institutions involved, their functions, competences and interactions will be detailed. The risk analysis defined in the SPS agreement is a sequential process comprised by Risk Assessment, Management and Communication that must be transparently exposed and available to all public institutions and governments or private organizations. For this reason, each institution at the regional, national, community or international level has an assigned body (s) and entities responsible for risk analysis, which will be shown throughout the module.

Taking into account the need to establish an adequate risk assessment, a series of useful theoretical and technical knowledge will be provided to identify risk and make decisions. In this module you will learn basic notions of epidemiology, statistical and mathematical models and their application to epidemiological studies and risk assessment.


Competences

  • Act in accordance with the code of ethics of the profession.
  • Display understanding and familiarity with using the methodologies and tools of zoonotic risk assessment based on the concept of One Health.
  • Solve problems in new or little-known situations within broader (or multidisciplinary) contexts related to the field of study.
  • Take decisions on the establishment of zoonosis surveillance and containment plans.
  • Use acquired knowledge as a basis for originality in the application of ideas, often in a research context.
  • Work alone or in a multidisciplinary team within the area of study, showing critical reasoning and creativity, and the ability to analyse, interpret and synthesise the data generated.

Learning Outcomes

  1. Find information on zoonoses in all areas of health, through the resources available online.
  2. Know and recognise the limitations of risk assessment and determine the areas of uncertainty.
  3. Know the bodies and institutions involved in the evaluation, management and communication of risk.
  4. Know the current legislation with regard to One Health.
  5. Know the importance of multidisciplinary work in tackling diseases from the perspective of One Health.
  6. Know the multidisciplinary concept of One Health and its applications.
  7. Know the principal actors in risk management at all levels of intervention.
  8. Know the profession and the political, economic, social and cultural contexts in which it will be practised.
  9. Learn to work alone or in a team, effectively and multidisciplinarily, on all the components of human, animal and environmental health.
  10. Use epidemiological and statistical tools and methodologies: both basic and applied to the surveillance and containment of zoonoses from the multidisciplinary perspective of One Health.

Content

- Introduction to the One Health Concept

- Official bodies: organization chart and risk assessment, management and communication functions

- Epidemiology and surveillance

- Basic and advanced Statistics

 


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Classes of problem solving, cases and exercises 34 1.36 9, 7, 2, 8, 1, 10
Debates 6 0.24 6, 7, 2, 5, 4
Master classes / Exhibition classes 13 0.52 9, 6, 3, 7, 2, 5, 4, 8, 1, 10
Problem-based learning 25 1 9, 3, 2, 5, 8, 1, 10
Type: Supervised      
Resolution of cases, exercises and problems in a virtual way 35 1.4 9, 6, 3, 7, 2, 5, 4, 8, 1, 10
Tutorials 15 0.6 9, 6, 3, 7, 2, 5, 4, 8, 1, 10
Type: Autonomous      
Personal study 85 3.4 9, 6, 3, 7, 2, 5, 4, 8, 1, 10
Reading articles and reports of interest 45 1.8 6, 3, 7, 2, 5, 8, 1
Realization of works / reports 42 1.68 9, 6, 3, 7, 2, 5, 4, 8, 1, 10

Directed activity:

         Master classes / Exhibition classes

         Problem-based learning

         Debates

         Problem solving classes / cases / exercises

Supervised activity:

         Tutorials

          Resolution of cases, exercises and problems 

Autonomous activity:

          Realization of works / reports

          Reading articles / reports of interest

          Personal study

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Delivery of reports / works 40 0 0 9, 6, 3, 7, 2, 5, 4, 8, 1, 10
Oral presentations of works 60 0 0 9, 6, 3, 7, 2, 5, 4, 8, 1, 10

A. The assessment of the students will be done through a combination of the following criteria:

  - It is mandatory to attend at least 80% of the presential classes. Attendance to lectures and participation in the activities carried out individually or in groups during those sessions will be recorded. Non justified absences for a given activity are not accepted. In case of a justified absence (illness, work issues, etc.) the qualification of this activity will be considered but restrictions may apply.

 

-  In the teamwork and oral presentations, the assessment will take into account the quality and clarity of the presentation and the knowledge demonstrated during the discussion of the subject.

 

B. To pass this module, compulsory attendance is required at a minimum of 80% of the on-site class hours of the module. The final average grade of the module must be equal to or greater than 5 out of 10.

 

C. In the case of failing, the students will have an additional opportunity consisting in a complementary work in which they must obtain at least 5 out of 10 points.

 

 - Oral presentations (60%):

Oral presentation on the role of official bodies (20%)
Oral presentation on descriptive epidemiology (40%)

 - Written works (40%):

Descriptive statistics (20%)
Simple and logistic regression (20%)

 

Students who do not appear for any assignment will be "non-evaluable"


Bibliography

- Introducción a Una Sola Salud (One Health concept)

The evolution of One Health: a decade of progress and challenges for the future. Downloaded from veterinaryrecord.bmj.com on September 29, 2014 - Published by group.bmj.com:

https://www.onehealthcommission.org/documents/news/Gibbs_The_evolution_of_One_Health_BBE95DE2EA279.pdf

http://www.onehealthinitiative.com/about.php

http://www.fao.org/ag/againfo/home/en/news_archive/2010_one-health.html

-Organismos oficiales: organigrama y funciones de evaluación, gestión y comunicación de riesgos (Official Institutions and their role in Risk Management and Communication).

* United Nations

WTO- SPS agreement. Impact on Public Health Food safety, Animal & Plant Health  https://www.wto.org/english/tratop_e/sps_e/spsagr_e.htm

WHO.  Areas of work in food safety and zoonosis: http://www.who.int/foodsafety/areas_work/en/

FAO.  Contributing to One World , One Health http://www.fao.org/docrep/011/aj137e/aj137e00.htm

CODEX ALIMENTARIUS. Public Health, Food safety, Animal and Plant Health.

http://www.fao.org/fao-who-codexalimentarius/codex-home/en/

* World Animal Health  (OIE). http://www.oie.int/en/ . The concept of One health.

http://www.oie.int/en/for-the-media/onehealth/

* European Union.

Overview of EU activities Public Health, Animal & Plant Health and Food safety:  http://ec.europa.eu/health/index_en.htm

General Food law (Food , Feed , Animal & Plant legislation): http://ec.europa.eu/food/safety/general_food_law/index_en.htm

EFSA: http://www.efsa.europa.eu

ECDC:   http://ecdc.europa.eu/en/Pages/home.aspx

ECDC-EFSA Rapid risk assesssments: http://ecdc.europa.eu/en/publications/risk_assessment/Pages/default.aspx

EMA:  http://www.ema.europa.eu/ema/

Antimicrobial resistance: http://www.ema.europa.eu/ema/index.jsp?curl=pages/special_topics/general/general_content_000439.jsp

 Maximum residues levels MRL: http://www.ema.europa.eu/ema/index.jsp?curl=pages/regulation/document_listing/document_listing_000165.jsp&mid=WC0b01ac058002d89b

European National Agencies:

http://www.bfr.bund.de/cm/364/eu-food-safety-almanac.pdf

* United States:

FDA.   Home page http://www.fda.gov    FDA organigram http://www.fda.gov/AboutFDA/CentersOffices/OrganizationCharts/ucm393155.htm

Center for Food Safety and Applied Nutrition http://www.fda.gov/AboutFDA/CentersOffices/OfficeofFoods/CFSAN/default.htm

Center for Veterinary Medicine http://www.fda.gov/AboutFDA/CentersOffices/OfficeofFoods/CVM/default.htm

Opinion article from FDA about One health: http://www.fda.gov/animalveterinary/resourcesforyou/animalhealthliteracy/ucm278139.htm

Centre of Disease Control (CDC): http://www.cdc.gov/foodborneburden/PDFs/CDC-and-Food-Safety.pdf\

Office of Regulatory Affairs: http://www.fda.gov/AboutFDA/CentersOffices/OfficeofGlobalRegulatoryOperationsandPolicy/ORA/default.htm

USDA (United States Department of Agriculture)  APHIS One health concept :

http://www.usda.gov/wps/portal/usda/usdahome?navid=onehealth

https://www.aphis.usda.gov/aphis/ourfocus/animalhealth/SA_One_Health

EPA Environmental Protection Agency   Activities in Public Health , animal Health and Plant health:

https://www.epa.gov/aboutepa

* Otros:

Transatlantic Taskforce on Antimicrobial Resistance – TATFAR -

http://ecdc.europa.eu/en/activities/diseaseprogrammes/TATFAR/Pages/index.aspx

http://www.cdc.gov/drugresistance/tatfar/index.html

J. Serratosa, Oriol Ribo 2009 International context and impact of EFSA activities in animal welfare in the European Union. 2009 Elsevier  (Book- 275-303 pp)  Welfare of animal production : assessment and management of risks. 

 - Epidemiología y análisis de riesgo

Dohoo I., Martin W., Stryhn H. (2009) Veterinary Epidemiologic Research - 2nd Edition.

Dirk U. Pfeiffer, Timothy P. Robinson, Mark Stevenson, Kim B. Stevens, David J. Rogers, and Archie C.A. Clements. (2008). Spatial Analysis in Epidemiology.

Thrusfield, M. (2005) Veterinary Epidemiology. (3ª ed.) Ed. Blackwell Science. Oxford.

OIE (2004) Handbook on Import Risk Analysis for Animals and Animal Products, vol. 2. World Organization for Animal Health (Office International des Epizooties), Paris, France.

R. Bonita, R. Beaglehole, T. Kjellström. Basic epidemiology. 2nd edition. World Health Organization.

- Modelización estadística

David Collett. Modelling Survival Data in Medical Research. 2nd edition. Chapman& Hall.

Hosmer, DW, Lemeshow S. Applied logistic regression. New York. John Wiley & Sons. 2000.

Katz MH. Multivariable Analysis: A Practical Guide for Clinicians. Cambridge University Press, 2006.

Kleinbaum, David G., Klein, Mitchel. Survival Analysis. A Self-Learning Text, Third Edition. Springer.

Lawson A.  (2013). Bayesian disease mapping.

Rawlings JO, Pantula SG, Dickey DA. Applied Regression analysis. A research Tool. Second Edition. Springer

Saez M, Saurina C. (2007). Estadística y Epidemiología Espacial. Girona: Documenta universitaria.


Software

QGIS (https://qgis.org/ca/site/)

R (https://www.r-project.org/9

 Use of AI: In thismodule, the use of Artificial Intelligence (AI) technologies is allowed as an integral part of the development of the work, provided that the final result reflects a significant contribution of the student in the analysis and personal reflection. The student must clearly identify which parts have been generated with this technology, specify the tools used and include a critical reflection on how these have influenced the process and the final result of the activity. The lack of transparency in the use of AI will be considered a lack of academic honesty and may lead to a penalty in the grade of the activity, or greater sanctions in serious cases.


Groups and Languages

Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.

Name Group Language Semester Turn
(PAULm) Classroom practices (master) 1 English first semester morning-mixed
(TEm) Theory (master) 2 English first semester morning-mixed