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Medical Microbiology

Code: 42935
Credits: 6
2026/2027
Degree programme Type Course
Applied Microbiology OB 1

Contact lecturer

Name :
Carles Alonso i Tarrés
Email :
carles.alonso@uab.cat

Group languages

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

Prerequisites

It is absolutely necessary to have a basic previous knowledge about microorganisms capable of causing human disease: habitat, transmission forms, type of infections caused and identification.

Objectives

Objectives:

a) to acquire abilities to apply own scientific knowledge to the clinical application of Microbiology

b) to begin learning the methods of clinical reasoning in order to adapt to the healthcare setting and to the field of laboratories that supply equipment and reagents

Learning outcomes

  1. Solve problems in new or little-known situations within broader (or multidisciplinary) contexts related to the field of study.
  2. Use and manage bibliographic information and computer resources related to microbiology and related sciences.
  3. Continue the learning process, to a large extent autonomously.
  4. Design and apply scientific methodology in problem solving.
  5. Develop critical reasoning within the subject area and in relation to the scientific or business context.
  6. Integrate knowledge and use it to make judgements in complex situations, with incomplete information, while keeping in mind social and ethical responsibilities.
  7. Know the appropriate methods for processing human samples for microbiological analysis.
  8. Design identification strategies aimed at making a microbiological diagnosis in the field of clinical microbiology.
  9. Design typification strategies aimed at conducting epidemiological studies in the field of clinical microbiology.
  10. Apply appropriate methodologies for conducting studies on sensitivity to antimicrobial agents.
  11. Interpret microbiological findings appropriately in order to take decisions regarding microbial identification, study of resistance to antibiotics and typifications. Write up the reports on the above analyses.
  12. Integrate microbiological findings with clinical data in order to diagnose an infectious human disease microbiologically.

Contents

 -         Introduction to medical reasoning 


-          Collection of specimens, transport and processing techniques


-          Application of microbiological techniques to the clinical laboratory


-          Main infection syndromes: pathogenesis, etiology and diagnosis

Learning activities and methodology

Title Hours ECTS Learning outcomes
Lectures 30 1.2 1, 3, 4, 5, 6, 7, 8, 10, 11, 12
Personal study 72 2.88 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
Written work 12.5 0.5 1, 2, 4, 5, 6, 7, 10, 11, 12
On site exercises 15 0.6 1, 2, 3, 4, 5, 6, 12
Problem based learning 5 0.2 1, 2, 3, 4, 5, 6, 7, 10, 11, 12
Clinical cases discussion 12.5 0.5 1, 3, 5, 6, 8, 9, 10, 11, 12

Learning method includes lecture lessons, clinical cases discussion, problem based learning, and personal study.

Power Point slides and text is given for every lecture. During lessons this material is enriched with real examples, taken from recent or past clinical cases.

In clinical sessions one or several cases are exposed and discussed according to clinical reasoning.

Problem based learning session has the objective to apply previous knowledge learned to solve a real clinical case. The oral presentation of the problem-solving process will be assessed.

For this subject, the use of Artificial Intelligence (AI) technologies is permitted exclusively for support tasks, such as bibliographic or information searches, text correction, or translations. The student must clearly identify which parts have been generated using this technology, specify the tools used, and include a critical reflection on how these have influenced the process and the final outcome of the activity. Lack of transparency in the use of AI in this assessed activity will be considered academic dishonesty and may result in a partial or total penalty in the grade for the activity, or more serious sanctions in severe cases.

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

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Written exam 50 3 0.12 4, 5, 6, 7, 8, 9, 10, 11, 12
Problem based learning 40 0 0 1, 2, 3, 5, 6, 7, 9, 10, 11, 12
Attendance 10 0 0 1, 4, 5, 6, 7, 8, 10, 12

The lectures and seminars will be assessed with a short-answer and multiple-choice exam (50%). It is necessary to pass the exam in order to pass the course

Problem based learning will be evaluated with the compulsary attendance to the corresponding sessions, participation in class and oral exposition (40%).

Attendance to lessons will count 10%. 4 non-justified misses are allowed to get this 10%. From 5 misses on, every miss will discount 1/4 of this 10%.

Final considerations:

To be eligible for the retake process, the student should have been previously evaluated in a set of activities equaling at least two thirds of the final score of the course or module. Thus, the student will be graded as \"No Avaluable\" if the weighth in of all conducted evaluation activities is less than 67% of the final score. The oral presentation cannot be retaken.

Single assessment

Single assessment encompasses:

- Written exam (50%). Necessary to pass the whole subject.

- Problem based learning sessions (two) with oral exposition (50%)



The commission of any irregularity in an assessment activity (academic fraud, plagiarism, or improper use of AI, unless such use is expressly authorized in the course syllabus) that may lead to a significant variation in the grade shall result in that activity being graded with a 0. If the course syllabus stipulates that obtaining a minimum grade in this assessment activity is an essential requirement for passing the course, or if several irregularities occur in the assessment activities of the same course, the final grade for that course shall be 0. In addition to this, disciplinary proceedings may be initiated against any student who commits any of these irregularities.

Bibliography

REFERENCES

BIBLIOGRAFÍA

1)      Manual of Clinical Microbiology. American Society for Microbiology. Jorgensen J et al. 13rd edition. ASM press. WashingtonDC. 2023. 12th edition available online at https://csuc-uab.primo.exlibrisgroup.com/permalink/34CSUC_UAB/avjcib/alma991009924369706709 

2)      Sarah J. Pitt. Clinical Microbiology for Diagnostic Laboratory Scientists. 2017 John Wiley & Sons Ltd. Availabale at https://bibcercador.uab.cat/permalink/34CSUC_UAB/1eqfv2p/alma991010353534106709

3)      Guillem Prats. Microbiología y Parasitología Médicas. Editorial Panamericana. 2nd edition 2022. Availabale at https://bibcercador.uab.cat/permalink/34CSUC_UAB/1eqfv2p/alma991010879631306709

4)      Miller M, Miller S. A Guide to Specimen Management in Clinical Microbiology, Third Edition. 2017. Availabale at https://bibcercador.uab.cat/permalink/34CSUC_UAB/1eqfv2p/alma991010346792906709

5)      Leber A. Clinical Microbiology Procedures Handbook. ASM Books. 2016. Availabale in the UAB's web: https://bibcercador.uab.cat/permalink/34CSUC_UAB/1eqfv2p/alma991010432938606709

6)      Farreras-Rozman. Medicina Interna. 20th edition. Elsevier 2024. Available at the UAB's web: https://csuc-uab.primo.exlibrisgroup.com/view/action/uresolver.do?operation=resolveService&package_service_id=8970442540006709&institutionId=6709&customerId=6705&VE=true .

7)      Harrison Principles of Internal Medicine. 21a edición. MacGraw Hill 2022. Spanish verseion available online at https://bibcercador.uab.cat/permalink/34CSUC_UAB/avjcib/alma991010637433606709

8)     Molecular Medical Microbiology.  Tang, Yi-Wei ; Hindiyeh, Musa ; Liu, Dongyou ; Sails, Andrew ; Spearman, Paul ; Zhang, Jing-Ren ; Sussman, Max 2023. https://bibcercador.uab.cat/permalink/34CSUC_UAB/15r2rl8/cdi_askewsholts_vlebooks_9780323899925

 

Software

- http://www.pschreck.com/. P.C. Schreckenberger's Microbiology Homepage. Bayesian Microbial identification. For gramnegative bacilli

https://apiweb.biomerieux.com/?action=prepareLogin. Bayesian Microbial identification of Bio-Mérieux commertial system. Liscence required. Will be shown in class.

- Calculator for Positive Predictive Value (PPV) and Negative Predictive Value (NPV) for individual tests and combined. https://www.fda.gov/media/137612/download

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TEm) Theory (master) 1 Catalan/Spanish first semester afternoon
(PAULm) Classroom practices (master) 1 Catalan/Spanish first semester morning-mixed