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Course, academic year 2024/2025
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Epidemiology and evidence based medicine - D1106089
Title: Epidemiologie a medicína založená na důkazech
Guaranteed by: Department of Epidemiology (13-472)
Faculty: Second Faculty of Medicine
Actual: from 2023
Semester: summer
Points: 3
E-Credits: 3
Examination process: summer s.:
Hours per week, examination: summer s.:14/14, C+Ex [HT]
Extent per academic year: 14 [weeks]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
Key competences:  
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Level:  
Additional information: https://dl1.cuni.cz/course/view.php?id=15857
Guarantor: doc. MUDr. Pavla Brennan Kearns, Ph.D.
Co-requisite : D1105038
Pre-requisite : D1103002
Is co-requisite for: D1105038
Annotation -
The course is intended for students of the 3rd year of the General Medicine course, takes place in the summer semester and consists of six lectures and seven practical sessions. Lectures and practical sessions have specific intended learning outcomes (see the syllabus).
Last update: Brennan Kearns Pavla, doc. MUDr., Ph.D. (14.02.2024)
Course completion requirements -

In order to receive credits, the following two conditions must be met:

● Participation in practicals: It is possible to miss one practical for a serious reason, please let your teacher know.

● Successful completion of the online course "Vaccination - from Theory to Practice and Beyond” by 24.5.2024. The course is available on moodle: https://dl1.cuni.cz/course/view.php?id=4434. To successfully complete the course, at least 15 points in the self-test must be achieved. There are 3 attempts of this test.

Last update: Brennan Kearns Pavla, doc. MUDr., Ph.D. (14.02.2024)
Literature -

Kenneth J. Rothman , Epidemiology: An Introduction , 2nd edition , Oxford University Press , 2012.

Free access to this book will be provided to all students.

Last update: Brennan Kearns Pavla, doc. MUDr., Ph.D. (14.02.2024)
Requirements to the exam -

The course ends with a written exam that takes place during the exam period. It is necessary to register for the exam via SIS, the dates will be announced at the end of the summer semester. It is necessary to bring an ordinary calculator (not a phone) and a pen to the exam. The exam tests the achievement of the pre-defined intended learning outcomes and consists of 20 questions with 4 possible answers, only one of which is correct. One point is awarded for each correct answer.

Final grade:

18, 19 and 20 points: 1

16 and 17 points: 2

14 and 15 points: 3

13 or less points: 4 (failed)

In the case of a "failed" result, it is necessary to re-register for the written exam via SIS. In case of failure on the second attempt, a third attempt follows, which will take place as an oral exam.

Last update: Brennan Kearns Pavla, doc. MUDr., Ph.D. (14.02.2024)
Syllabus -

Lectures

1) Foundations of Epidemiology and Evidence-Based Medicine

Intended learning outcomes:

• Define the role of epidemiology.

• Evaluate the credibility of the evidence of individual types of descriptive and analytical studies according to the hierarchy in medical research

• Contrast and explain the terms internal validity, external validity, and precision.

2) Association and causality

Intended learning outcomes:

• Explain the principle of randomization.

• Apply Bradford-Hill criteria to the results of an observational study.

3) Principles of epidemiology of infectious diseases

Intended learning outcomes:

• Define and characterize basic concepts (epidemic, pandemic, epidemiological triangle, surveillance, herd immunity, incubation period, latent period, infectious period, basic reproductive number, effective reproductive number).

• Differentiate between direct and indirect type of transmission and list relevant examples.

• Explain the SIR (susceptible-infectious-recovered) framework.

• Calculate the potential necessary vaccine coverage for a given disease based on vaccine efficacy and basic reproductive number.

4) Epidemiology of non-communicable diseases

Intended learning outcomes:

• Describe trends in the occurrence of non-communicable diseases (cardiovascular, mental, neurological, oncological diseases and diabetes mellitus )

• List and explain the role of risk factors in the development of non-communicable diseases.

• Propose effective measures to promote prevention of non-communicable diseases.

5) An introduction to social epidemiology and health inequalities

Intended learning outcomes:

• Define what are social determinants of health using examples and describe multiple mechanisms by which they influence individual and public health.

• Understand ways of measuring inequalities (absolute vs. relative) and differences between disparity, inequity, and inequality.

• Explain the concept of natural experiment and quasi-experiment and describe how they may contribute to establishing causal links in social epidemiology.

• Debate how social determinants of health may influence quality of care and what clinicians can do to limit their role.

6) Emerging and re-emerging infectious diseases

Intended learning outcomes:

• Explain biological mechanisms for the emergence and re-emergence of infectious diseases.

• Assess the risk of emerging and re-emerging infections, interpret trends in their occurrence and identify risk factors for their occurrence and spread.

• Specify social causes for the emergence and re-emergence of infectious diseases.

Practical sessions:

1) Parameters of disease occurrence and death

Intended learning outcomes:

• Calculate a suitable indicator of the occurrence of a disease (chance, prevalence, risk, incidence rate, attack rate) and death (mortality, case fatality rate).

• Reflect on the appropriateness of using cumulative incidence and incidence rate on the example of specific diseases.

• Hypothesize a mechanism in the change of incidence / prevalence / mortality / case fatality rate.

2) Association parameters

Intended learning outcomes:

• Calculate an appropriate relative (risk ratio, incidence rate ratio, odds ratio) or absolute (risk difference, incidence rate difference, attributable risk, population attributable risk) indicator for the association between a risk/protective factor and a disease.

• Interpret the resulting association indicator in terms of its value and statistical significance.

3) Observational analytical studies

Intended learning outcomes:

• Recognize the type of study and assess the strength of its evidence within the hierarchy.

• Characterize main advantages and disadvantages of analytical studies.

• Propose an appropriate analytical study design for a specific research question.

• Calculate and interpret an appropriate indicator of association (relative risk, odds ratio).

4) Bias

Intended learning outcomes:

• Determine individual types of bias (confounding, selection bias, information bias) and their effect on the outcome of the study.

• Contrast between a confounding factor, a mediator, and an effect modifier.

• Apply various methods of eliminating confounding factors.

5) Journal Club

Intended learning outcomes:

• Evaluate the overall quality, validity and precision of an observational study.

• Interpret study results, including graphical displays (tables, graphs).

• Recognize bias, its type and the direction, in which it distorts the results.

6) Evidence-based medicine I

Intended learning outcomes:

• Formulate research and clinical questions using the PICO system.

• Assess the overall quality, validity and precision of a randomized controlled trial.

• Interpret result of a randomized controlled trial in terms of clinical and statistical significance.

• Decide whether it is possible to apply result of a randomized controlled trial to a specific patient.

7) Evidence-based medicine II

Intended learning outcomes:

• Assign a level of evidence (AD) for a study.

• Evaluate validity of a systematic review (specificity of the question, search and selection strategy of studies, evaluation of the risk of bias of primary studies).

• Interpret a Forrest plot (value, precision, heterogeneity).

• Assess the risk of publication bias in a systematic review / meta-analysis.

Last update: Brennan Kearns Pavla, doc. MUDr., Ph.D. (14.02.2024)
 
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