Title: Good epidemiological practice: design, implementation and analysis of global health studies (e-learning))
Keywords: Quantitative methods
International/Global Health
Ethics
Epidemiology
Country: Netherlands
Institution: The Netherlands - Royal Tropical Institute (KIT), Amsterdam
Course coordinator: Dr Sandra Alba
Date start: 2021-12-13
Date end: 2021-12-17
About duration and dates: Classroom sessions: 16hrs E-learning: 3hrs Guided practical sessions with Stata: 6hrs Guided group work (tutorial): 3hrs Self-study: 11hrs Exam: 3hrs Total: 42 hrs
Classification: advanced optional
Mode of delivery: Distance-based
Course location: KIT Royal Tropical Institute, Amsterdam
PO Box 95001, Amsterdam, The Netherlands.
Tel: +31-20-5688256 / Website: http://www.kit.nl
ECTS credit points: 1.5 ECTS credits
SIT:
Classroom sessions: 16hrs
E-learning: 3hrs
Guided practical sessions with Stata: 6hrs
Guided group work (tutorial): 3hrs
Self-study: 11hrs
Exam: 3hrs

Total: 42 hrs
Language: English
Description:
At the end of the course participants should be able to:
• Recognise and adhere to the fundamental principles of good epidemiological practice
• Perform basic data management and data analysis in Stata
• Interpret and contrast results from linear and logistic regression analyses (univariate and multivariate)
Assessment Procedures:
At the end of the one week program students will be given a statistical analysis plan and a checklist to assess it. This summative assessment will be an open book in-classroom exam. Feedback will be provided within three weeks of completion. A resit exam will be provided to those who failed within 2 months after reception of the results The passmark is 5.5 out of 10.
Content:
• Fundamentals of good epidemiological practice (including existing guidelines) covering all steps of an epidemiological study ranging from study preparation to reporting/dissemination and data storage
• Purpose and content of a statistical analysis plan and other study documentation
• Sampling approaches for community based and health facility based surveys/studies
• Introduction to sample size calculation
• Basic data management with Stata (using do-files)
• Contingency tables, Chi-square and t-tests with Stata (using do-files)
• Interpretation of linear regression (Stata input and output)
• Interpretation of logistic regression (Stata input and output)
• Interpretation of multiple logistic regression (Stata input and output)
• Tutorial: guided analysis of a dataset (groups of apx 5 students with a tutor)
• Exam
Methods:
Throughout the course, all sessions will be embedded within a practical case study. Participants will be put in the perspective of a panel of experts who need to review the planning and conduct of a nation-wide study, and advise policy-makers based on its results. Sessions will include lectures, individual online learning, group exercises, discussions, practical sessions with Stata, and tutored data analysis session.

The online learning session, all study material including preparatory reading will be shared via the KIT online learning platform (Virtual Grounds).
Prerequisites:
• Having completed the core course OR Bachelor’s degree or equivalent academic training in either medicine or another field related to health care, such as health sciences, economics, social science or nursing.
• Successfully completed a statistics and epidemiology course covering measures of association in public health (odds and risk ratios), statistical inference (chi-square ant t-tests), confidence intervals, Type I and Type II errors.
• Participants should bring their own computer with Windows installed. A free 1-month Stata licence will be provided for the course
• Proficiency in spoken and written English equivalent to TOEFL score of 5.5 or a IELTS academic score of 6.0
Attendance:
30 participants max
Selection:
TropEd students will be given priority over other external applicants. There is no maximum number for TropEd students.
Fees:
• EUR 500 for TropEd students
• EUR 750 for external applicants
Scholarships:
No scholarships available
tropEd accreditation: Accredited in January 2019, in Lisbon.
This accreditation is valid until January 2024.
Remarks:
Epidemiology is the cornerstone of global health. It shapes policy decisions and evidence-based practice by identifying disease risk factors and preventive healthcare targets. Most epidemiological findings are genuine and make an important contribution to global health, but some findings are obtained from ill-designed, poorly implemented, inappropriately analysed or selectively reported studies.

This course aims to provide students with the skills and knowledge needed to critically appraise epidemiological practice in global health, as a basis for sound decision making. The course will have a strong focus on the emerging themes of good epidemiological practice within the boarder debate of reproducibility crisis in science.

Recommended reading will include:
• Alba and Mergenthaler 2018 - Lies, damned lies and epidemiology: why global health needs good epidemiological practice
• CIOMS 2006 - International Ethical Guidelines for Health-related Research Involving Humans
• Juul 2004 - Take good care of your data
• OECD 2011 - Data quality dimensions
• Von Elm 2007 - The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies
• UK data archive 2011 - Managing and Sharing Data: Best Practice For Researchers
• Tangcharoensathien 2010. Sharing health data: developing country perspectives.
Email Address: s.alba@kit.nl
Date Of Record Creation: 2019-02-15 08:34:39 (W3C-DTF)
Date Of Record Release: 2019-02-15 13:56:15 (W3C-DTF)
Date Record Checked: 2019-02-15 (W3C-DTF)
Date Last Modified: 2021-11-20 21:55:59 (W3C-DTF)