| This course runs from 23 June to 11 July 2025 in London.This course will also run in The Gambia (find out more information). |
The course will have a hybrid format and students can choose to attend in person in London or online.
Data is key - in everything from vaccines to pandemics, cancer prevention or climate change. Being able to understand and analyse the numbers underpins efforts to improve health outcomes and tackle today’s challenges in public health and healthcare.
This three-week course brings together the basic principles of two complementary disciplines: epidemiology and medical statistics. It will give you a foundation in practical statistical tools and confidence to make sense of the sometimes overwhelming amount of healthcare data that exists.
You will learn from highly experienced researchers through fascinating real-world examples on a wide range of topics from infectious disease to clinical care and prevention. These insights will help you apply your new knowledge to study design, interpretation and analysis, laying the groundwork to avoid common pitfalls and follow the latest best practices.
Year after year, participants in this course have also developed a supportive and collaborative community as they work through the packed schedule of theory and practical elements.
Who should apply?
The course is relevant to clinicians, current PhD students, and other graduates who work in medical research units, academic institutions, or health services. The course is designed primarily for those working on epidemiological research projects, or for anyone interested in moving in that direction or finding out more. Or perhaps you’ve recently graduated, in which case this course can be a useful way of getting a taster of the field before more in-depth studies such as a Master’s or starting on your career or further training.
Whether you’re looking to build on current knowledge or just starting in this field, this course is an excellent opportunity to learn fundamental principles and skills from world-leading experts and join a life-long community of professionals in epidemiology and medical statistics.
Applicants should have a good command of the English language. However, no previous formal training in epidemiology or statistics is required. Those who are already confident in these methods may prefer to consider the Advanced Course in Epidemiological Analysis, which can also be a helpful next step to take after completing this course.
Teaching methods
You can study this hybrid short course either online or in person. Course participants will receive three weeks of training in the fundamental principles of epidemiology and medical statistics.
This introduction to the field focuses on:
- The basic concepts of epidemiology.
- The application of statistical methods, including linear and logistic regression, using STATA and R software.
- Practical skills in study design, data analysis and interpretation.
Participants should expect to spend approximately 5-6 hours daily on the course. Of these, 2 hours will be live/recorded lectures, and 3 hours will be practical with tutor support, to be taken at the same time for all participants (usually 11 am-3.30 pm BST). A more detailed timetable will be available at the start of the course.
Members of the Faculty of Epidemiology & Population Health of the London School of Hygiene & Tropical Medicine will teach the course. LSHTM is well known as a leading international centre for epidemiological research. Staff have considerable experience in the design and analysis of epidemiological studies in high, middle and low-income settings.
Course Content
The topics to be covered will include:
- Measuring health and disease
- Data and distributions
- Study design: ecological and cross-sectional studies
- Study design: cohort studies
- Study design: intervention studies
- Study design: case-control studies
- Introduction to data analysis
- Errors, biases & confounding
- Measures of effect and impact
- Statistical inference
- Analysis of categorical data
- Confounding and stratification
- Analysing quantitative data
- Errors in exposure and outcome measurements
- Prevention strategies
- Sample size and power
- Epidemiology to Policy
- Regression and correlation
- Introduction to logistic regression
- Infectious disease epidemiology
- Multiple regression
- Sampling
- Systematic reviews and meta-analysis
Comprehensive notes will be given to participants, but the following books are recommended for those interested in further reading:
- Webb P and Bain C. Essential Epidemiology: An introduction for Students and Health Professionals. Cambridge University Press. 2011.
- Bailey L, Vardulaki K, Langham J and Chandramohan D, Introduction to Epidemiology, Open University Press, 2005 (Understanding Public Health, Series editors: Nick Black and Rosalind Raine).
- Essentials of Medical Statistics (2nd Edition); B Kirkwood (Blackwell Publishing, 2003).
The course makes use of the STATA and R packages during some practical data analysis sessions.
There is no formal assessment, but at the conclusion of the course, a Certificate of Attendance will be provided. Approximately 30-60 participants will be accepted.
Comments by course participants
"In terms of feedback for the course, it is the most useful short course I have done since starting my academic career. I have done a plethora of statistics modules and short courses, but none of it really hit home until it was actually integrated with study design. I really don’t think one can be consolidated without the other, making your unique combination gold dust for early academics.
The variety of coordinators meant the content was delivered in many unique, changing and thus, constantly engaging ways. It was clear that all lecturers were experts in their field, had immense experience in what they were discussing, and had delivered it many times to allow proficiency, but maintained a passion and an openness throughout.
It really was a wonderful experience, one that further ingrained my love for the scientific process. And how lucky we all are to implement it for a living."
Fearghal Behan
"The course was well-designed and effectively delivered. The structure, which began with theory sessions followed by practical exercises, significantly reinforced the skills being taught. Additionally, the course was taught by experts in their respective fields, ensuring that the examples and practical exercises were current and relevant.
Personally, I benefitted by not only gaining a deeper understanding of data analysis but also learning the R programming language, which was one of my main objectives for joining the course. While I have been using Stata for my analysis, this course provided me with the opportunity to expand my skills by learning a new programming language."
Henry Karanja
"Many thanks to you James, Camille and your entire team for the tremendous work that you have and continue to put into this course. I only wish I had done it sooner as now I realise that mere mortals like me can actually grasp the contents of this subject matter. The course was so well structured and easy to navigate. As a former RANZCOG trainee, I now encourage current trainees to undertake this course prior to their undertaking their research requirement for the training. Cannot recommend it enough to anyone who seeks to understand evidence-based medicine."
Mabimba Mwanza
"The ICEMS short course was an excellent learning opportunity that has had an impact on my research. I used the knowledge and skills I gained during the course to refine my research questions and improve my methods. I found the medical statistics modules particularly valuable, as they provided important insights into selecting appropriate statistical methods for analyzing data. The interactive practical sessions were also really useful because we practised analytical skills on real-life research data, this boosted my confidence in interpreting and reporting statistical model outputs."
Effita Masoamphambe
The course fee includes all teaching and practical materials (in electronic format) and access to relevant statistical programmes for the duration of the course. The fee for 2025 is £3,700 and includes a Certificate of Attendance.
Applying for this course
Applications for 2025 are now open and can be made via our online application form.
Please read LSHTM's Admissions policies prior to submitting your application.
Visas
The student is responsible for obtaining any visa or other permissions to attend the course, and is encouraged to start the application process as early as possible as obtaining a visa for the UK can sometimes take a long time. The Short Courses team can provide supporting documentation if requested.
Accommodation
A list of hotels located in the vicinity of LSHTM, along with further resources for short term accommodation, can be found on our accommodation pages.
Important information
Please note:
- Students will be required to bring their own laptops. The Stata package will be available for the duration of the course.
- If you have been offered a place on the course you will not be able to register without bringing a formal ID (Passport) and without having obtained the correct visa if required.
- It is essential that you read the current visa requirements for short course students.
- LSHTM may cancel courses two weeks before the first day of the course if numbers prove insufficient. In those circumstances, course fees will be refunded.
- LSHTM cannot accept responsibility for accommodation, travel and other losses incurred as a result of the course being cancelled.