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PhD Epidemiology, Evolution and Control of Infectious Diseases

PhD Epidemiology, Evolution and Control of Infectious Diseases

Programme details


Year 1


The 4-year programme begins with a 1 year specialist MRes course. During this first year, students will undertake core training one day each week, including sessions on infectious disease epidemiology, statistics, infectious disease modelling, bioinformatics, genetics and evolution, programming skills and technical workshops. In addition, the MRes course will include a component of generic skills training, including seminars and workshops on grant writing, peer review, information retrieval, ethics, academic writing and presentation.

Alongside the taught courses, students undertake two 5-month attachments in the research groups of potential PhD supervisors. Types of research project include extended systematic literature reviews, primary field data collection, secondary data analysis, laboratory-based analysis and mathematical modelling. During these placements, students will be full members of the research group, attending group meetings and participating in internal seminars in the same manner as PhD students and postdoctoral staff. Year 1 will be assessed on the basis of written reports and oral presentations of the two projects. In addition, students need to pass a separate grant writing exercise as part of the core development programme.


Years 2-4


At the end of the first year students who have achieved a Merit or better in the MRes will move onto the PhD programme. The School of Public Health provides a comprehensive research training programme for all PhD students. In addition, students receive general training in transferable skills through the highly-rated Graduate School.

The Department provides further technical training for PhD students via lunch-time courses on open to both students and postdoctoral staff (for example, computer programming, statistical inference, genetics and evolution), and via informal research discussion groups (again for both students and postdoctoral staff). Students are expected to attend the weekly Departmental research seminars,and are encouraged to be active members of academic community of the MRC Centre and Department.

Throughout the 4-year programme students will also be members of the Graduate School. The Graduate School provides an award-winning and internationally renowned programme of transferable skills training, including personal development & effectiveness, presentation skills, project management, networking and research ethics. There is also a three-day residential course in research and professional skills development which all students are strongly encouraged to attend at the beginning of Year 2.




Four 4-year Wellcome Trust studentships are available for this course. All studentships provide generous support including a tax-free stipend to cover living expenses. The value of this stipend is reviewed annually. For the 2019 cohort stipends will be not less than £22,278 in year 1, rising to £26,839 in year 4. Stipends are tax-free.

Up to two additional studentships funded by Northampton College are available. These studentships provide a stipend at the research council rates, currently £16,777 in the first year rising to £18,000 for the next 3 years. Stipends are tax-free.

Additionally a number of studentships funded by the MRC Centre for Global Infectious Disease Analysis (MRC GIDA) are available. These studentships provide a stipend at the research council rates, currently £16,777 in the first year rising to £18,000 for the next 3 years. Stipends are tax-free.

Tuition fees at the rate applicable to Home (EU) students are provided by the Wellcome Trust and Northampton College and MRC funding. Suitably qualified non-EU students are welcome to apply and we particularly welcome applications from low and middle-income countries (LMIC). Non-EU students will be liable for paying the difference between the home and overseas fee rates. A scholarship is available for up to 1 LMIC student to cover the difference between the home and overseas rates

Additional studentships may become available over the course of the admission process – all eligible candidates will be considered without needing to submit any further details.

Please note that this does not include MRC Doctoral Training Programme studentships for which a separate application process should be followed. Please note that this scheme has an earlier deadline date (19 November 2018 for 2019 entry). Successful students under this scheme are able to join this 4-year programme.

All applications will be considered equally irrespective of financial means, age and nationality.


Research areas


Both the MRes and PhD projects are embedded within the wider research in the Department of Infectious Disease Epidemiology. The research in the department focuses on the transmission, evolution and control of infectious diseases in both human and animal populations. A particular strength is in epidemiological and genetic analysis and mathematical modelling.  

The work in the department spans a wide range of disease areas, including emerging infectious diseases, HIV, malaria, tuberculosis, polio, influenza, mosquito-borne viral infections, sexually transmitted infections, neglected tropical diseases and bacterial and fungal infections. Since much of our research has direct relevant to policy, we work in close partnership with a wide range of public and global health organisations – including Public Health England (PHE) and the World Health Organisation (WHO).  

MSc Epidemiology

MSc Epidemiology


Duration: 1 year full-time

ECTS: 90 credits



This course offers training in the methodology, design, conduct and interpretation of epidemiological studies on chronic and infectious diseases.

Epidemiology is the study of the distribution, causes, and possible prevention and control, of diseases in populations.

The MSc in Epidemiology offers training in the methodology, design, conduct and interpretation of epidemiological studies on chronic and infectious diseases.

It is particularly suitable for students who wish to acquire skills in epidemiology and biostatistics, and to get involved with research projects.


Study programme


In the first term, all students follow a common core pathway covering epidemiological methods, biostatistics, and infectious and chronic disease epidemiologyTerm two modules aim to reflect areas of emerging research as well as providing extended tutoring in core epidemiological and statistical concepts and skills, building upon the knowledge, insight and skills gained in term one.

The third term consists of a four-month research project carried out under supervision, possibly in collaboration with other universities and research institutions.




Upon completion of this course, students usually develop an academic career by beginning a PhD, or move on to work for public health organisations, pharmaceutical companies or non-governmental agencies.



Modules shown are for the 2019-20 academic year and are subject to change depending on your year of entry.

Please note that the curriculum of this course is currently being reviewed as part of a College-wide process to introduce a standardised modular structure. As a result, the content and assessment structures of this course may change for your year of entry. We therefore recommend that you check this course page before finalising your application and after submitting it as we will aim to update this page as soon as any changes are ratified by the College.

Find out more about the limited circumstances in which we may need to make changes to or in relation to our courses, the type of changes we may make and how we will tell you about changes we have made.


You take all of the core modules below.


Introduction to Infectious Disease Modelling


This module provides an overview of infectious disease modelling and develops skills in designing and analysing infectious disease models for public health policy. Students will be taught how to represent the characteristics of an infectious disease using a mathematical model, how to simulate that model using a computer, and how to analyse that model. Students will also learn how models have been applied in public health policy, and how models are designed to address a research question. 


Principles and Methods of Epidemiology


This module ensures students will be familiar with the core concepts of epidemiology and acquire the skills necessary to describe, analyse, interpret and appraise epidemiological studies. Further modules and projects require such knowledge, and a good grasp of these basics is thus essential for successful completion of the degree. 


Disease Masterclass


This module aims to provide students with an overview of core health challenges and lines of epidemiological research being undertaken, across a range of infectious and non-communicable diseases.    


Introduction to Statistical Thinking and Data Analysis


The aim of this module is to give students an understanding of the importance of statistical thinking in epidemiology, randomised trials and public health, to enable them to critically evaluate the results of standard statistical analyses published in journal articles and to carry out a range of statistical analyses using 

You choose six optional modules from below.




Bayesian Statistics




The module introduces the students to the concepts of Bayesian models and inference commonly used in Biostatistics. Throughout the entire module several examples from epidemiology, social science, and clinical trials will be introduced to complement the theory. The students will also become familiar with the software package OpenBUGS, which will be used to implement the Bayesian models presented. 




Spatial Analysis




This module will introduce students to the main statistical methods used in spatial epidemiology and provide them with the theoretical and practical skills to analyse and interpret geo-referenced health data.




Molecular and Genetic Epidemiology




This module provides students with a fundamental understanding of the core concepts of molecular and genetic epidemiology and the application of molecular and genetic epidemiologic findings to public health and translational medicine. The module will encompass the appropriate study design for molecular and genetic epidemiologic investigations, biomarker development and the integration of biomarkers into epidemiologic studies, and the application of new and emerging molecular technologies in epidemiologic research.




Genetics of Infectious Disease Pathogens




The aim of this module is to introduce students to both the theoretical concepts and the practical methodology used in the genetic epidemiology of infectious pathogens. The module content includes pathogen population genetics, phylogenetics, phylodynamics and antimicrobial resistance. 




Further Methods in Infectious Disease Modelling




The module aims to provide students with the ability to interpret key evidence generated by modern infectious disease modelling methods that appears in non-specialist high impact journals. By the end of the course, students will also be able to design, execute and interpret results from streamlined versions of those same models. Although students will be given the opportunity to implement complex models using mathematical techniques and basic programming tools, they will not be expected to independently generate results from novel complex models. 








Building on the skills gained by students in earlier modules (including the prerequisite module Further Methods in Infectious Disease Modelling), this module aims to give a broad and “real-life” view of using epidemiological research (specifically mathematical models and statistical analysis) to address key public health questions relating to the control of outbreaks. The module includes important contemporary topics such as the broader ecological context of infectious disease emergence and transmission, as well as state-of-the-art techniques required to calibrate mathematical models and make the best use of data. 




Advanced Regression




This module will allow students to become familiar with the principles of advanced regression for high-dimensional data so that they are able to apply such techniques on real data problems (e.g. complex omics data). In particular, students will learn how to perform advanced statistical analyses, including penalised likelihood and nonparametric regression models using R. 




Advanced Topics in Biostatistics




The module will introduce some of the issues faced while analysing complex datasets in advanced epidemiology. From these illustrations, methodological developments to address the resulting technical/computational challenges will be described, assessed and compared. Each of these established methods will be associated with a practical session during which students will implement the method.


In Term 3, individual research projects are carried out under supervision.

It is possible that the projects may be carried out in collaboration with other universities and research institutions, but this is not common and not always recommended.

Projects are expected to take four months of full-time study, with one (or more) member(s) of Imperial academic staff assigned to advise and monitor students. There may also be external supervisors.

Teaching and assessment


Teaching methods


  • Class tutorials
  • Computer-based practical workshops
  • Final research project (dissertation)
  • Formative and summative assessment via Blackboard e.g. in-class quizzes
  • Group work sessions
  • Group workshops and revision sessions
  • Lectures
  • Mentimeter
  • Seminars and practicals
  • Small group tutorials
  • Teaching materials published via Blackboard

Assessment methods


  • Articles and case study reviews
  • Computer based tests
  • Essays
  • Individual and group presentations
  • MCQs and online quizzes
  • Mini research project
  • Reports and paper reviews
  • Written examinations

Entry requirements


We welcome students from all over the world and consider all applicants on an individual basis.

Minimum academic requirement

Our minimum requirement is a 2.1 degree in mathematics, statistics, medicine (human or veterinary) or biological sciences.

International qualifications

We also accept a wide variety of international qualifications.

The academic requirement above is for applicants who hold or who are working towards a USA qualification.

For guidance see our Country Index though please note that the standards listed here are the minimum for entry to the College, and not specifically this Department.

If you have any questions about admissions and the standard required for the qualification you hold or are currently studying then please contact the relevant admissions team.

English language requirement (all applicants)

All candidates must demonstrate a minimum level of English language proficiency for admission to the College.

For admission to this course, you must achieve the standard College requirement in the appropriate English language qualification. For details of the minimum grades required to achieve this requirement, please see the English language requirements for postgraduate applicants.

How to apply



Making an application

All applicants to our Master’s courses must apply online.