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This module will introduce students to the field that has developed at the interface between epidemiology and molecular biology. The course will cover core concepts that underpin this area of research, providing students with a basic understanding of the key molecular methods used to generate molecular datasets and the epidemiological and statistical concepts that are used to link molecular data with clinical and behavioural data and interrogate these datasets. In this module,Ìýbasic assumptions underlying molecular epidemiology, laboratory methods, key terminology and definitions, applications of molecular epidemiology, computational methods and phylogenetic tree construction and interpretation, limitations of molecular epidemiology, and ethical issues will be explained. At the end of the module, students will have a good working knowledge of how to read and critique infectious disease molecular epidemiological research and be able to apply this knowledge in understanding infectious diseases and their control.

By the end of the module, students should be able to:

1. Describe the basic assumptions underlying molecular epidemiology, including that pathogens with similar profiles (as measured by molecular typing) are likely to be related, and that the degree of similarity between strains can be used to infer the time since their divergence
2. Define key terms within molecular epidemiology, including strain, isolate, clone, clade, molecular clock, and phylogenetic tree nomenclature
3. Articulate a basic understanding of the key laboratory methods used to generate molecular data for different pathogens, and describe their main advantages and limitations
4. Articulate a basic understanding of the key computational methods used to build phylogenetic trees to answer relevant public health questions, and describe their main advantages and limitations
5. Outline and give examples of the main applications of molecular epidemiology for infectious diseases, including outbreak investigations, surveillance, investigation of transmission dynamics, natural history of infection and disease (e.g. relapse versus reinfection), pathogen evolution, cross contamination, measurement of virulence and antimicrobial resistance, and evaluation of interventions
6. Undertake case studies to explore instances where molecular epidemiology has led to scientific or public health advances (and where it has not)
7. Critically evaluate peer-reviewed published papers on molecular epidemiology to demonstrate understanding about the key limitations, including the importance of understanding background prevalence, and issues around missing data, multi-strain infections, discovery bias, sample size calculations, clustering, cross-contamination, and inferring transmission directionality
8. Articulate a basic understanding of the ethical issues arising when undertaking molecular epidemiology studies for infectious diseases.

This module is mandatory for students in the MSc Applied Infectious Disease Epidemiology.

This module will be delivered using a combination of teaching and self-directed reading and learning. Interactive lectures will be combined with seminars and group discussion, where critical appraisal of scientific evidence will be explicitly taught. Tutors within IGH will carry out the bulk of teaching, but external lecturers may also be employed.

Readings for this module include:

• SintchenkoÌýV, Holmes EC. The role of pathogen genomics in assessing disease transmission. BMJ. 2015 May 11; 350: h1314.
• N Field, DÌýMacCannell, and H Stagg. Oxford Specialist Handbook of Infectious Disease Epidemiology; Chapter 10, Molecular Epidemiology. Oxford University Press. 2016.
• H Stagg, S H Aliyu, N Field. Oxford Specialist Handbook of Infectious Disease Epidemiology; Chapter 9, Public health microbiology. Oxford University Press. 2016.
• Field N, Cohen T,ÌýStruelensÌýMJ, et al. Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) an extension of the STROBE statement. Lancet Infect Dis 2014; published online March 14.