Introductory description

Epidemiology is key to understanding disease patterns, predicting outbreaks, and shaping public health responses. This module explores how we define and measure disease, model its spread, and use evidence to inform health policy, bridging theory and real-world application.

The module is structured around three core themes:
Quantifying Disease – How do we measure disease in populations? This section covers case definitions, diagnostic accuracy, study designs, and key epidemiological metrics for both infectious and non-communicable diseases.
Disease Dynamics – How do infections spread? Using mathematical models, students will explore epidemic patterns, herd immunity, control and intervention, and various factors that influence the dynamics of infectious disease.
Public Health and Policy – How do we turn data into action? This section examines how epidemiological evidence guides interventions, and how decisions are made linking science to economics and policy.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

This module introduces key concepts in epidemiology and public health, covering both infectious and non-infectious diseases in human and animal populations, with an emphasis on infectious disease dynamics. The content is structured around three equally weighted areas:

1. Assessing the Evidence – Measuring disease occurrence, evaluating risk factors, and establishing causality using epidemiological study designs and diagnostic accuracy measures.
2. Predicting Disease Dynamics – Understanding how infectious diseases spread, using mathematical models to explore epidemic patterns, herd immunity, and the impact of interventions.
3. Protecting Population Health – Applying epidemiological evidence to public health decision-making, including disease prevention strategies, vaccination policies, and managing health inequalities.

This structure ensures students develop quantitative, analytical, and applied skills to assess, predict, and manage disease at both individual and population levels.

Learning outcomes

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

• Apply epidemiological methods to measure and analyse disease patterns in populations
• Evaluate disease causation and risk factors
• Understand how to build and interpret basic epidemiological models
• Explain how infectious diseases spread dynamically
• Assess the role of epidemiology in public health

Indicative reading list

Coggon, D., Rose, G. and Barker, D. J. P. (eds). Epidemiology for the Uninitiated, 5th Ed. (BMJ Publishing Group, 2003). ISBN 0-7279-1604-1. Contains 80 pages.
Keeling, M. J. and Rohani, P. Modeling Infectious Diseases in Humans and Animals (Princeton University Press, 2008). ISBN13: 978-0-691-11617-4

Subject specific skills

Students will develop the ability to:

1. Analyse and interpret epidemiological data, using statistical and computational tools to assess disease risk, causality, and transmission patterns.
2. Evaluate diagnostic and screening methods, critically assessing their sensitivity, specificity, and real-world applicability in different population settings.
3. Apply mathematical models to simulate infectious disease transmission, exploring the effects of different transmission routes, intervention strategies, and population dynamics.
4. Assess public health policies based on epidemiological evidence, interpreting how scientific data informs decision-making in disease control, vaccination programs, and health inequalities.
5. Integrate knowledge from immunology, epidemiology, and public health, synthesising complex interactions between host immunity, pathogens, and societal factors in disease outcomes.

Transferable skills

1. Quantitative data analysis skills, including interpreting measures and using models to assess real-world health challenges.
2. Independent and self-directed learning, building the ability to critically engage with scientific literature and epidemiological data.
3. Problem-solving and analytical thinking, applying epidemiological concepts to assess risks, design studies, and evaluate public health interventions.
4. Effective communication of complex data, translating epidemiological findings into clear, evidence-based conclusions for scientific and policy audiences.