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L19_Introduction to Epidemiology and Population Sciences

May 12, 2025

Introduction to Epidemiology and Population Sciences

Lecture by Prof Mieke Van Hemelrijck

  • Part of Transforming Cancer Outcomes through Research (TOUR) at Kings College London

Key Objectives

  • Define and explain the relevance of epidemiology in population health.
  • Understand key concepts such as exposure, outcome, and risk.
  • Differentiate between prevalence and incidence in public health.
  • Describe and distinguish relative and absolute measures of effect.
  • Identify confounding sources and strategies to control confounding.
  • Define effect modification and distinguish it from confounding.
  • Appreciate historical context and significance of epidemiological work.

TOUR Overview

  • Aim: Improve healthcare outcomes by translating oncology research into clinical practice.
  • Focus on clinical cancer epidemiology.
  • Methodology for prevention, diagnosis, treatment outcomes, and cancer survivorship.

Modules Offered

  1. 4BBY1002: Introduction to Clinical Exercise Epidemiology
  2. 5MCS1000: Introduction to Epidemiology & Population Sciences (15 credits, Semester B)
  3. 6MCS1001: Advanced Epidemiology & Population Sciences (15 credits, Semester B)
  4. 6MCS1000: Cancer in Context: Public Health & Clinical Epidemiology (15 Credits, Semester A)

Historical Context: Dr John Snow

  • Widely regarded for his work in London with a famous case involving a pump handle, leading to advancements in public health.

What is Epidemiology?

  • Study of disease distribution and determinants in human populations.
  • Aims to prevent disease by identifying and eliminating determinants.
  • Involves biostatistical methods.

Key Concepts in Epidemiology

  • Exposure: Risk factor or characteristic influencing an event.
  • Outcome: Disease, progression, death, comorbidity.
  • Prevalence: Proportion of a population with a condition at a specific time.
  • Incidence: Proportion developing a condition over a period.
  • Risk: Probability of disease occurrence in a time interval.
  • Relative and Absolute Effects: Comparisons of exposed vs unexposed.

Confounding

  • Distortion of the effect of exposure due to extraneous factors.
  • Classic examples: Birth order and maternal age on Down syndrome.
  • Control methods: Randomisation, Restriction, Matching, Stratification.

Effect Modification

  • Interaction between risk factors modifying outcomes.
  • Example: Physical activity’s effect on heart disease risk depending on BMI.

Course Content Highlights

  • 5MCS1000: Includes study design, bias, confounding, causality, RCTs, behavioural and implementation sciences.
  • 6MCS1001: Covers lifestyle markers, systematic reviews, pharmaco-epidemiology, behaviour, real-world evidence.
  • 6MCS1001: Focuses on cancer epidemiology, behavioural sciences, RCTs vs real-world evidence, quality of life.
  • 6MCS1000: Public health and clinical epidemiology related to cancer.

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