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Epidemiology 1 (POPH90014)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville) and Online
To learn more, visit 2023 Course and subject delivery.
About this subject
Contact information
Semester 1
ankur.singh@unimelb.edu.au Andrew.lau@unimelb.edu.au
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
Semester 2
ankur.singh@unimelb.edu.au Andrew.lau@unimelb.edu.au
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
Overview
Availability | Semester 1 - Online Semester 2 - Dual-Delivery |
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Fees | Look up fees |
This subject is a core subject within the Master of Public Health, the Master of Epidemiology, the Master of Science (Epidemiology) and the Master of Biostatistics. Students should enrol in this subject early in their program of study.
Epidemiology is the study of the distribution and determinants of disease frequency in human populations and the application of this study to control health problems. It is a fundamental science of public health.
Three main tasks of epidemiology include description, causal inference and prediction. This subject focuses on the first two and emphasises the application of epidemiological evidence to informing public health practice and policy.
Description: the epidemiological measures of disease frequency and summary measures of population health are introduced and used to describe patterns and trends in disease occurrence within and between populations. The role of routinely collected data, particularly for surveillance of infectious diseases, is discussed.
Causal inference: is key to applying epidemiological evidence to controlling health problems if interventions are to be effective. In this subject, causal inference is considered within the modern counterfactual framework. Causal diagrams, which are an integral part of this approach to causal inference are introduced. The common experimental and observational study designs, and systematic reviews, and their relative strengths and weaknesses are discussed. The implications of common types of bias (selection bias, information bias, and confounding) are discussed, as are methods to minimise them. Methods to control for confounding, including standardisation, are discussed.
Differences in characteristics of the major sources of morbidity (infectious disease, non-communicable disease, and injury) are discussed in the context of prevention and early detection of disease. Transmission dynamics of infectious diseases are introduced in this context. The applicability of epidemiological evidence (external validity) to interventions in target populations is introduced. Measures of the validity and performance of tests for early detection are introduced.
Intended learning outcomes
At the completion of this subject, students are expected to be able to:
- Calculate and interpret measures of disease frequency, association, impact, and validity and performance of screening tests
- Interpret patterns and trends of disease within and between populations using surveillance and other routinely collected data
- Explain how differences in the epidemiological features of infectious diseases, non-communicable diseases, and injury influence strategies for their control
- Develop research questions to address causal questions in epidemiology
- Apply the counterfactual approach and epidemiological tools and guidelines to assessing causation in epidemiological studies
- Evaluate epidemiological evidence from experimental and observational studies
- Synthesise epidemiological evidence to inform decisions in public health
Generic skills
Upon completion of this subject, students will have developed skills in:
• Critical thinking and analysis
• Finding, evaluating and using relevant information
• Problem-solving
• Written communication
• Using computers
Last updated: 31 January 2024