Outline

Overview

This unit provides students with core skills in epidemiology, particularly the ability to critically appraise public health and clinical epidemiological research literature regarding public health and clinical issues. This unit covers: study types; measures of frequency and association; measurement bias; confounding/effect modification; randomized trials; systematic reviews; screening and test evaluation; infectious disease outbreaks; measuring public health impact and use and interpretation of population health data. Classes may be face to face or on-line and consist of a one-hour lecture/seminar and two-hour tutorial each week. Student attendance is expected at ALL classes. Students are expected to spend an additional three to four hours at least each week preparing for their classes.

Unit details and rules

Academic unit	Public Health
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	BSTA5011
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Erin Mathieu, erin.mathieu@sydney.edu.au
Lecturer(s)	Tim Driscoll, tim.driscoll@sydney.edu.au
	Erin Mathieu, erin.mathieu@sydney.edu.au
	Lucy Corbett, lucy.corbett@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Supervised exam ?	Final exam Written examination	60%	Formal exam period	2 hours
Outcomes assessed:
Tutorial quiz	Tutorial quiz Short answer or multiple choice quiz - IN CLASS - student must be present.	5%	Multiple weeks	10 to 15 minutes
Outcomes assessed:
Assignment	Mid-term assessment Written assessment	25%	Week 06 Due date: 06 Apr 2025 at 23:59	Detail provided on Canvas page
Outcomes assessed:
Online task	Weekly quizzes Online quizzes	10%	Weekly	Variable - 30 to 60 minutes
Outcomes assessed:
= hurdle task ? = AI allowed ?

Assessment summary

Assessment tasks include online weekly quizzes, in-class quizzes, a mid-term assessment and a final exam.

Permitted uses of AI in the online weekly quizzes, in-class quizzes, and mid-term assessment include:

· Searching for and summarising relevant literature.

· Translation.

· Checking grammar.

· Editing, polishing, and proofreading initial drafts.

The following uses of AI are prohibited:

· Generating ideas

· Answering multiple choice questions

· Using AI to write the first draft of any of your assignments

· Copying and pasting text generated by AI without incorporating original writing and your own interpretation.

You must NOT use AI to answer the content of weekly quizzes, the tutorial quizzes and the mid-term assessment.

AI is not permitted in the final exam.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Any written work submitted after 11:59pm on the due date may be penalised by 5% of the maximum awardable mark for each calendar day after the due date. If the assessment is submitted more than ten calendar days late, a mark of zero may be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Study Types	Lecture and tutorial (3 hr)
Week 02	Measures of Frequency	Lecture and tutorial (3 hr)
Week 03	Measures of Association	Lecture and tutorial (3 hr)
Week 04	Confounding and Effect Modification	Lecture and tutorial (3 hr)
Week 05	Selection Bias	Lecture and tutorial (3 hr)
Week 06	Measurement Error	Lecture and tutorial (3 hr)
Week 07	Randomised Controlled Trials	Lecture and tutorial (3 hr)
Week 08	Critical Appraisal	Lecture and tutorial (3 hr)
Week 09	Infectious disease outbreaks	Lecture and tutorial (3 hr)
Week 10	Systematic Review and Meta-Analysis	Lecture and tutorial (3 hr)
Week 11	Screening and Test Evaluation	Lecture and tutorial (3 hr)
Week 12	Causality and population health data	Lecture and tutorial (3 hr)
Week 13	Revision	Tutorial (2 hr)
Week 14 (STUVAC)	Population Health Data	Independent study (2 hr)
Week 14 (STUVAC)	Causality and Public Health Importance	Independent study (3 hr)

Attendance and class requirements

You should attend the live lecture/seminar sessions and the tutorials, either face-to-face or via Zoom, according to your enrolment mode.

Attendance at these sessions is not compulsory but is STRONGLY encouraged, in particular at the the tutorials. We consider that discussion and debate of concepts and approaches is a fundamental part of learning epidemiology and being able to apply the concepts; so, we want to see you in class!

Also, the in-class assessments held during semester can only be undertaken by students who attend the relevant tutorial.

More details are available from the unit Canvas site.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

See the unit Canvas site.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. identify whether the hypothesis of a paper is concerned with the efficacy of intervention, causality, test accuracy, or determining the magnitude of the health problem
LO2. identify which study type has been used, and judge how this affects the interpretation of the results
LO3. calculate and interpret measures of disease frequency and measures of association
LO4. identify and assess the implications of the main forms of bias (selection, measurement, confounding, lead time, and length time) in epidemiological and clinical medicine research
LO5. distinguish which of the methodological flaws in any paper are the most important
LO6. assess the overall quality of a research paper or report concerned with defining the magnitude of a health problem, evaluating the effect of a health intervention, causal inference, evaluating screening tests, and interpreting their use in different populations
LO7. assess the reliability, validity, and efficacy of a diagnostic test
LO8. (critically) appraise and use a systematic review
LO9. assess infectious disease outbreaks
LO10. identify and interpret key sources of population health data.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Changes were made to the lectures, tutorials and assessments for 2023. These included addition of in-class assessments in some tutorials and overall review of session content. For 2025, the in-class assessments (and associated on-going feedback to students) will be used again in 2025. The lecture and tutorial content have also been reviewed and revised where thought helpful to students.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI) and automated writing tools

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

PUBH5010: Epidemiology Methods and Uses

Semester 1, 2025 [Normal evening] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI) and automated writing tools

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links