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Unit outline_

PUBH5010: Epidemiology Methods and Uses

Semester 1, 2024 [Normal day] - Camperdown/Darlington, Sydney

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. CIasses may be face to face or on-line and student attendance is expected at ALL classes. Students are expected to spend an additional two to three 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 Tim Driscoll, tim.driscoll@sydney.edu.au
Lecturer(s) Tim Driscoll, tim.driscoll@sydney.edu.au
Edward Jegasothy, edward.jegasothy@sydney.edu.au
Kate Milledge, kate.milledge@sydney.edu.au
The census date for this unit availability is 2 April 2024
Type Description Weight Due Length
Supervised exam
? 
hurdle task
Final exam
Written examination
65% Formal exam period
Due date: 04 Jun 2024 at 18:00
2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10
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: LO1 LO10 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2
Assignment Mid-term assessment
Written assessment
25% Week 06
Due date: 28 Mar 2024 at 23:59
Detail provided on Canvas page
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
Online task Weekly quizzes
Online quizzes
5% Weekly Variable - 30 to 60 minutes
Outcomes assessed: LO1 LO10 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2
hurdle task = hurdle task ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

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.

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.

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

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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 2023 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 2023. 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

WK Topic Learning activity Learning outcomes
Week 01 Study types Lecture and tutorial (3 hr) LO1 LO2
Week 02 Measures of frequency Lecture and tutorial (3 hr) LO2 LO3
Week 03 Measures of Association Lecture and tutorial (3 hr) LO1 LO2 LO3
Week 04 Confounding and Effect Modification Lecture and tutorial (3 hr) LO1 LO2 LO4
Week 05 Selection Bias Lecture and tutorial (3 hr) LO1 LO2 LO4
Week 06 Measurement Error Lecture and tutorial (3 hr) LO1 LO2 LO4
Week 07 Randomised Controlled Trials Lecture and tutorial (3 hr) LO3 LO4 LO5 LO6
Week 08 Critical Appraisal Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 09 Systematic Review and Meta-Analysis Lecture and tutorial (3 hr) LO8
Week 10 Infectious disease outbreaks Lecture and tutorial (3 hr) LO3 LO9
Week 11 Screening and Test Evaluation Lecture and tutorial (3 hr) LO3 LO7
Week 12 Causality and population health data Lecture and tutorial (3 hr) LO6 LO10
Week 13 Revision Tutorial (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10
Week 14 (STUVAC) Population Health Data Independent study (2 hr) LO10
Causality and Public Health Importance Independent study (3 hr) LO6

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 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.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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 2024, the in-class assessments (and associated on-going feedback to students) will be used again in 2024. 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.