Outline

Overview

This unit of study is only available to students approved to be participating in the NYU Sydney Program.

Unit details and rules

Academic unit	Public Health
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Yuri Ogura, yuri.ogura@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Assignment	Final Assignment Multiple choice and short answer questions covering all course topics	20%	Formal exam period Due date: 11 Jun 2025 at 09:00	6 pages
Outcomes assessed:
Small continuous assessment	Weekly quiz Each quiz comprises questions on the essential pre-reading	10%	Multiple weeks	ongoing
Outcomes assessed:
Participation	Class Participation Students gain participation marks through active engagement in class	10%	Ongoing	ongoing
Outcomes assessed:
Assignment	Annotated Bibliography Work in groups to prepare an annotated bibliography	5%	Week 05 Due date: 26 Mar 2025 at 15:00	1 page
Outcomes assessed:
Assignment	Homework assignment 1 Demonstrate concepts and apply knowledge to epidemiological study or papers	15%	Week 06 Due date: 02 Apr 2025 at 23:59	3-4 pages
Outcomes assessed:
Assignment	Homework Assignment 2 Demonstrate concepts and apply knowledge to epidemiological study or papers	15%	Week 10 Due date: 07 May 2025 at 23:59	3-4 pages
Outcomes assessed:
Assignment	Homework Assignment 3 Demonstrate concepts and apply knowledge to epidemiological study or papers	15%	Week 12 Due date: 21 May 2025 at 23:59	3-4 pages
Outcomes assessed:
Assignment	Facts Sheet Presentation 10 minute presentation on fact sheet which summarises key information about a disease or health condition	10%	Week 13 Due date: 28 May 2025 at 15:00	10 minutes
Outcomes assessed:
= group assignment ? = AI allowed ?

Assessment summary

Weekly Quizzes: Each quiz comprises questions on the essential pre-reading to be completed before attending class
Class Participation: Students gain participation points through active engagement in interactive lectures, class discussions, in-class group exercises, and a discussion forum
Disease Fact Sheet Group Assignment and Presentation: Students will work in groups to prepare an annotated bibliography, an oral presentation, and a final fact sheet summarising key information about a disease or health condition.
Homework Assignments (x3): Allows students to demonstrate your understanding of specific epidemiological concepts and your ability to apply this knowledge to specific epidemiological studies and/or published papers.
Final Exam: A multiple choice and short answer exam covering topics presented in Sessions 1 – 13.

Assessment criteria

For this course your total numerical score, calculated from the components listed above, correspond to the following letter grades:

A	90 to 100
A-	86 to < 90
B+	82 to < 86
B	72 to < 82
B-	68 to < 72
C+	64 to < 68
C	54 to <64
C-	50 to < 54
D+	45 to < 50
D	40 to < 45
F	0 to < 40

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.

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	The origins of modern epidemiology; Using epidemiology in health policy: Kingdon framework and the health policy triangle; The role of the epidemiologist; Outbreak investigation	Block teaching (3.5 hr)
Week 02	Outbreak investigation	Block teaching (3.5 hr)
Week 03	Introduction to the hierarchy of evidence ; Study designs for descriptive epidemiology; Data sources for descriptive epidemiology	Block teaching (3.5 hr)
Week 04	Measurement of disease frequency; Disease prevalence; Disease incidence; Global indicators of disease	Block teaching (3.5 hr)
Week 05	Measurement of association; Odds ratio; Risk ratio; 95% confidence internals; p values	Block teaching (3.5 hr)
Week 06	Analytical study designs Part I: case control and cohort studies	Block teaching (3.5 hr)
Week 07	Analytical study design Part II: non- randomised and randomised controlled trials; Research question formation; Test sensitivity; Test specificity	Block teaching (3.5 hr)
Week 08	Internal and external validity; Chance ; Random error; Selection bias; Measurement bias; Annotated Bibliography	Block teaching (3.5 hr)
Week 09	Confounding; Ethics	Block teaching (3.5 hr)
Week 10	Critical appraisal; Bradford Hill’s viewpoints	Block teaching (3.5 hr)
Week 11	Causation theory; Synthesis of evidence; Systematic reviews; Meta analysis; Pooled analysis	Block teaching (3.5 hr)
Week 12	Design and evaluation of screening programs ; Positive predictive value; Negative predictive value	Block teaching (3.5 hr)
Week 13	Group presentations; Revision of selected topics	Block teaching (3.5 hr)

Attendance and class requirements

Attendance: Studying at NYU Sydney is an academically intensive and immersive experience, in which students from a wide range of backgrounds exchange ideas in discussion-based seminars. Learning in such an environment depends on the active participation of all students. And since classes typically meet once or twice a week, even a single absence can cause a student to miss a significant portion of a course. To ensure the integrity of this academic experience, class attendance at NYU Sydney is expected promptly when class begins. Attendance will be checked at each class meeting.

Unexcused absences may be penalized with a two percent deduction from the student’s final course grade for every week's worth of classes missed, and may negatively affect your class participation grade. Four unexcused absences in one course may lead to a Fail in that course. Being more than 15 minutes late counts as an unexcused absence.

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

G Webb P, Bain C and Page A. Essential Epidemiology 4th Edition, 2019. Cambridge University Press

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. Understand and describe the evolution and current role of epidemiology as an approach to assessing public health problems over time and across populations
LO2. Describe epidemiological approaches to defining and measuring health problems to understand the distribution of health and disease in human populations worldwide and the persistence of health inequities across regions and groups
LO3. Understand and describe key principles of how epidemiologic studies are designed and analysed
LO4. Understand and describe the basic concepts of measurement of test performance and be able to apply these concepts of testing and screening
LO5. Recognise epidemiological criteria needed to establish cause and effect relationships
LO6. Recognise key ethical issues in the conduct of epidemiological and other scientific investigations in communities and populations
LO7. Conduct library research to find information on diseases and other health conditions
LO8. Critically read and understand health information in different formats and contexts
LO9. Apply epidemiological knowledge and skills to Australian, US and global public health problems

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.

Updates to assessment dates to reflect semester 1, 2025

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

NYUS3503: Epidemiology for Global Health

Semester 1, 2025 [Normal day] - 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