7312MED EPIDEMIOLOGY: PINCIPLES AND PRACTICES
(Trimester 1)
School of Medicine & Dentistry, Griffith University
ALTERNATIVE ASSIGNMENT ONE
INSTRUCTIONS:
THIS ASSIGNMENT IS WORTH 20% OF THE OVERALL ASSESSMENT OF THIS COURSE.
IT IS INTENDED TO BE AN INDIVIDUAL EXERCISE AND, AS SUCH, YOU ARE REQUIRED
TO WORK INDEPENDENTLY WITHOUT RECEIVING HELP FROM ANYONE ELSE OR
COLLABORATING WITH YOUR FELLOW STUDENTS.
NUMBER ALL THE QUESTIONS CLEARLY (such as Q1-a, Q3-b…). THE MARKS
ALLOCATED TO EACH QUESTION IS SHOWN AFTER THE INTRODUCTORY LINES OF
EACH QUESTION. USE YOUR FULL NAME AS THE FILE NAME WHEN SUBMITTING THE
ASSIGNMENT. DO NOT ATTACH THE STANDARD ASSIGNMENT COVER SHEET TO
THIS ASSIGNMENT.
PLEASE USE MICROSOFT WORD DOCUMENT TO TYPE YOUR ANSWERS, USING A
MINIMUM FONT SIZE OF 11 AND 1.5 LINE SPACING. DO NOT SUBMIT A PDF FILE. YOU
ARE REQUIRED TO MAKE UP THE CALCULATIONS (INCLUDING INTERPRETATIONS)
AND PROVIDE BRIEF ANSWERS TO THE QUESTIONS IN THIS ASSIGNMENT. A TOTAL
OF LESS THAN 1,500 WORDS (EXCLUDING EQUATIONS & TABLES) WILL BE
SUFFICIENT TO ANSWER ALL QUESTIONS IN THIS ASSIGNMENT.
THE ASSIGNMENT IS DUE BY 5 pm Monday the 15th of May 2023. Please submit
your completed assignment to the convenor A/Prof Patricia Lee
([email protected])
PLEASE REMEMBER TO PAY ATTENTION TO YOUR NUMERATORS AND
DENOMINATORS AND SHOW WORKINGS IN YOUR ANSWERS. KEEP ONE
DECIMAL PLACE IN YOUR FINAL ANSWERS OF CALCULATIONS.
ASSIGNMENT 1 Measures of Disease Frequency and Association, Types
of Epi Study Design (Total: 40 Marks)
Question 1 (15 marks)
Diabetes is one of the fastest growing chronic diseases in Australia. The following
table shows the total new cases of diabetes from January 2010 to December 2012 in
Queensland and Northern Territory and the population data of the two states from
Census survey in 2011.
Table 1 Numbers of type II diabetics and total populations by age in Queensland
and Northern Territory

(a) Which measure of disease frequency (prevalence, cumulative incidence, incidence
density or estimated incidence rate) is most suitable in this example? Provide two
reasons to justify your answer. (1.5 marks)
(b) Calculate the overall disease occurrence (using a crude measure which was
nominated in the previous question) of type II diabetes in each of the two states.
Please include a population multiplier of per 10,000 in your calculations and
identify which state had a higher crude rate of type II diabetes. (2.5 marks)
(c) What were the risks (ie using a measure of disease frequency) of developing type
II diabetes in different age groups in each of the two states? How does the risk of
developing diabetes vary by age in each state? (Use an appropriate measure of
association to quantify the variation). Based on your results, discuss whether or
not age is a risk factor of type II diabetes in the two states. (4 marks)
(d) Compare the age structures in the populations of Queensland and Northern
Territory (calculate the percentage of each age group). Is the comparison of crude
occurrence valid in consideration of the population structures in the two states?
Why or Why not? (3 marks)
(e) Use Australia’s population as the standard population to compute the direct
standardised rates (age adjusted rates) of type II diabetes in Queensland and in
Northern Territory. Compare the results of crude and standardised rates between
the two states and interpret your findings. (4 marks)
Question 2 (8 marks)
An epidemiologist investigated a Covid-19 cluster at an aged care residence. The
following figure presents the findings of the investigation. Assume that the total
observation period was eight weeks. Please use per 100 people as the population
multiplier for this question.
Table 2 Investigation of Covid-19 cluster at an aged care facility

(a) What is the point prevalence at the beginning of Week 5? (2 marks)
(b) What is the cumulative incidence (incidence proportion) from the beginning of
Week 5 to the end of Week 8? (2 marks)
(c) What is the incidence rate (incidence density) of Covid-19 during the 8-week
investigation? (2 marks)
(d) What is the risk of dying (mortality) due to Covid-19 from the beginning of Week
5 to the end of Week 8? (2 marks)
Question 3 (6 marks)
A recent study assessed whether or not having hepatitis C virus (HCV) infection
would increase the risk of B-cell non-Hodgkin lymphomas (B-NHL). The patients
newly diagnosed with B-NHL were identified in the hematology department wards of
10 cities in Country A. The control group consisted of patients admitted to other
departments of the same hospitals. The table below presents the numbers of cases
and controls as well as the numbers of HCV tests results by age.
Table 3 Numbers of B-NHL outcome status and HCV result by age

(a) What was the actual study design? Under similar research conditions, which type
of study design would be most feasible? (provide reasoning for your choice) (2
marks)
(b) Calculate the appropriate measure to determine the strength of association
between HCV and B-NHL regardless of the effect of age. Interpret your result briefly.
(HINT: draw a 2×2 table according to the participants’ outcome and exposure status)
(2 marks)
(c) What percentage of B-NHL among patients with HCV positives could have been
potentially prevented if they were not HCV positives? What is this measure called?
Calculate the measure and explain your result briefly. (2 marks)
Question 4 (11 marks)
Search data of “Mortality and Global Health Estimates” (using data in 2016, except
life expectancy and healthy life expectancy data) for 3 selected countries:
Australia, Brazil and Kenya from WHO’s Global Health Observatory website WHO’s
Global Health Observatory website (Link:
https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates) and
complete the following table (Table 4) (Items 4-8, excluding the shaded parts) (3
marks). Compare the population health data among the three selected countries and
answer Question 4 (a)-(c) (8 marks).
Table 4 WHO health statistical profiles for Australia, Brazil and Kenya

(a) Compare the population and crude mortality data (Items 1-3) of the three
selected countries, and summarise your comparison results briefly (Word limit:
150 words). Considering the population proportions presented in the table, is
crude mortality rate a useful measure for comparing the overall public health
status among the three countries? Why or why not? (Word limit: 200 words). (3
marks)
(b) In comparison of the life expectancy data between the selected countries (Items
7-8), why do the total years of life expectancy estimated at birth differ from the
lengths of life expectancy estimated at age 60? Also, why are the lengths of
healthy life expectancy at birth not the same as the lengths of life expectancy at
birth? (Word limit: 200 words). (2 marks)
(c) According to the completed Table 4, compare the population health data (Items 3-
8) and conclude the general levels of public health among the three countries
(Word limit: 200 words). (3 marks)