1.
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
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Queensland
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Northern Territory
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Australian
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Age group
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Population
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Total new
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Population
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Total new
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population in
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in 2011
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cases in
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in 2011
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cases in
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2011
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2010-2012
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2010-2012
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0-49
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3,091,347
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5008
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181,145
|
798
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15,196,057
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50-64
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805,673
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20206
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37,306
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3237
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4,056,056
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65+
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579,758
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33342
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12,841
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2843
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3,087,911
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- Which measure of disease frequency (prevalence, cumulative incidence, incidence density or estimated incidence rate) is most suitable in this example? Provide reasoning to justify your answer.
- Calculate the overall crude measures of disease frequency (use the measure nominated in the previous question) of type II diabetics for both states and identify which state had the higher crude rate of type II diabetes.
- Calculate the age-specific rates (using the same measure of disease frequency as in Q1-(b)) in the two states (3 marks). How does the risk of developing diabetes vary by age in each of the two states? (Calculate the appropriate measure to quantify the variation). Based on your results, is age a risk factor for type II diabetes in both states? (2 marks) (Hint: measures of associationcan be used to quantify the variation by age)
- Use Australia’s population as the standard population to compute the direct standardised occurrences (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.
2.
A study was conducted to assess the effect of hepatitis C virus (HCV) infection on the development of B-cell non-Hodgkin lymphomas (B-NHL). A total of 480 newly diagnosed B-NHL patients were recruited in hematology department wards of 10 hospitals in City A. A comparison group consisted of 420 non B-NHL patients admitted to other departments of the same hospitals. The study found that 80 of the B-NHL patients and 25 of the non B-NHL patients were identified with HCV positives (having HCV infection).
- What is the actual study design? Under similar research conditions, which type of study design is most feasible? (provide reasoning for your choice)
- Draw up a 2 x2 table (including the total counts of different outcome and exposure groups) and calculate the appropriate measure of association between HCV and B -NHL. Interpret your result briefly.
- What percentage of B-NHL among HCV positives could have been potentially prevented if they were HCV negatives? What is this measure called? Calculate the measure and explain your result briefly.
3.
Classify each of the following descriptions of epidemiological studies according to study type. In your answer nominate one of the analytic epidemiological study types (listed below) and also provide 2 reasons for your choice of each study type.
List of analytic study designs:
Intervention/experimental study design, prospective cohort study, retrospective cohort study, nested-case control study, case-control study, cross-sectional study and ecological study
- A study investigated the impact of smoking and socioeconomic status (SES) on the risk of primary Sjögren’s Syndrome (pSS). Participants in a large population-based health survey (completed in 1991) who were subsequently diagnosed with pSS were identified through data linkage with the Swedish Sjögren’s Syndrome Register in 2002. A matched group without pSS were selected from the same survey data. Participants’ demographic data (including SES) and smoking status were collected at the time of the health survey.
- A study was conducted among pregnant women who attended one large healthcare centre during their pregnancy. Interviews were carried out with each woman participating in the study. The study assessed the relationship between the ethnic background of the women and their intention to breastfeed their babies.
4.
Table 2 below presents population data extracted from Australian Department of Health’s Coronavirus (Covid-19) surveillance (Source: https://www.health.gov.au/news/health-alerts/novel-coronavirus-2019-ncov-health-alert/coronavirus-covid-19-current-situation-and-case-numbers#at-a-glance). Use the summary statistics in Appendix 1 (Covid-19 at a glance on 15 May) and Appendix 2 (Covid-19 at a glance on 15 November) to complete the table and answer the following questions.
Table 2 Covid-19 surveillance data in Australia and selected states
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Australia
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Victoria
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New South Wales
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Total Population on the 1st of
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25,649,985
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6,689,377
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8,157,735
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January 2020
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Total accumulated Covid-19
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cases up to 15/05/2020
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Total accumulated Covid-19
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deaths up to 15/05/2020
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*Incidence (per 105) of Covid-19
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from 1 January to 15 May
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*Mortality (per 105) of Covid-19
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from 1 January to 15 May
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Total accumulated Covid-19
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cases up to 15/11/2020
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Total accumulated Covid-19
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deaths up to 15/11/2020
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*Incidence (per 105) of Covid-19
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from 1 January to 15 November
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*Mortality (per 105) of Covid-19
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from 1 January to 15 November
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Note: * working of calculation is required.
- Compare the incidence and mortality rates of Covid-19 up to the 15thof November between Victoria and New South Wales. Calculate the measures of association to show the risks of Covid-19 incidence and mortality between the two states and interpret your results in brief.
- Compare the case-fatality ratios between Victoria and New South Wales from the 1stof January to the 15th of May (during the first wave of Covid-19). Calculate the measure of association to show the risk of case-fatality between the two states and interpret your result.
- Calculate the measure of association to show the risk of case-fatality between Victoria andNew South Wales from the 1st of January to the 15th of November (including the first and the second waves of Covid-19). How has the measure of association changed from Q4-(b) to Q-4(c)? Explain your results briefly.
