Designing a Disease Investigation
In 2021, the Doherty Institute published a 64-page modelling report that convinced the Australian government to set a 70% vaccination target, connecting pathogen biology, transmission data, vaccine efficacy, and population health into a single integrated picture.
Printable Worksheets
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What makes a scientific question 'investigable'? Write one example.
Why is it important to identify controlled variables in an experiment?
● Know
- Identify investigable questions and write testable hypotheses about disease
● Understand
- Distinguish independent, dependent, and controlled variables and explain what makes a test fair and valid
● Can do
- Design a controlled disease investigation in the style of John Snow's epidemiology
A concept map is only as good as the connections it makes. In the Disease unit, the central concept is the chain of infection: pathogen → reservoir → portal of exit → transmission → portal of entry → susceptible host. Every topic in this unit modifies one or more links in that chain. Vaccination makes the host less susceptible. Handwashing blocks transmission. Antibiotics kill the pathogen. Public health addresses reservoirs.
But the chain does not exist in isolation. Antibiotic resistance connects to evolution by natural selection. Social determinants connect to epidemiology and health equity. Global travel connects to pandemic potential. A student who sees these patterns can answer novel questions by reasoning from first principles rather than searching for a memorised fact.
Asked to explain why tuberculosis is hard to eliminate, a synthesising student connects multiple concepts: TB has a long latency period (pathogen behaviour), spreads through airborne droplets (transmission), primarily affects immunocompromised people (host susceptibility), and requires a six-month antibiotic course (treatment adherence). No single fact explains it; the pattern does.
The Australian Academy of Science promotes systems thinking in science education, arguing that students who understand connections between concepts are better prepared for complex careers in medicine, research, and public health.
The herd immunity threshold is a mathematical certainty, not a political choice. For any infectious disease, the threshold is approximately 1 minus 1 divided by R₀. Diseases with high R₀ need higher coverage because each infected person spreads the disease to many others. Measles, with an R₀ around 15, needs about 93% coverage. Influenza, with an R₀ near 2, needs only about 50%. COVID-19 original strain had an R₀ around 3, requiring roughly 67% coverage; the Delta variant pushed that above 80%.
These numbers matter for public policy. When coverage drops below the threshold, outbreaks become mathematically inevitable. The size of the outbreak depends on how far below threshold coverage falls and how quickly it can be restored. This is why public health officials panic over small dips in childhood vaccination rates.
A new infectious disease has R₀ = 4. Threshold = 1 - 1/4 = 75%. If 70% of the population is immune, the disease will still spread because 70% is below threshold. To stop sustained transmission, coverage must rise to at least 75%.
NCIRS publishes quarterly coverage data for every Australian postcode, allowing health departments to target outreach to areas where coverage has slipped below disease-specific thresholds.
A depth study is your chance to demonstrate scientific thinking at its best. The difference between a good study and an excellent one often comes down to how well you handle limitations. Every study has flaws: maybe your sample size was small, maybe you could not control room temperature, maybe your measuring tool had limited precision. Acknowledging these limitations honestly does not weaken your study, it strengthens it, because it shows you understand how science really works.
Strong conclusions go beyond yes or no. They evaluate how strongly the evidence supports the hypothesis. They suggest improvements: what would you do differently with more time, better equipment, or a larger sample? They connect back to the scientific concepts that motivated the study in the first place. Science is not about proving you are right; it is about building reliable knowledge through evidence.
A student concludes: My results support the hypothesis that antibacterial soap reduces bacterial growth, but my sample size was only three trials per condition. With more replicates, I would have greater confidence. I would also test more soap brands to see if the effect is general. This conclusion is strong because it is honest, specific, and forward-looking.
The CSIRO Double Helix magazine publishes student depth studies with a special emphasis on honest reporting of limitations, teaching young scientists that failure and uncertainty are normal parts of the scientific process.
Wrong: "A depth study is just a long essay about a disease." No, a depth study is an investigation. It requires you to ask a question, gather evidence, analyse data, and draw conclusions. It is active science, not just research.
Right: A depth study is an active scientific investigation that requires asking a question, gathering evidence, analysing data, and drawing conclusions. It is not just a research essay.
Wrong: "The different topics in this unit have no connection to each other." No, they are deeply connected. Pathogens cause disease, which the immune system fights, which vaccines train, which antibiotics treat, which resistance limits, which public health prevents. Every topic links to others.
Right: All topics in this unit are deeply connected: pathogens cause disease, which the immune system fights, which vaccines train, which antibiotics treat, which resistance limits, which public health prevents.
Wrong: "Once you memorise facts about disease, you understand it." No, true understanding means being able to explain connections, apply concepts to new situations, and evaluate evidence. Facts are tools; understanding is the ability to use them.
Right: True understanding means being able to explain connections between concepts, apply them to new situations, and evaluate evidence. Facts alone are not enough without the ability to use them.
Australian Scientists Fighting Disease
Professor Fiona Stanley (AC): An Australian epidemiologist who founded the Telethon Kids Institute in Perth. Her research on birth defects, Indigenous health, and population health methods transformed Australian public health. She championed the use of population data to guide health policy.
Professor Ian Frazer: Co-developer of the HPV vaccine at the University of Queensland. His work has prevented countless cases of cervical cancer worldwide and put Australia on track to eliminate cervical cancer entirely.
Modern Australian research: Today, Australian scientists at WEHI, the Doherty Institute, CSIRO, and universities across the country continue to fight disease. During COVID-19, Australian researchers contributed to vaccine development, genomic surveillance, and long COVID research. Aboriginal and Torres Strait Islander researchers are increasingly leading health research that addresses community priorities with cultural authority.
✍ Copy Into Your Books
▾Unit Connections
- Pathogen -> Transmission -> Defence -> Treatment
- Infectious vs non-infectious disease
- Local, national, and global perspectives
Key Formulas
- Herd immunity threshold ≈ 1 - 1/R0
- Incidence rate = (new cases/population) × multiplier
- Case fatality rate = (deaths/cases) × 100%
Depth Study Steps
- Choose topic -> Formulate question -> Research -> Hypothesis -> Method -> Data collection -> Analysis -> Conclusions -> Communication
Concept Connections
Depth Study Planning
At the start of this lesson, you thought about how every great discovery in disease science, from germ theory to vaccines to cancer treatments, started with one well-designed investigation question.
Now that you've worked through the scientific method, can you explain what makes a question genuinely investigable, and why controlling variables is so important for trusting results? How would you apply this to a disease topic that interests you?
Q1. Explain what makes a scientific question 'investigable'. Rewrite the vague question "Does exercise affect health?" as a properly investigable question. 2 marks
Q2. A student investigates whether soap reduces bacteria on hands. Identify the independent variable, the dependent variable, and two controlled variables for this investigation. 3 marks
Q3. Explain the difference between validity and reliability in an investigation, and describe one ethical consideration a student should think about when designing a disease investigation. 3 marks
Revisit Your Thinking
Go back to your Think First answer. Has your understanding changed?
- How has your understanding of disease and health developed across this entire unit?
- What connections between concepts do you find most powerful or surprising?
Model answers (click to reveal)
Answers
▾MCQ 1
B An investigable question is specific enough to be answered by collecting data. Option B compares two measurable handwashing times against a measurable result (colony count). The others are too vague or are opinion or 'why' questions that cannot be tested directly.
MCQ 2
A The independent variable is the one factor the investigator deliberately changes. The dependent variable is measured, and controlled variables are kept the same.
MCQ 3
C Keeping controlled variables the same means any change in the dependent variable can be attributed to the independent variable alone. This keeps the test fair and the results valid.
MCQ 4
D Repeating measurements and averaging reduces the effect of random error, improving reliability. It does not change the variables or the hypothesis.
MCQ 5
B An investigation is valid when it actually tests what it set out to measure, with only the independent variable changed. Cost, speed, or getting a hoped-for result do not make an investigation valid.
Short Answer 1
Model answer: An investigable question is one that is specific, testable by collecting data through observation or measurement, and linked to scientific concepts. "Does exercise affect health?" is too vague because exercise and health are not defined or measurable. A better, investigable version is: "Does 30 minutes of moderate daily walking for four weeks reduce the resting heart rate of Year 9 students?" This is specific (30 minutes of walking), testable (measure resting heart rate before and after), and linked to cardiovascular health.
Short Answer 2
Model answer: Independent variable: whether soap is used when washing hands (for example, soap and water versus water only). Dependent variable: the number of bacterial colonies grown from hand swabs (the amount of bacteria measured). Controlled variables (any two): the same washing time, the same water temperature, the same area of the hand swabbed, the same growth medium, and the same incubation conditions. Keeping these the same makes the test fair so that any difference in bacteria is due to the soap.
Short Answer 3
Model answer: Validity is whether an investigation actually tests and measures what it set out to measure, which requires changing only the independent variable while controlling everything else (a fair test). Reliability is whether the results are consistent and repeatable, which is improved by repeating measurements and averaging. An investigation can be reliable (consistent) but still invalid if it measures the wrong thing. Ethical consideration (any one): if testing involves people, you must gain informed consent, protect privacy and keep data confidential, avoid causing harm or discomfort, and treat any living organisms (such as bacterial cultures) safely and dispose of them properly.