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Created byJoe Galazka
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Outbreak Architect: Modeling Exponential Growth to Flatten the Curve

Grade 9Math5 days
In this math project, 9th-grade students act as public health strategists to model the spread of a viral outbreak using exponential functions. By constructing and analyzing $f(t) = a \cdot b^t$ models, students distinguish between linear and exponential growth while identifying the critical "Red Line" where healthcare capacity is exceeded. Through simulating real-world interventions like social distancing, learners apply mathematical transformations to "flatten the curve" and present their strategic findings in a professional portfolio.
Exponential GrowthMathematical ModelingFunction TransformationsPublic HealthFlatten The CurveData AnalysisHealthcare Capacity
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Inquiry Framework

Question Framework

Driving Question

The overarching question that guides the entire project.How can we, as public health strategists, use mathematical modeling to predict the spread of a virus and design community interventions that successfully flatten the exponential curve to protect our healthcare capacity?

Essential Questions

Supporting questions that break down major concepts.
  • How can mathematical models help us predict and control the spread of an infectious disease?
  • What distinguishes exponential growth from linear growth, and why is this distinction critical during a public health crisis?
  • How do variables like the 'initial number of cases' and the 'transmission rate' influence the shape and steepness of an exponential curve?
  • In what ways can community interventions (like social distancing or vaccination) be represented as transformations or changes to the base of an exponential function?
  • How do we determine when a mathematical model is 'flattening,' and what does that mean for a community's healthcare capacity?
  • What are the limitations of using a simple exponential model to represent real-world human behavior and biological spread?

Standards & Learning Goals

Learning Goals

By the end of this project, students will be able to:
  • Construct exponential growth functions ($f(t) = a \cdot b^t$) to model the spread of a virus based on varying initial infection rates and transmission factors.
  • Compare and contrast linear and exponential growth models to explain why exponential spread creates unique challenges for healthcare infrastructure.
  • Analyze the impact of parameter changes (e.g., reducing the growth factor 'b') to simulate public health interventions like social distancing and vaccination.
  • Interpret graphical data to identify the point at which healthcare capacity is exceeded and justify 'flattening the curve' strategies using mathematical evidence.
  • Evaluate the limitations of simple exponential models by identifying real-world variables (e.g., immunity, population density) that require more complex modeling approaches.

Common Core State Standards for Mathematics (High School)

CCSS.MATH.CONTENT.HSF.LE.A.1.C
Primary
Distinguish between situations that can be modeled with linear functions and with exponential functions. Recognize situations in which a quantity grows or decays by a constant percent rate per unit interval relative to another.Reason: This is the core mathematical distinction students must make when analyzing why outbreaks require different responses than linear growth problems.
CCSS.MATH.CONTENT.HSF.LE.A.2
Primary
Construct exponential functions, including arithmetic and geometric sequences, given a graph, a description of a relationship, or two input-output pairs.Reason: Students will build their own pandemic models from initial data sets provided in the project.
CCSS.MATH.CONTENT.HSF.BF.B.3
Secondary
Identify the effect on the graph of replacing $f(x)$ by $f(x) + k$, $k f(x)$, $f(kx)$, and $f(x + k)$ for specific values of $k$ (both positive and negative).Reason: Students will use transformations to represent how interventions (like social distancing) modify the base function and 'flatten' the curve.

Common Core Mathematical Practices

CCSS.MATH.PRACTICE.MP4
Primary
Model with mathematics. High school students can apply the mathematics they know to solve problems arising in everyday life, society, and the workplace.Reason: The entire project is centered on applying mathematical modeling to a critical societal issue (public health).

Next Generation Science Standards (NGSS)

NGSS.HS-LS2-1
Supporting
Use mathematical and/or computational representations to support explanations of factors that affect carrying capacity of ecosystems at different scales.Reason: While a math project, this standard supports the inquiry into healthcare capacity as a 'carrying capacity' for a human community during an outbreak.

Entry Events

Events that will be used to introduce the project to students

The Viral Saturation Point

Students enter a classroom transformed into a high-stakes 'Social Command Center.' They are shown the real-time analytics of a local 'viral' video or meme and asked to use exponential modeling to predict the exact hour it will reach 'saturation' (every person in the city having seen it), before the teacher reveals that a biological pathogen follows the exact same math—only with deadly consequences.
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Portfolio Activities

Portfolio Activities

These activities progressively build towards your learning goals, with each submission contributing to the student's final portfolio.
Activity 1

The Red Line: Finding the Breaking Point

Students graph their exponential model against a 'Healthcare Capacity Line.' They must determine the exact day the 'Red Line' (hospital capacity) is crossed. This activity introduces the concept of a 'Carrying Capacity' as a limit to the system, forcing students to see the human cost of the unchecked curve.

Steps

Here is some basic scaffolding to help students complete the activity.
1. Using graphing software or graph paper, plot the exponential function created in Activity 2.
2. Draw a horizontal line ($y = k$) representing the local hospital capacity provided in the scenario.
3. Calculate the intersection point to find the 'Day of Saturation'—the moment the medical system fails to support new patients.

Final Product

What students will submit as the final product of the activityA 'Crisis Threshold Graph' featuring the exponential curve, the horizontal capacity line, and a 'Crisis Point' annotation marking the day the community runs out of beds.

Alignment

How this activity aligns with the learning objectives & standardsAligns with CCSS.MATH.PRACTICE.MP4 (Model with mathematics) and NGSS.HS-LS2-1 (Carrying capacity). This activity forces students to interpret the horizontal line as a resource constraint (hospital beds).
Activity 2

Curve Crushers: Designing the Intervention

In this high-stakes simulation, students must 'flatten the curve.' They are given intervention cards (e.g., 'Mask Mandate' reduces $b$ by 15%, 'Strict Quarantine' reduces $b$ by 40%). Students will apply these changes to their original function to see if they can keep the curve below the 'Red Line' established in the previous activity.

Steps

Here is some basic scaffolding to help students complete the activity.
1. Select a combination of public health interventions and calculate the new 'Mitigated Growth Factor' ($b_{new}$).
2. Write the new 'Intervention Function' and graph it on the same axes as the original outbreak curve.
3. Describe the transformation: compare the steepness of the curves and calculate how many additional days of capacity were gained.

Final Product

What students will submit as the final product of the activityAn 'Intervention Impact Report' showing two overlaid graphs (Original vs. Mitigated) and a mathematical analysis of how the change in the 'b' value saved the community's healthcare system.

Alignment

How this activity aligns with the learning objectives & standardsAligns with CCSS.MATH.CONTENT.HSF.BF.B.3: Identify the effect on the graph of replacing $f(x)$ by $f(x) + k$, $k f(x)$, $f(kx)$, and $f(x + k)$. It specifically focuses on how changing the base (b) acts as a transformation that stretches or compresses the growth over time.
Activity 3

The Strategic Defense Portfolio: Briefing the Council

Students compile their findings into a final strategic portfolio. They must not only present their math but also critique it. They will identify why a simple $a \cdot b^t$ model eventually fails (e.g., people getting better/immune, finite population) and present their 'Flattened Curve' model to a mock 'City Council.'

Steps

Here is some basic scaffolding to help students complete the activity.
1. Compile all previous graphs and equations into a professional 'Public Health Briefing.'
2. Write a 'Strategic Summary' that uses the math to justify why specific community interventions were necessary.
3. Research and write a final reflection on 'The Logistic Reality'—explaining why exponential growth cannot continue forever in the real world (e.g., the concept of herd immunity).

Final Product

What students will submit as the final product of the activityThe 'Outbreak Architect Portfolio,' containing the model, the intervention data, the capacity analysis, and a 'Limitations Brief' explaining the difference between theoretical exponential growth and real-world logistic growth.

Alignment

How this activity aligns with the learning objectives & standardsAligns with CCSS.MATH.PRACTICE.MP4 and provides the final evaluation for the learning goal of identifying real-world limitations of simple models. It synthesizes all previous standards into a final communication piece.
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Rubric & Reflection

Portfolio Rubric

Grading criteria for assessing the overall project portfolio

Outbreak Architect: Exponential Modeling & Public Health Rubric

Category 1

Modeling Accuracy & Function Theory

Focuses on the core mathematical ability to build and identify exponential functions as outlined in CCSS.MATH.CONTENT.HSF.LE.A.1.C and HSF.LE.A.2.
Criterion 1

Mathematical Modeling & Construction

Ability to construct and distinguish exponential growth functions ($f(t) = a \cdot b^t$) from linear models based on provided pandemic data.

Exemplary
4 Points

Constructs a highly accurate exponential model with precise identification of initial value (a) and growth factor (b). Provides a sophisticated mathematical explanation of why exponential growth, rather than linear, is required for this context, citing specific rate-of-change characteristics.

Proficient
3 Points

Constructs an accurate exponential function that models the provided data. Correct identifies 'a' and 'b' and provides a clear explanation of the difference between linear and exponential growth in the context of viral spread.

Developing
2 Points

Constructs an exponential function with minor errors in the growth factor or initial value. Provides a basic explanation of exponential growth but may struggle to clearly distinguish it from linear growth mathematically.

Beginning
1 Points

Attempts to construct a function but uses an incorrect format (e.g., linear) or fails to identify 'a' and 'b' correctly. Demonstrates significant misconceptions about the nature of exponential growth.

Category 2

Data Interpretation & Carrying Capacity

Evaluates the student's ability to model with mathematics (MP4) and understand carrying capacity (NGSS.HS-LS2-1).
Criterion 1

Constraint Analysis & Graphing

The ability to graph functions against a resource constraint (hospital capacity) and interpret the real-world implications of the intersection point.

Exemplary
4 Points

Graphs the 'Red Line' and exponential curve with professional precision. Identifies the 'Day of Saturation' accurately and provides a deep analysis of the human and systemic consequences of exceeding this carrying capacity.

Proficient
3 Points

Successfully graphs the function and the capacity line. Correct calculates the intersection point and explains what it represents for the community's healthcare system.

Developing
2 Points

Graphs both elements but with scaling or plotting errors. Identifies an intersection point but provides a limited explanation of its significance regarding hospital capacity.

Beginning
1 Points

Fails to correctly graph the capacity line or the curve. Cannot identify or explain the significance of the intersection point where the model exceeds capacity.

Category 3

Intervention Analysis & Curve Flattening

Aligned with CCSS.MATH.CONTENT.HSF.BF.B.3, focusing on how changes to the function parameters affect the output.
Criterion 1

Parameter Manipulation & Transformation

Ability to apply transformations to the exponential function by modifying the growth factor (b) and analyzing the resulting 'flattening' of the curve.

Exemplary
4 Points

Calculates complex mitigated growth factors with perfect accuracy. Demonstrates a sophisticated understanding of how changing the base (b) transforms the curve. Provides a detailed comparative analysis of 'days gained' and lives saved.

Proficient
3 Points

Correctly calculates a new growth factor based on intervention cards. Accurately graphs the new 'flattened' curve and describes the transformation in terms of the function's steepness and growth rate.

Developing
2 Points

Applies an intervention to the growth factor but makes calculation errors. The resulting graph shows a flatter curve, but the student struggles to explain the mathematical relationship between the change in 'b' and the transformation.

Beginning
1 Points

Struggles to modify the growth factor or graph the new function. Shows little understanding of how interventions translate into mathematical transformations of the base function.

Category 4

Strategic Synthesis & Model Critique

Assesses the student's ability to communicate complex mathematical ideas and evaluate the validity of their models in a real-world context.
Criterion 1

Communication & Critical Evaluation

Synthesis of findings into a professional briefing, including a critical evaluation of the model's real-world limitations (exponential vs. logistic growth).

Exemplary
4 Points

Presents a professional-grade portfolio with compelling mathematical justifications. Provides a profound reflection on logistic growth, herd immunity, and the ethical implications of modeling, showing mastery of model limitations.

Proficient
3 Points

Compiles a clear and organized briefing that uses mathematical evidence to justify interventions. Correct identifies at least two real-world factors (like immunity or population size) that limit simple exponential models.

Developing
2 Points

The portfolio is organized but lacks strong mathematical justification for the interventions. Mentions limitations of the model but provides a shallow or purely descriptive explanation without scientific/mathematical depth.

Beginning
1 Points

The final portfolio is incomplete or disorganized. Fails to address the limitations of the model or provides a justification for interventions that is not supported by the mathematical data.

Reflection Prompts

End-of-project reflection questions to get students to think about their learning
Question 1

How confident do you feel in your ability to translate a real-world action (like a public health policy) into a mathematical change within an exponential function?

Scale
Required
Question 2

Looking back at your 'Strategic Defense Portfolio,' which mathematical concept provided the most 'eye-opening' moment regarding the urgency of a pandemic response?

Multiple choice
Required
Options
The speed at which the 'Red Line' of hospital capacity is reached compared to linear growth.
How a small decrease in the transmission rate (b) leads to a massive difference in cases over time.
The fact that exponential growth eventually fails to account for things like immunity (The Logistic Reality).
The way transformations on a graph can represent complex human behaviors.
Question 3

How does the 'Healthcare Capacity Line' change the way we interpret an exponential graph? Why is it mathematically and ethically different to look at a curve with a 'Red Line' versus a curve without one?

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Question 4

A simple exponential model assumes the virus has an infinite number of people to infect. Based on your 'Limitations Brief,' how does adding real-world variables like 'herd immunity' or 'population density' change the way you view the reliability of mathematical models in the news?

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