3
Explore

Modeling an Outbreak

Duration
45 minutes
Type
Explore / Explain
Standards
MS-LS2-1, 8.EE.A.1

Learning Objectives

Students will be able to:

The Power of 2

Challenge: One person gets sick and infects 2 others. Each of those 2 infects 2 more. How many people are infected after 10 rounds?

Round New Cases Calculation
01Start
1221
2422
3823
53225
101,024210

From just ONE person, over a thousand can be infected! This is exponential growth.

Introducing R0 (R-naught)

R0 = The average number of people infected by one sick person in a population where everyone can get sick.

What R0 Tells Us

←— Dies Out —|— Grows —→
R0 < 1       R0 = 1       R0 > 1
R0 < 1
Outbreak shrinks
(each case makes <1 new case)
R0 = 1
Stable
(each case makes exactly 1)
R0 > 1
Outbreak grows
(each case makes >1 new case)

R0 of Real Diseases

Disease R0 How Contagious?
Measles 12-18 Extremely contagious
Chickenpox 10-12 Very contagious
COVID-19 (Omicron) 8-15 Very contagious
COVID-19 (Original) 2-3 Moderate
Common cold 2-3 Moderate
Seasonal flu 1.3-1.5 Lower
Ebola 1.5-2.5 Moderate (but contact spread)

The Math of Exponential Growth

New cases after n generations = R0n

Example Comparison:

Flu (R0 = 1.4), 5 generations:

1.45 = 5.4 cases

Measles (R0 = 15), 5 generations:

155 = 759,375 cases!

This is why measles spreads so much faster than flu!

Activity: Calculate the Spread

Calculate new cases after 5 generations for each disease:

Disease R0 Calculation After 5 Generations
Disease A 1.5 1.55 ~7.6 cases
Disease B 2 25 32 cases
Disease C 3 35 243 cases
Disease D 5 55 3,125 cases

Good News: We Can Change R!

R0 isn't fixed—interventions reduce the effective R:

Vaccination

Fewer susceptible people = fewer potential infections

Masks

Reduce particles released and inhaled

Ventilation

Lower concentration = lower transmission probability

Isolation

Sick people don't spread if they stay home

If we can get R below 1, outbreaks shrink instead of grow!

Key Takeaway

R0 tells us how fast a disease can spread. When R0 > 1, cases multiply exponentially. Small differences in R0 lead to huge differences in outbreak size. The good news: we can use interventions to reduce effective R below 1 and stop outbreaks.

← Lesson 2 Lesson 4: The Math of Epidemics →