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Population Doubling Time Formula

Calculate how long it takes a population to double using t_d = ln(2)/r.
Learn the doubling time formula with worked examples.

The Formula

t_d = ln(2) / r β‰ˆ 0.693 / r

The population doubling time formula calculates how long it takes for a population to double in size, given a constant growth rate. It applies to bacteria, animal populations, human demographics, and even cell cultures in the lab.

The formula is derived from the exponential growth equation N(t) = Nβ‚€ Γ— e^(rt). Setting N(t) = 2Nβ‚€ and solving for t gives the doubling time.

This is sometimes called the "Rule of 70" in demography. If the growth rate is expressed as a percentage, doubling time β‰ˆ 70 / (growth rate in %). For example, a population growing at 2% per year doubles in about 35 years.

Variables

SymbolMeaningUnit
t_dDoubling timeSame unit as the growth rate's time base (hours, days, years)
ln(2)Natural logarithm of 2, approximately 0.693β€”
rGrowth rate (as a decimal, not a percentage)per time unit

Example 1

E. coli bacteria divide every 20 minutes under optimal conditions. What is the growth rate, and does the formula confirm the 20-minute doubling time?

If the doubling time is 20 minutes, find r: r = ln(2) / t_d = 0.693 / 20

r = 0.0347 per minute

Verify: t_d = 0.693 / 0.0347 = 20 minutes βœ“

The growth rate is 0.0347 per minute, confirming the 20-minute doubling time

Example 2

A country's population grows at 1.4% per year. How long until the population doubles?

Convert the percentage to a decimal: r = 1.4 / 100 = 0.014 per year

Apply the formula: t_d = 0.693 / 0.014

t_d β‰ˆ 49.5 years β€” the population will double in about 50 years

Example 3

A cell culture grows at a rate of 0.05 per hour. How long until it doubles?

Apply directly: t_d = 0.693 / 0.05

t_d = 13.86 hours β€” the culture doubles roughly every 14 hours

When to Use It

  • Predicting bacterial colony growth in microbiology
  • Demographic forecasting for human populations
  • Cell culture planning in biomedical research
  • Ecology β€” estimating wildlife population recovery timelines
  • Public health β€” modeling disease spread during outbreaks

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