When Does a Disease Become an Outbreak?

By Dr. Jay K. Varma
Physician, Epidemiologist, and Public Health Expert

🔍 Defining an Outbreak, Epidemic, and Pandemic

In public health, the terms outbreak and epidemic mean the same thing:

More cases of a disease than expected in a specific population, time, and place.

A pandemic is an outbreak or epidemic that spreads across multiple countries or continents, usually affecting a large number of people.

Understanding whether something is “normal” or “concerning” requires historical data, context, and often judgment. One case of Ebola, for example, is considered an outbreak. But one case of influenza is not—because we expect to see it every season.

📈 How Many Cases Is “Too Many”?

Determining the threshold for concern is not always simple. Here’s why:

• Some diseases are rare but severe (e.g., measles, meningitis)

• Some are common and mild (e.g., colds, norovirus)

• Some rise slowly and may be missed at first

• Others appear suddenly with a dramatic spike

The question is not just “Is this unusual?” but also:

• “Is this dangerous?”

• “What cost are we willing to pay to reduce the number of cases?”

🤔 Society’s Tolerance for Risk

Outbreak response is shaped not only by science—but by social values and economics.

During COVID-19, for example, societies made collective decisions:

• We are willing to accept X cases

• Y hospitalizations

• Z deaths

Why? Because reducing all of those to zero might require unacceptable costs to jobs, schools, or individual freedoms.

This balancing act happens in public health all the time—even if it's rarely stated so plainly.

Example:

• We could have zero traffic deaths by banning cars—but we don’t.

• We could eliminate teen STIs by mandating isolation—but that’s also not acceptable.

🧮 How Do We Detect an Outbreak?

Public health professionals use epidemiologic judgment and sometimes statistical tools called “aberration detection algorithms” to determine whether the number of reported cases is unusually high.

One example is SaTScan, which detects space-time clusters of disease. But even with these tools, the hardest part is knowing:

“What is the normal background rate of illness?”

This is particularly challenging when:

• The disease is rare or has a low attack rate (not everyone exposed gets sick)

• The symptoms are non-specific (e.g., diarrhea, fatigue)

• The cases are geographically dispersed

🧠 Outbreaks Aren’t Always Obvious

Some are:

• 🔥 Rapid and explosive (e.g., norovirus in a school)

• 🌊 Slow and subtle (e.g., a new STD among a marginalized population)

• 🏙️ Masked by noise (e.g., respiratory illnesses in winter)

Each one requires a combination of:

• Good data

• Alert clinicians

• Skilled epidemiologists

• Local knowledge

🔗 Learn More

• 📖 Case Study on Detecting Legionnaires Disease Outbreak in New York City

• 📖 How to think about reports of a new disease or cluster of unexplained illness

• ▶️ Is There an Autism Epidemic?