Investigation of an Outbreak

Reading the curve before you name the pathogen

Dr Arun Mitra

Dept of Community & Family Medicine, AIIMS, Bibinagar

2026-06-02

Learning Objectives

By the end of this session you should be able to:

  • Define endemic, outbreak, epidemic and pandemic — all as excess over expected
  • Read the four epidemic-curve shapes and infer the likely source
  • List the steps of an outbreak investigation (Park / CDC)
  • Compute food-specific attack rates and a relative risk to find the vehicle
  • Map John Snow’s 1854 work onto the modern investigation steps

Note

Competency CM7.4 · 7th-semester MBBS, Community Medicine

1 · The Hook

Which curve is which?

Four outbreaks. Four epidemic curves. No labels yet.

Think–pair–share (2 min): Which one spread person-to-person? Which was one bad meal? Which is contaminated piped water? Decide with your neighbour.

The four shapes, named

Important

The shape narrows the source before you have named the pathogen.

Shape → mechanism

Single sharp peak — all cases within one incubation period. A single brief exposure: hostel dinner, wedding feast → food poisoning.

Sustained plateau — cases persist while the exposure continues. Contaminated piped water (Snow’s Broad Street).

Irregular spikes — the source is shared, but contaminated only on some days. A food sporadically served unsafe.

Successive, taller peaks one incubation period apart. Person-to-person spread: measles, COVID-19, Nipah.

2 · Definitions

Endemic → Pandemic

Endemic

The constant, expected presence of a disease in an area — the baseline.

Outbreak

Cases in excess of expectation, usually localized / smaller scale.

Epidemic

Cases clearly in excess of normal expectancy in a community or region.

Pandemic

An epidemic spread across countries / continents.

Also: cluster (aggregation in place/time) · sporadic (irregular, scattered cases).

It all hinges on the baseline

Important

You cannot call something an outbreak until you know the expected count. No baseline → no outbreak.

3 · Famous Investigations

A story gallery

  • John Snow, 1854 — the founding case; a spot map indicts the Broad Street pump (our storyboard).
  • Semmelweis, 1847 — handwashing cuts puerperal-fever deaths; evidence rejected for decades.
  • “Typhoid Mary” Mallon — the asymptomatic carrier who infected dozens through cooking.
  • Legionnaires’, 1976 — a novel organism (Legionella) found because of the investigation.
  • Nipah, Kerala 2018 — a recent Indian anchor: rapid response team, zoonotic spillover → One Health.

Note the thread: investigation can stop an outbreak, expose a carrier, or discover a brand-new pathogen.

4 · Why Investigate?

Six reasons

  1. Control the current outbreak — interrupt transmission now
  2. Prevent recurrence — fix the source, not just the cases
  3. Identify novel agents & new risk factors
  4. Evaluate prevention & surveillance programmes
  5. Statutory obligation + public concern / rumour control
  6. Research & training — every outbreak teaches

Tip

You will often act on more than one of these at the same time — control rarely waits for certainty.

5 · What You Need First

The “5 P” checklist

Rapid response team with defined roles — epidemiologist + clinician + lab + data.

Administrative authorisation, ethics, data-sharing; multisectoral / One Health sign-off for zoonoses.

Line-list proforma, PPE, specimen kits + cold chain, transport, mobile data capture.

Draft case definition, specimen plan, analytic plan, SOPs.

Surveillance data for the expected count, population denominators, maps.

Ask the class: A late-night call reports “many fever cases” in a hostel. Which of the 5 Ps would you secure before leaving the office?

6 · The Steps

Steps of an outbreak investigation

Park / CDC — not strictly linear; control can begin early.

flowchart LR
  A[Verify<br/>diagnosis] --> B[Confirm the<br/>epidemic]
  B --> C[Case definition<br/>+ line list]
  C --> D[Describe:<br/>time · place · person]
  D --> E[Hypothesise]
  E --> F[Test<br/>attack rates · RR/OR]
  F --> G[Refine +<br/>lab/environment]
  G --> H[Control]
  H --> I[Communicate]
  I --> J[Maintain<br/>surveillance]

The epidemic curve (time) and the spot map (place) pay off here. Watch them work on a real case →

Soho, August 1854

Steps 1–2 · Verify diagnosis · Confirm the epidemic

A violent illness kills within hours around Broad Street. Snow confirms it is cholera and that deaths far exceed baseline — a true epidemic. The neighbourhood and its pumps; no deaths plotted yet.

Ask: The prevailing theory blames miasma (bad air). What one fact must you confirm first?

Case finding

Step 3 · Case finding & line listing

Door to door, Snow records each death by home address — an early line list. Every red mark is a death tied to a place.

Ask: Why fix a precise case definition before you start counting?

PLACE — the spot map

Step 4 · Describe by PLACE

Mapped by location, deaths are not scattered with the wind — they cluster tightly around one pump. The farther the home, the safer.

Ask: If cholera spread by bad air, what different spatial pattern would you expect?

PERSON — the exceptions test the idea

Step 5 · Describe by PERSON · test the hypothesis

The brewery (workers drank beer + own well) and the workhouse (own well) are spared. A widow in distant Hampstead died — she had Broad Street water carted in. The voids fall exactly on brewery and workhouse.

Ask: These act like a control group. What finding would have weakened Snow’s idea?

The hypothesis

Step 6 · Formulate the hypothesis

Snow states it plainly: cholera is carried by water fouled with sewage — decades before the bacterium is accepted. He reaches it by pattern and reason alone. The Broad Street pump is the suspect.

Ask: We have a strong association. What is the danger of acting on association alone — and why act anyway?

The analytic test — the “Grand Experiment”

Step 7 · Test the hypothesis analytically

Same South-London streets, two water firms: Southwark & Vauxhall (sewage-fouled Thames) vs Lambeth (intake moved upstream). The contaminated supply carried ≈ 8× the mortality.

Ask: Exposed vs unexposed households — what modern study design is this?

Control — remove the handle

Step 8 · Control measure

The parish takes the handle off the Broad Street pump. The iconic lesson: you can interrupt transmission before you fully understand the organism.

Ask: The epidemic was already declining (many had fled). How sure can we be the handle caused the fall?

What Snow teaches

Steps 9–10 · Report & maintain surveillance

His map and reasoning become the founding case of epidemiology.

Verify → Count → Describe (time, place, person) → Hypothesise → Test → Control → Report.

Ask: Which formal step did the spot map itself belong to?

7 · Examples — Matched to the Curves

The curve tells you where to look

Example Curve shape The drill
John Snow / Broad Street Continuous common source (water) Place · spot map · natural experiment
Hostel gastroenteritis Point source Food-specific attack rates → RR → vehicle
Nipah / measles Propagated Contact tracing · incubation spacing

Example A · Hostel — a point source

  • 64 students; a sharp burst of vomiting & diarrhoea
  • All onsets within ~24–30 h of one dinner
  • Single tight peak → point source, one common meal
  • Task: which dish was the vehicle?

Tip

Point source → compute a food-specific attack-rate table.

Example A · Attack-rate table

Attack rate (AR) = ill ÷ total, among those who ate vs did not eat each food.

Food Ate: ill/total (AR%) Did not eat: ill/total (AR%) Relative Risk
Chicken curry 38/40 (95%) 2/24 (8%) 11.4
Paneer 20/33 (61%) 20/31 (65%) 0.94
Salad 25/40 (63%) 15/24 (63%) 1.00
Ice cream 18/30 (60%) 22/34 (65%) 0.92

Important

Chicken curry: highest AR in eaters, lowest in non-eaters, RR ≈ 11 → the vehicle.

Example A · Reading the RR

\[RR = \frac{\text{AR}_{\text{exposed}}}{\text{AR}_{\text{unexposed}}} = \frac{95\%}{8\%} \approx 11.4\]

  • RR > 1 → exposure raises risk
  • RR ≈ 1 → no association (paneer, salad)
  • Big gap + dose-response + biological plausibility → vehicle

Confirm, don’t just compute

Lab the food & cases · inspect the kitchen · check the cook (carrier?) · trace the supply.

Example B · Nipah / measles — propagated

  • Successive peaks, each ~one incubation period apart, building taller
  • Signature of person-to-person transmission
  • Kerala 2018: index case → family & health-care contacts; rapid RRT; zoonotic (fruit bats) → One Health
  • Drill: contact tracing, isolation, incubation-based quarantine

Important

Spacing between peaks ≈ the incubation period — it lets you predict the next wave.

8 · Take-home

One thread to carry

The whole seminar in one line

An outbreak is cases in excess of expected. Read the curve, fix the case definition, then: Verify → Count → Describe → Hypothesise → Test → Control → Communicate — and act before you’re certain.

  • Point source → one sharp peak → one bad meal
  • Continuous common → plateau → contaminated water (Snow)
  • Intermittent common → irregular spikes → sporadically unsafe food
  • Propagated → taller successive peaks → person-to-person (Nipah)

The shape narrows the source before you’ve named the pathogen.

References

  • Park K. Park’s Textbook of Preventive and Social Medicine — Epidemiology; Investigation of an Epidemic.
  • CDC. Principles of Epidemiology in Public Health Practice (Lesson 6: Investigating an Outbreak). https://www.cdc.gov/csels/dsepd/ss1978/
  • Snow J. On the Mode of Communication of Cholera. 2nd ed. London: John Churchill; 1855.
  • Arunkumar G, et al. Outbreak investigation of Nipah virus disease in Kerala, India, 2018. J Infect Dis. 2019;219(12):1867–1878.
  • WHO. Disease outbreak toolkit / Field epidemiology resources. https://www.who.int/emergencies/outbreak-toolkit

Questions?

Thank You