Outbreak data and agent ID lab
This page has four parts, in the order you use them. Part 1 is what you need to know. Part 2 says what to do, in plain English. Part 3 shows the work done once on a case that is not yours. Part 4 is your own work and where to turn it in.
Open your materials, follow the steps, then turn in your work.
Students build outbreak visualizations and run identification tests to characterize the infectious agent.
Check you have the right sheet: the top of it prints today's portal day, Outbreak data and agent ID lab. The PLTW activity itself is in myPLTW and is not posted here.
Optional: listen or watch a unit review▸
Part 1 of 4 · Background and definitions▸
💡 Big idea: Each identification test reads only one property of a , so narrowing to the true agent works by stacking several test results together to eliminate suspects, not by finding one test that names it.
- • An outbreak investigation manipulates nothing: the is observational data, the and spot map are displays of it, and each identification test measures one property of the agent.
- • A is one row per case with onset date, location and exposures; an counts cases by onset date, and its shape (one sharp peak, a plateau, successive waves) suggests how exposure happened; a spot map marks where each case was, to reveal a cluster.
- • Plotting a spot map requires converting addresses or zones into a visual cluster to reveal a common source.
- • Agent-identification tests each detect a specific property: morphology, biochemical profile, or .
An infection-control CER earns trust because it names the mechanism, predicts an outcome, and states its assumptions, so anyone can test whether the control actually works.
Each identification test reads only one property of a , so narrowing to the true agent works by stacking several test results together to eliminate suspects, not by finding one test that names it.
Driving question: Given the printed your teacher hands out and a set of identification tests, can you plot the outbreak, run the tests, and narrow six possible bacteria down to the one that fits both the data and the test results?
What you already know: An infection-control CER earns trust because it names the mechanism, predicts an outcome, and states its assumptions, so anyone can test whether the control actually works.
New idea: Each identification test reads only one property of a , so narrowing to the true agent works by stacking several test results together to eliminate suspects, not by finding one test that names it.
- Observe or measure the relevant feature in today's lesson.
- Organize the observation with a stable evidence ID.
- Apply this rule: Patterns across time and connection can narrow a explanation without proving it by themselves.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Given the printed your teacher hands out and a set of identification tests, can you plot the outbreak, run the tests, and narrow six possible bacteria down to the one that fits both the data and the test results?
What the evidence supports: E1 to E3 and the figure support the daily take-home when the response meets the stated success criteria.
What it cannot prove: The package does not support claims beyond this lesson's or any real patient diagnosis.
- • epidemiology: The study of how diseases spread, who they affect, and what causes them across populations, used to find patterns and guide prevention.
- • : A table used in outbreak investigations where each row records one patient's key details, such as symptoms, dates, and exposures.
- • : A bar graph showing the number of new disease cases over time, used to track how fast an outbreak is growing or shrinking.
- • : Keeping samples or cultures at a controlled warm temperature for a set time so cells, microbes, or reactions can grow or proceed.
- • prevalence: The share of a population that has a particular disease or condition at a given time, often shown as a percentage.
- • incidence: The number of new cases of a disease that appear in a population during a set period of time.
- • : The specific organism or factor, such as a bacterium, virus, or , that directly produces a particular disease.
Use it now: Choose one decision option. Cite E1 and E3, then explain how the rule connects the evidence to your choice. This is thinking practice for the one turn-in named under Turn in, not a second submission.
Go further, optional: The source links below are optional enrichment. Every fact required for today's local evidence decision appears in this lesson package.
Patterns across person, place, and time can narrow an outbreak hypothesis, but they require case definitions, comparison data, and laboratory or epidemiological confirmation before a source is established.
Limit: A classroom map or curve can support a limited hypothesis and next investigation step, not a confirmed source or individual diagnosis.
Patterns across time and connection can narrow a explanation without proving it by themselves.
Limit: People change behavior, infections have periods, and surveillance data can be incomplete.
Produce an accurate and map from the .
Limit: E3 defines the classroom product or success criterion. It is not independent scientific evidence and cannot justify a clinical or causal claim.
Today's decision · Simulated classroom evidence scenario
Your role: biomedical investigator
Decision: Your team must decide what the evidence from today's lesson supports before submitting the labeled and result claim named on today's page.
- • Pick the single test that identifies the by name, because that result settles which bacterium caused the outbreak.
- • Run every test beside a bacterium whose properties are already known, because stacked results cannot reveal that one reading was wrong.
- • Stack several test results together, since each test reads one property, and rule suspects out until one bacterium still fits.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Use it inside the one turn-in named under Turn in; it is not a separate submission.
Claim ceiling: Today's evidence supports a classroom claim about today's lesson. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Reason for review: Your team must decide what the evidence from today's lesson supports before submitting the labeled and result claim named on today's page.
Context: Identifying an outbreak agent is applied science under uncertainty: you convert case data into a curve and a map, then use tests that each read one property of the to rule suspects out until a short list remains.
- • T1: Record the for completing the and recording test results.
- • T2: Write down what kind of investigation this is: nothing is manipulated, the is observational data, the curve and the map display it, and each identification test measures one property of the agent.
- • T3: Plot an and a spot map from the printed your teacher hands out; if it is not in the room, practice both plots on the practice outbreak dataset in Part 2 of this page.
- • T4: Read the 3.1.5 plates through the lid. Mr. Mendoza streaked these plates in advance; they have incubated at 30 degrees C for 48 hours. Record each 's color, form, elevation and margin, then use the identification results to narrow the candidate agent.
- • T5: Note sources of measurement error and one limitation of the data set.
- • E1: Patterns across person, place, and time can narrow an outbreak hypothesis, but they require case definitions, comparison data, and laboratory or epidemiological confirmation before a source is established.
- • E2: Patterns across time and connection can narrow a explanation without proving it by themselves.
- • E3: Produce an accurate and map from the .
Measurements: Use only the measurements, units, graph, or counts supplied in today's task. No additional patient measurement is implied.
Figure finding: Blank epidemic-curve axes labeled cases and onset date, a blank four by four grid map, and an elimination ladder with columns candidate, test and in or out and six empty rows.
Uncertainty: This is a composite classroom scenario. Missing history, measurements, or confirmation tests remain unknown and limit the conclusion.
Ate dish A: 12 / 40 x 100 = 30 percent. Did not eat it: 2 / 20 x 100 = 10 percent. The dish's rate is three times the other, which points at dish A as the exposure worth testing.
Suppose 40 people ate dish A and 12 became ill, while 20 people did not eat it and 2 became ill. What are the two attack rates, and what does the difference suggest?
Each rate uses its own denominator, the people in that group; a rate with the wrong denominator compares nothing. A difference suggests an exposure; the map and the agent-ID test still have to agree before it is a claim.
For your own , write the attack rate for each exposure with its denominator beside it, and mark the one that stands out.
Students often think one master test reads out the 's name, like a barcode scanner that just tells you the answer. The trap: No single test names the agent, because each test only detects one property (a shape, a sugar it can ferment, an it carries), and identification is the logic of stacking several results together to eliminate suspects until one candidate survives.
- CER:
- Claim, Evidence, Reasoning: make a claim, back it with evidence, explain your reasoning.
- SOP:
- Standard Operating Procedure, the exact steps to follow (especially in a lab).
- Tracker:
- Your PLTW progress log where you record completed evidence.
- myPLTW:
- The PLTW course site where you do the online activities. Find it in Clever with your Microsoft sign-in, right next to Schoology.
Tap the speaker to hear a term. Add two of these to your notebook glossary with a definition and an example in your own words.
Pick just 2 or 3 words from today and make them yours: write what each one means in your own words, name the context clue or evidence that helped, then give one example from what you actually did in Outbreak data and agent ID lab. Try your own words first; the glossary is there if you get stuck. This is voluntary and counts as extra credit, so keep it short.
Saved on this device. Show Mr. Mendoza or add these to your notebook glossary to claim the extra credit.
Part 2 of 4 · Directions in plain English▸
2.1 Open your materials
Use the materials named in the first step below. Open lesson resources.
Practice outbreak dataset (made-up practice data, not the class outbreak and not real patients)
The setting
- A practice hospital watched three units for 12 days, Day 1 to Day 12. A case is a patient with a new wound infection or fever that started on one of those days.
- Use this dataset only if you do not have your class line list, curve, map and agent-ID results. Write "practice dataset" on anything you build from it.
Line list: one row per case
| Case | Unit and room | Onset day | Main sign | Dressing change from the 3 North supply cart? | Gram stain | Colony: color, form, elevation, margin | Oxidase test |
|---|---|---|---|---|---|---|---|
| 1 | 4 East, room 412 | Day 2 | Red, painful wound | No | Positive, rods | Tan, circular, raised, entire | Negative |
| 2 | 3 North, room 306 | Day 3 | Wound drainage and fever | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 3 | 3 North, room 312 | Day 4 | Wound drainage | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 4 | 3 North, room 308 | Day 4 | Fever | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 5 | 3 North, room 314 | Day 5 | Wound drainage | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 6 | 3 North, room 303 | Day 5 | Wound drainage and fever | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 7 | 3 North, room 310 | Day 5 | Fever | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 8 | 3 North, room 316 | Day 6 | Wound drainage | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 9 | 3 North, room 311 | Day 6 | Wound drainage and fever | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 10 | 3 North, room 318 | Day 7 | Fever | No | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 11 | 3 North, room 305 | Day 8 | Wound drainage | Yes | Negative, rods | Cream with a green tint, irregular, flat, undulate | Positive |
| 12 | 3 South, room 327 | Day 10 | Fever | No | Negative, rods | Cream, circular, convex, entire | Negative |
Patients at risk, Day 1 to Day 12
| Unit | Patients on the unit during Day 1 to Day 12 | Of those, patients who had a dressing change from the 3 North supply cart |
|---|---|---|
| 3 North | 40 | 20 |
| 3 South | 50 | 0 |
| 4 East | 30 | 0 |
Map key for the spot map
- Each unit is one hallway. 3 North is rooms 301 to 320, odd numbers on the left side and even numbers on the right. The 3 North supply room, where the dressing cart is kept, sits between rooms 309 and 311.
- 3 South is rooms 321 to 340 on the same floor, across the elevator lobby from 3 North. 4 East is rooms 401 to 420, one floor up.
Practice candidate key (made-up candidates, not the class culture key)
| Candidate | Gram stain | Colony color | Oxidase test |
|---|---|---|---|
| Candidate A | Positive, rods | Tan | Negative |
| Candidate B | Positive, cocci in chains | White or gray, small | Negative |
| Candidate C | Negative, rods | Cream | Negative |
| Candidate D | Negative, rods | Cream with a green tint | Positive |
- Cross a candidate off as soon as one result does not fit it. A match narrows the field; it does not confirm an identity.
The two rates you calculate
- Incidence: new cases during Day 1 to Day 12, divided by the patients at risk during Day 1 to Day 12, times 100. Say which group you used: the whole hospital or one unit.
- Attack rate: cases among the patients who had the exposure, divided by all patients who had that exposure, times 100. Compare it with the same rate for patients on the unit who did not have the exposure.
2.2 Start the work
Record the SOP for completing the line list and recording test results.
Show all 5 required steps
- Record the SOP for completing the line list and recording test results.
- Write down what kind of investigation this is: nothing is manipulated, the line list is observational data, the curve and the map display it, and each identification test measures one property of the agent.
- Plot an epidemic curve and a spot map from the printed line list your teacher hands out; if it is not in the room, practice both plots on the practice outbreak dataset in Part 2 of this page.
- Read the 3.1.5 plates through the lid. Mr. Mendoza streaked these plates in advance; they have incubated at 30 degrees C for 48 hours. Record each colony's color, form, elevation and margin, then use the identification results to narrow the candidate agent.
- Note sources of measurement error and one limitation of the data set.
Lost your place? This is a lab. Check your SOP step: recorded the SOP (1), stated what the data, the displays and the tests are (2), plotted the curve and spot map (3), interpreted the ID tests to narrow the agent (4), then noted one error source and one data limitation (5). Resume at your first unchecked step.
- 0-8 minReview for line-list completion and test-result recording; write it in your notebook.
- 8-15 minRecord what the is (observations), what the curve and map are (displays), and what each test measures.
- 15-38 minComplete from case data; plot on graph paper or provided template.
- 38-52 minPlot spot map; identify geographic cluster.
- 52-68 minRun or interpret agent-identification test results; record candidate pathogens in .
- 68-80 minRecord one measurement error source and one data-set limitation; begin organizing for the CER next class.
- • Today you also read the 3.1.5 plates. Mr. Mendoza streaked these plates in advance; they have incubated at 30 degrees C for 48 hours.
- • Today you work as an outbreak investigation team: the is your raw data and the lab is your analysis pipeline.
- • Every result you record must follow the exactly, because a misrecorded test result can redirect an entire investigation.
- • Strand 5 of your end-of-course WebXam covers handling, preparing, storing and disposing of materials, which you practice today.
- • Document your measurement error source: it is part of the lab report, not an optional add-on.
PLTW connection and today's work
In myPLTW, open Lesson 3.1 Nosocomial Nightmare and go to Activity 3.1.5 Isolation. Use it to guide your epidemic curve and your agent ID.
Today's stopping point: myPLTW responses for this Lesson 3.1 lab should be submitted before you leave today.
PLTW activity titles identify the course connection. If your account will not open, use the posted materials for today and tell Mr. Mendoza. Do not mark an online activity complete unless you completed it.
Use the turn-in directions in Part 4 of this page. Do not create a second submission unless your teacher asks for one.
Show another explanation or a smaller first step
Need help? Choose a starting point
Finish the assigned lab safely before starting extra practice.
Part 3 of 4 · Worked example▸
This is a parallel case, not your own. Read it for the order of the work, then do your own in Part 4.
SOP I recorded: complete one line-list row per case, then plot onset dates for the curve and locations for the map, then record each identification-test result exactly as observed.
What this investigation is: nothing is manipulated. The line list is observational data, the curve and the map display it, and each identification test measures one property of the agent.
Line-list summary: 18 cases, onset clustered November 14 to 16, most near the east cafeteria.
Epidemic curve: single sharp peak on November 15, which reads as a point-source pattern.
Spot map: a tight cluster around the east cafeteria, pointing to a common exposure there.
Agent-ID results: Gram stain showed gram-negative rods; the lactose test was positive; the candidate was narrowed to a gram-negative enteric bacterium.
Measurement error: two onset dates were self-reported from memory, so the curve's exact peak day could be off by a day. That is a data-quality limit, not a plotting mistake.
| Case | Onset date | Location | Gram stain | Lactose test |
|---|---|---|---|---|
| 1 | Nov 14 | East cafeteria | Negative rod | Positive |
| 2 | Nov 15 | East cafeteria | Negative rod | Positive |
| 3 | Nov 15 | East cafeteria | Negative rod | Positive |
| 4 | Nov 16 | West hall | Negative rod | Positive |
This model shows the level of evidence and organization needed to complete: Completes the outbreak lab: a line-list summary, a plotted epidemic curve and spot map, agent-ID results, and one stated measurement error.
- Name the variables and include units.
- Enter observations without changing the raw values.
- Check labels, calculations, and patterns before interpreting the data.
Keep the structure. Replace the question, facts, measurements, and evidence. Then recheck units, vocabulary, and whether the conclusion goes beyond the evidence.
Also due today: Submit as one PDF in Schoology.
Wet footprints appear across connected rooms after one person enters from the rain.
- Which footprint came first?
- Which rooms connect?
- What pattern would support more than one entry point?
Patterns across time and connection can narrow a explanation without proving it by themselves.
People change behavior, infections have periods, and surveillance data can be incomplete.
- • Footprints map to recorded cases.
- • Room connections map to exposures.
- • The route hypothesis maps to a limited claim.
Part 4 of 4 · Your work▸
Check your work before submitting
- Produce an accurate epidemic curve and map from the line list.
- Narrow the infectious agent and state one procedural limitation.
Before lab work: read the safety rules
- Reading the 3.1.5 plates: Mr. Mendoza streaked these plates in advance; they have incubated at 30 degrees C for 48 hours. Goggles and a lab coat on, plates stay closed and are read through the lid, the bench is disinfected before and after, and gloves and plates go into the biohazard container, never the trash.
- If your class uses printed result cards instead, there are no bench hazards; keep the cards at your station.
- Wash hands thoroughly with soap and water after handling any lab materials.
- Keep all printed case data at your station; do not share papers between stations to prevent data contamination.
4.1 Turn in your work
DueCheck the Schoology assignment for this day- Hand in
- Completed data table with line-list summary, plotted epidemic curve (labeled with transmission type), spot-map cluster description, agent-ID results, and one stated measurement error.
How to submit and name your file
Submit as one PDF in Schoology.
In Schoology, open your course and the assignment for this lesson. Attach your file, select Submit, and check that it appears in the submission.
PDF upload helpYou get two school days for every day you were absent, so this deadline moves with you.
Today's lesson is in Schoology
Each school day has one lesson page in Schoology that holds everything for the day: the goal, the story so far, every table and data value, the numbered steps, and what to turn in. Open it first and work from it. The other rows for this day, if any, are the score line for a paper quiz or test and the John Carroll debate item; they do not add work. Check Schoology for each deadline.
- Today's Lesson · Tue 11/24 · Wk14 · Review the eleven patients, then the six kinds of infectious agents(today's lesson page: the goal, the data, the steps, and what to turn in are all on it)
Link will not open? Open Schoology, choose your course and section, and find the title shown above.
- CompleteEvery required part of the artifact is present, nothing left blank.
- AccurateThe science and the data are correct and match the evidence.
- Scientific reasoningYou explain your claim with evidence and reasoning (CER), not just an answer.
- Professional communicationClear, organized, labeled, and written the way a clinician or scientist would.
- SubmittedGo to Schoology to turn this in. Submit one PDF. Schoology attaches your name to your upload; on the page itself, write your period and code. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf. If you cannot get in, see Mr. Mendoza. Do not skip the work.
- Error analysis and method · counts doubleName a specific limit of the method and how it moved your result, and compare what you predicted to what happened. "Human error" does not count; say what about the procedure or instrument caused it.
How this lesson connects
Keep using what you learned last class: An infection-control CER earns trust because it names the mechanism, predicts an outcome, and states its assumptions, so anyone can test whether the control actually works. Today: Each identification test reads only one property of a pathogen, so narrowing to the true agent works by stacking several test results together to eliminate suspects, not by finding one test that names it.
Practice: try a question, then check your answer▸
Claim ceiling for this check: Today's evidence supports a classroom claim about today's lesson. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Your candidate list is E. coli, Salmonella, Shigella, and Staphylococcus aureus. A gram stain of the outbreak sample shows gram-negative rods. Which suspect can you cross off right now, and why can't the gram stain alone name the agent?
Write an answer and pick a confidence to unlock the key.
Fast retrieval with instant answers, not the commit-then-reveal check above. Try each from memory first: write what you remember about the earlier units, then check yourself here.
Missed class or ready for more?▸
Run this before you touch the bench. It is built from the real lab procedure, so the decisions you make here are the ones you will make with the equipment in your hands.
I can name the procedure's purpose and the evidence I will record. I can state today's specific hazards and the control for each. If this deck does not name them, I ask Mr. Mendoza before I touch anything. My data table is ready before materials are handled.
Finish the checklist before you handle any material.
- • Reading the 3.1.5 plates: Mr. Mendoza streaked these plates in advance; they have incubated at 30 degrees C for 48 hours. Goggles and a lab coat on, plates stay closed and are read through the lid, the bench is disinfected before and after, and gloves and plates go into the biohazard container, never the trash.
- • If your class uses printed result cards instead, there are no bench hazards; keep the cards at your station.
- • Wash hands thoroughly with soap and water after handling any lab materials.
- • Keep all printed case data at your station; do not share papers between stations to prevent data contamination.
- 1Before materials are handled, identify the purpose, variables or comparison, controls, measurement units, and stop-work condition.
- 2Record the SOP for completing the line list and recording test results.
- 3Write down what kind of investigation this is: nothing is manipulated, the line list is observational data, the curve and the map display it, and each identification test measures one property of the agent.
- 4Plot an epidemic curve and a spot map from the printed line list your teacher hands out; if it is not in the room, practice both plots on the practice outbreak dataset in Part 2 of this page.
- 5Read the 3.1.5 plates through the lid. Mr. Mendoza streaked these plates in advance; they have incubated at 30 degrees C for 48 hours. Record each colony's color, form, elevation and margin, then use the identification results to narrow the candidate agent.
- 6Note sources of measurement error and one limitation of the data set.
- 7Record each result in the prepared table before interpreting it. Mark missing, repeated, or invalid results truthfully.
- 8Complete the named cleanup and waste route, remove PPE safely, wash hands when required, and confirm the station is ready for the next group.
| Which trial or sample this row is | What you changed on purpose | What you measured, with units | What you saw, before you explain it | Anything that could make this reading wrong |
|---|---|---|---|---|
Before the procedure, predict the result and cite the rule behind the prediction.
After the procedure, compare the result with the prediction and name one limitation or source of uncertainty.
What today's skills lead to. These are real health-science careers this course builds toward. Tap one to see, on the US Department of Labor's O*NET site, what the job actually involves, what it pays, and how fast it is growing.
At home: use the practice outbreak dataset in Part 2 of this page. Plot an from the onset days and a spot map from the rooms, then use the case test results and the practice candidate key to cross candidates off one property at a time and write which candidate survives and why. Label your "practice dataset".
CDC: Quick-Learn Epi CurvesSubmit as one PDF in Schoology.
Class still runs. Complete today's work as this page describes (it is self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
CDC: principles of epidemiology and outbreak investigationThe optional extra-credit track is open. Complete reserved-unit work from home, including virtual labs, for extra credit. Each item shows its correct submission route.
Open the extra-credit trackSources: slides, readings, and resources▸
The deck carries the prior idea forward, lets you inspect an analogy, maps the rule to biology, and ends with the same evidence decision and exit ticket used on this page.
Play the cold open at the start of the unit to set the scene. Each recording is AI-generated and simulated (fictional callers, no real people or student data).
Hand-picked readings and interactives for this lesson, from authoritative open organizations and PLTW's own public course outline.
This week
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