Outbreak data and agent ID lab
Open your materials, follow the steps, then turn in your work.
Students build outbreak visualizations and run identification tests to characterize the infectious agent.
1. Open your materials
Use the materials named in the first step below. Open lesson resources.
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.
- Identify the independent and dependent variables in the agent-ID procedure.
- Plot an epidemic curve and a spot map from the provided case data.
- Run or interpret the identification test results to narrow the candidate agent.
- Note sources of measurement error and one limitation of the data set.
Lost your place? Lost your place? This is a lab. Check your SOP step: recorded the SOP (1), labeled independent and dependent variables (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.
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
- If using simulated biological samples, wear gloves and avoid touching face.
- Dispose of all simulated sample materials in the designated waste container, not the regular trash.
- 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.
3. Turn in your work
DueCheck Schoology- 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
Use the submission route shown on today's today's page.
In Schoology, open your course and the assignment for this lesson. Attach your file, select Submit, and check that it appears in the submission.
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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.
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▸
Need help? Warm-up, timing, and directions▸
💡 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.
- 0-8 minReview SOP for line-list completion and test-result recording; write it in your notebook.
- 8-15 minIdentify and record , , and controlled variables.
- 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 Thursday CER.
- • 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 SOP exactly, because a misrecorded test result can redirect an entire investigation.
- • This is a WebXam 072110 strand 5 day: Handling/Preparation/Storage/Disposal procedures are being assessed.
- • Document your measurement error source: it is part of the lab report, not an optional add-on.
- • : the case data provided; : the shape and agent-ID result.
- • 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 .
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: Platform 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 at the top 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.
Lesson resources: reading, slides, and vocabulary▸
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.
Generated from this lesson's canonical data with a red-team citation check.
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.
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.
Driving question: Given this reunion 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.
Visual or model: F1. F1. A lesson illustration or teaching diagram for Outbreak data and agent ID lab. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled observation or evidence sequence before choosing an explanation.
- 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 this reunion 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-E3 and F1 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.
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.
PLTW-PBT-2026-11-24 · 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.
- • Support the claim by saying the curve, the map, and the test all show the potato salad caused it.
- • Gather comparison data on who ate the potato salad and who did not, because case counts alone cannot show what differed.
- • Name the source only when the curve's timing, the map's location, and the test's biology each point there independently.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the labeled and result claim.
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 SOP for completing the and recording test results.
- • T2: Identify the independent and dependent variables in the agent-ID procedure.
- • T3: Plot an and a spot map from the provided case data.
- • T4: Run or interpret the identification test 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: Teaching diagram for Outbreak data and agent ID lab. Trace the labeled observation or evidence sequence before choosing an explanation. This is a teaching model, not patient or experimental data.
Uncertainty: This is a composite classroom scenario. Missing history, measurements, or confirmation tests remain unknown and limit the conclusion.
Rate or percent = part / comparison total x 100%. Percent change = (new - comparison) / comparison x 100%.
If 18 of 60 records meet a condition, the frequency is 18 / 60 x 100% = 30%.
Name the comparison total. A percent describes the supplied group and does not automatically predict an individual's outcome.
Use today's supplied counts to calculate one rate, risk, frequency, or percent change. Show the denominator and interpretation.
- • The solution must address the stated need in today's lesson.
- • The decision must be supported by E1-E3.
- • The final product must make the success criteria visible.
- • Complete the work inside the 80-minute block.
- • Use only supplied or teacher-approved materials and evidence.
- • Do not trade , accessibility, or privacy for speed.
- • and evidence quality: must pass before scoring other criteria.
- • User need and effectiveness: highest scored criterion.
- • Time, cost, and ease of use: compare only after and effectiveness pass.
Test evidence: For each option, record the E1-E3 result that supports or fails each criterion. Do not assign a score without a named observation.
- Version or option tested
- Criterion met or missed
- Evidence ID and result
- Revision made
- Reason for the revision
- Need and user
- Criteria and constraints
- Chosen option and evidence
- Test result
- Revision and reason
Students often think Students expect one master test that 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.
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.
Variables:
- Independent variable: the case data provided (onset dates, locations, test results).
- Dependent variable: the epidemic-curve shape and the narrowed agent ID.
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 your data table and visualization on Schoology before leaving.
- 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.
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.
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.
- • If using simulated biological samples, wear gloves and avoid touching face.
- • Dispose of all simulated sample materials in the designated waste container, not the regular trash.
- • 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.
- 3Identify the independent and dependent variables in the agent-ID procedure.
- 4Plot an epidemic curve and a spot map from the provided case data.
- 5Run or interpret the identification test 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.
| Trial or sample ID | Independent condition | Measured result with units | Observation before interpretation | Quality-control note |
|---|---|---|---|---|
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.
Hands-on outbreak lab: complete the , plot the and spot map, and run the agent-identification tests to record candidate pathogens.
CDC: Quick-Learn Epi CurvesUse the submission route shown on today's today's page.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
CDC: principles of epidemiology and outbreak investigationYou've passed Unit 2, so the 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 track- 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. Put your first and last name in the document header. 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.
This week
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