BioGuard NYC: Legionella Busters

Learning Goals & Products

Learning Goals

Students will be able to investigate Legionella growth conditions in NYC water systems using outbreak case data, water temperature patterns, and maintenance records to explain contamination risk.

Students will be able to synthesize NYC Legionnaires' disease outbreak evidence from maps, public health reports, and news sources to identify patterns in affected buildings and communities.

Students will be able to define a testable engineering problem for early Legionella detection in NYC Housing Authority residential water systems with clear criteria and constraints.

Students will be able to explain how temperature, stagnation, and maintenance practices affect Legionella transmission risk in large residential plumbing systems.

Students will be able to prototype a low-cost biosensor concept that could detect simulated Legionnaires' risk in apartment water samples.

Students will be able to test and refine a biosensor prototype using simulated apartment water samples and user feedback to improve accuracy, reliability, and usability.

Products

individual

Legionella Risk Research Brief and Prototype Concept Sheet

Each student produces a research brief grounded in NYC outbreak evidence and a one-page concept sheet for a low-cost biosensor or monitoring idea. The work must show how firsthand or case-based evidence led to a specific design direction.

team

NYC Housing Water Safety Problem Statement and Tested Biosensor Pitch

Teams create a shared problem statement and a higher-fidelity prototype or service concept for NYC Housing Authority stakeholders, supported by testing data and revision notes. The final pitch must clearly connect individual research insights to the team solution.

Rubric

Mastery-Based Rubric Standards-first rubric

Category	Standard	Beginning (1)	Developing (2)	Proficient (3)	Exceeding (4)
Next Generation Science Standards	HS-LS2-7 - Design, evaluate, and refine a solution for reducing the impacts of human activities on the environment and biodiversity.	I can describe how human activities in NYC water systems (like warm stagnant water and inconsistent maintenance) can increase Legionella growth and explain why early detection helps protect residents I can identify simple criteria (e.g., safety and low cost) and constraints for a monitoring idea using resources available in our school project.	I can use patterns from outbreak case data and information about Legionella growth to explain where risk is more likely to occur in residential water systems I can design a basic monitoring/biosensing approach with clear qualitative criteria and constraints (cost, speed, safety, practicality) and justify it as a possible solution that reduces outbreak impacts.	I can evaluate and refine my design by connecting scientific evidence (temperature, stagnation, maintenance effects) to how my biosensor would detect high-risk conditions I can test the solution using simulated apartment water samples, collect performance data (accuracy/reliability/usability), and use results to revise the engineering design and design brief.	I can optimize and iterate a low-cost biosensor solution by designing a coherent testing plan (including a simulation/model when appropriate) that tests impacts on Legionella risk under multiple interacting conditions and constraints I can evaluate trade-offs using prioritized criteria (cost, safety, reliability, and practicality) and refine the solution with feedback from public health reviewers, explaining how it would reduce environmental health impacts and improve decisions in NYC Housing Authority settings.
Next Generation Science Standards	HS-ETS1-2 - Design a solution to a complex real-world problem by breaking it down into smaller, more manageable problems that can be solved through engineering.	I can describe a real-world problem related to Legionnaires’ disease risk in NYC housing water systems and explain, in simple terms, how engineering solutions could help by enabling earlier detection I can list at least two engineering steps (e.g., identify a target, choose measurements) that connect to my biosensor idea.	I can break the complex Legionella monitoring problem into smaller engineering subproblems (e.g., sample collection, detection method, data reporting) and choose which subproblem to solve first based on what is feasible in a school setting I can create a basic plan with clear success measures (qualitative and/or simple quantitative) and constraints tied to safety, cost, and usability in dense housing.	I can design and justify a step-by-step engineering approach for a low-cost biosensor that directly addresses at least two subproblems (such as detecting contamination and supporting decision-making) I can specify criteria and constraints for my design, explain trade-offs (speed vs accuracy, cost vs reliability), and revise my plan using feedback from public health perspectives.	I can develop a refined engineering design solution by fully integrating multiple subproblems into one coherent system (biosensor + testing procedure + interpretation/use guidance) that targets earlier risk detection I can evaluate and iteratively improve my prototype using performance data from simulations, analyze evidence critically, and explain how my design meets prioritized criteria while accounting for societal needs, resident safety, and environmental considerations.
Next Generation Science Standards	HS-ETS1-1 - Analyze a major global challenge to specify qualitative and quantitative criteria and constraints for solutions that account for societal needs and wants.	I can analyze the NYC Legionnaires’ disease challenge and describe what makes a solution needed for residents, staff, and public health, using simple qualitative criteria (e.g., safer earlier detection) I can identify a few basic constraints (e.g., time, cost, available school testing materials) and explain how they influence my design idea in my own words.	I can translate the global challenge of Legionella risk into clear qualitative and quantitative criteria (e.g., detection time goals, acceptable error range, and practical usability needs) that reflect societal needs and wants in NYC Housing Authority settings I can specify key constraints (cost, safety, reliability, and practicality) and connect each criterion/constraint to how my biosensor design would need to work in real buildings.	I can analyze and justify a detailed set of qualitative and quantitative criteria and constraints for a low-cost monitoring biosensor, explaining how each one supports resident safety and effective public health decision-making I can use evidence from case data/research (temperature, stagnation, maintenance factors and limitations of current tests) to refine my targets and trade-offs, clearly stating what my solution must achieve and what it must not compromise.	I can comprehensively specify and defend prioritized criteria and constraints for my Legionella risk-detection solution, including measurable quantitative targets and well-supported qualitative requirements tied to societal needs, safety, and community trust I can evaluate multiple design options by comparing how they meet constraints and trade-offs (cost, reliability, usability, and environmental/safety impacts), and I can clearly explain how my final criteria guide an effective engineering design under realistic NYC Housing Authority conditions.
Next Generation Science Standards	HS-LS4-6 - Create or revise a simulation to test a solution to mitigate adverse impacts of human activity on biodiversity.	I can create a simple simulation of Legionella risk in an apartment water system that shows how one or two factors (like warm temperature or water stagnation) could increase contamination, and I can explain what inputs and outputs represent I can identify at least one way my simulation is connected to biodiversity/environment impacts through water quality effects on microorganisms and ecosystem health.	I can revise my simulation to include multiple interacting factors (such as temperature, stagnation time, and basic maintenance/monitoring frequency) and describe how changes in those inputs affect Legionella risk outputs I can run comparisons between at least two solution scenarios (e.g., more frequent testing or earlier detection) and use results to make a basic claim about mitigating adverse impacts on biodiversity-related ecosystem balance.	I can build and refine a more realistic simulation that models how my proposed low-cost biosensing approach influences detection timing and response actions, using evidence-based assumptions and clearly defined parameters I can test multiple solution versions in the simulation, analyze performance trends (accuracy/reliability proxies, trade-offs, and usability constraints), and justify which solution best reduces risk while considering public health and environmental impacts.	I can create an advanced, revised simulation that captures complex system interactions (within apartment plumbing and between monitoring/response steps) and allows for qualitative and quantitative criteria/constraints to be applied to mitigation effectiveness I can use simulation results to evaluate and iterate my biosensing solution through prioritized criteria and trade-offs (cost, safety, reliability, and practical usability in dense housing), and I can clearly explain how earlier detection reduces adverse impacts on biodiversity via improved water quality and reduced harmful microbial proliferation.
Next Generation Science Standards	HS-LS2-7 - Design, evaluate, and refine a solution for reducing the impacts of human activities on the environment and biodiversity.	I can describe how human activity and building conditions (e.g., warm stagnant water, inconsistent monitoring) increase Legionella risk and explain why earlier detection would protect residents and biodiversity in a shared city environment.	I can design and evaluate a basic monitoring solution by identifying the main problem, proposing a simple biosensing approach, and using clear observations/data from simulated apartment samples to justify whether it is likely to reduce risk.	I can refine my biosensor and design brief by setting qualitative and quantitative criteria (accuracy, reliability, speed, safety, usability) and constraints (cost, materials, feasible school testing) aligned to resident health needs and expert feedback.	I can iteratively improve and justify a comprehensive solution by creating/refining a simulation or testing plan to model how my biosensor results would reduce outbreak impacts, evaluating trade-offs with prioritized criteria, and explaining how the design accounts for societal, cultural, and environmental considerations while supporting future monitoring decisions.
Next Generation Science Standards	HS-ETS1-3 - Evaluate a solution to a complex real-world problem based on prioritized criteria and trade-offs that account for a range of constraints, including cost, safety, reliability, and aesthetics, as well as possible social, cultural, and environmental impacts.	I can use a simple set of criteria (cost, safety, and reliability) to explain which parts of my biosensor design for Legionnaires’ risk are most important for protecting apartment residents I can identify at least one trade-off (for example, lower cost vs lower accuracy) and describe how it could affect decision-making in an NYC Housing Authority setting.	I can prioritize criteria for my low-cost water biosensing solution by explaining how cost, safety, and reliability will be weighed to meet public health needs I can evaluate multiple design options by comparing at least two trade-offs (e.g., test speed vs accuracy, ease of use vs safety procedures) and describe which option best fits societal and environmental constraints.	I can evaluate my biosensor solution using prioritized criteria with evidence from testing on simulated apartment water samples, including reliability and measurement accuracy I can analyze trade-offs across constraints (cost, safety, reliability, and usability), and I can justify how my design reduces Legionella risk while considering social impacts such as resident trust and equitable access for dense housing.	I can evaluate and refine my biosensor solution by using a well-supported decision process that ranks criteria and explains how trade-offs are managed across cost, safety, reliability, and real-world usability I can propose and defend specific improvements based on data and expert feedback, addressing environmental and social impacts (e.g., reduced outbreak risk, practical adoption in NYC Housing Authority buildings) and clearly communicating how my final design best satisfies constraints.
Next Generation Science Standards	HS-ETS1-2 - Design a solution to a complex real-world problem by breaking it down into smaller, more manageable problems that can be solved through engineering.	I can define the engineering problem of reducing Legionnaires’ disease risk in NYC Housing Authority water systems by stating the main need (earlier detection) and naming a few simple factors that contribute to contamination (warm, stagnant water) I can break the challenge into 2–3 basic steps (what to detect, what to measure, and how I will test) using resources available in a school lab.	I can develop a solution plan for earlier, low-cost biosensing by identifying multiple sub-problems (biosensor detection target, sample collection process, and basic data collection) and connecting them to how Legionella risk increases in real water systems I can specify qualitative criteria (e.g., fast results, resident-safety) and quantitative targets (e.g., acceptable error range or time window) that are realistic for school-lab testing.	I can engineer a detailed biosensing design by breaking the complex problem into manageable components and explaining how each component contributes to reliable detection (assay method, controls, data capture, and usability for non-experts) I can test the design using simulated apartment water samples, analyze results for accuracy and reliability, and revise my sub-solutions and criteria based on evidence and expert feedback.	I can design, evaluate, and refine an integrated biosensing solution by clearly managing complex engineering trade-offs among cost, safety, reliability, and practicality for dense NYC Housing Authority settings I can use results from simulations/testing to justify iterative improvements, prioritize criteria, and communicate how my design meets (or does not meet) constraints while addressing potential social and public-health impacts.
Next Generation Science Standards	HS-ETS1-4 - Use a computer simulation to model the impact of proposed solutions to a complex real-world problem with numerous criteria and constraints on interactions within and between systems relevant to the problem.	I can describe how a simple simulation would represent Legionella risk in NYC water systems (e.g., temperature, stagnation, and monitoring gaps) and explain why it is relevant to earlier detection for apartment residents I can identify at least one measurable outcome my simulation should track to support safer decision-making.	I can build or adjust a computer simulation model that includes multiple interacting factors (such as water temperature, time since last use, and maintenance/monitoring practices) and clearly states the criteria and constraints the model must reflect for NYC Housing Authority settings I can run the simulation and interpret whether the proposed biosensing approach is likely to reduce high-risk contamination events, using evidence from simulation outputs.	I can refine my simulation by adding more realistic relationships among system components (e.g., how stagnation affects growth and how detection timing changes outbreak risk) and by specifying both qualitative and quantitative criteria (accuracy, reliability, cost, speed, safety) that shape the design I can compare alternative solution scenarios in the simulation and justify which option best meets prioritized criteria and constraints, explaining trade-offs that matter for residents and staff.	I can create or revise a detailed simulation that models solution impacts across interactions within and between systems (e.g., building conditions, sampling/detection process, and downstream public health consequences) and aligns the model assumptions with expert-informed constraints I can use simulation results to evaluate and iteratively improve my biosensor design brief, clearly communicating confidence, limitations, and how my recommendations support early, low-cost detection and long-term biodiversity/public health protection.
Next Generation Science Standards	HS-LS4-6 - Create or revise a simulation to test a solution to mitigate adverse impacts of human activity on biodiversity.	I can revise a simple simulation of Legionella risk in an apartment water system by changing one factor at a time (like temperature or stagnation) to test whether contamination risk could increase, and I can describe what my simulation suggests using evidence from the model outputs I can explain how the simulation helps decision-making for protecting residents in dense NYC housing (Global Citizen) and identify at least one limitation of my current model (Critical Thinker).	I can create or revise a simulation that includes multiple interacting variables (for example temperature, stagnation, maintenance practices, and sampling frequency) and I can run repeated trials to compare how different monitoring or response options affect predicted Legionella risk I can use the simulation results to make a testable claim about which intervention is likely to reduce high-risk contamination while considering practical constraints like cost and safety (Academically Prepared, Global Citizen).	I can refine my simulation so it more accurately represents how human activity and system conditions influence Legionella growth, and I can justify my model structure using scientific reasoning and available data from case reports or expert guidance I can evaluate how well the simulation tests my proposed low-cost biosensor solution by identifying measurable metrics (such as detection accuracy, reliability, or time-to-detection) and revising assumptions when the results disagree with expected patterns (Critical Thinker).	I can develop a simulation that models proposed biosensor-based monitoring and response strategies using prioritized criteria (accuracy, reliability, speed, safety, and usability) and includes constraints and trade-offs relevant to NYC Housing Authority settings I can use the simulation to compare multiple design options, predict outcomes before testing, and propose targeted refinements to the solution based on results, showing how my thinking and goals evolved through feedback and reflection (Reflective and Future Focused, Academically Prepared).
Next Generation Science Standards	9-12.AF.1.2 - Evaluate a question to determine if it is testable and relevant. (a) Ask questions that can be investigated within the scope of the school laboratory, research facilities, or field (e.g., outdoor environment) with available resources and, when appropriate, frame a hypothesis based on a model or theory. (b) Ask and/or evaluate questions that challenge the premise(s) of an argument, the interpretation of a data set, or the suitability of a design. (c) Define a design problem that involves the development of a process or system with interacting components and criteria and constraints that may include social, technical, and/or environmental considerations.	I can evaluate whether my question about Legionnaires’ disease risk in NYC Housing Authority water systems is testable with school-lab resources and relevant to protecting resident health I can identify one simple idea (model/theory) that could explain how temperature, stagnation, or maintenance relates to Legionella growth.	I can refine my question into a clear testable engineering/science problem and justify why it matters for early, low-cost detection I can propose a basic hypothesis or expected pattern and describe what variables I will measure using available materials and safety guidelines.	I can design an investigation or simulation that directly tests my hypothesis and fits the scope, constraints, and safety limits of my school setting I can challenge my own assumptions by checking whether my design problem and planned measures are appropriate and by explaining how results would address the public-health need for earlier detection.	I can clearly define a comprehensive design problem with interacting system components and prioritized criteria and constraints (e.g., accuracy, speed, cost, usability, and safety) that reflect societal needs and wants I can evaluate the relevance and testability of my question across multiple perspectives (including public health expert feedback) and adjust my hypothesis, variables, and approach when evidence shows my design premises are incomplete.