Lesson Passing the Bug

Quick Look

Grade Level: 11 (9-12)

Time Required: 1 hours 15 minutes

Lesson Dependency: None

A graph plots the number of H1N1 flu cases over time, from 4/24/09 to 6/29/09 with rising colored lines for Australia, Canada, Chile, Mexico, UK, USA, Other, deaths and total.
Development of H1N1 influenza cases during two months in 2009.
copyright
Copyright © (top) National Institutes of Health, (bottom) 2009 World Health Organization via Wikimedia Commons http://www.nih.gov/researchmatters/april2009/04272009influenza.htm http://commons.wikimedia.org/wiki/File:Influenza-2009-cases-logarithmic.png

Summary

Students apply concepts of disease transmission to analyze infection data, either provided or created using Bluetooth-enabled Android devices. This data collection may include several cases, such as small static groups (representing historically rural areas), several roaming students (representing world-travelers), or one large, tightly knit group (representing urban populations). To explore the algorithms to a deeper degree, students may also design their own diseases using the App Inventor framework.

Engineering Connection

Biomedical engineers work with doctors to find engineering solutions that model and affect the spread of disease. Software engineers use their expertise to generate models to help predict the spread, potency and likely carriers of diseases. Engineers use their knowledge of biology, computers, software and design to create simulations to model disease transmission. These models help physicians and public health officials develop the best approaches for allocation of resources and treatment.

Learning Objectives

After this lesson, students should be able to:

  • Describe how diseases are transmitted.
  • Explain how different characteristics of a disease, such as transmission speed and symptom severity, affect its global spread and survival.

Worksheets and Attachments

Visit [www.teachengineering.org/curriculum/print/uno_bug_lesson01] to print or download.

Pre-Req Knowledge

Students should have a basic knowledge of disease from biology class. The teacher and students should know how to load an Android app (provided) and run basic simulations. If experience with MIT's App Inventor is needed, start with the Program Analysis with App Inventor lesson. Find other App Inventor lessons in the TeachEngineering collection by searching for lessons with the keyword "App Inventor."

Introduction/Motivation

(Be ready to show students the 36-slide Flu Trends Presentation, a PowerPoint file. In addition, each group needs a computer with Internet access and an Android device that is Bluetooth capable. In advance, make copies of the Disease Transmission Tracking Worksheet and Disease Transmission Tracking Results for each group.)

How are diseases transmitted? How can we use what we know about biology, human behavior and software programming to analyze the spread of diseases so we better understand their sources, carriers and methods of transmission, and help us predict the spread and strength of diseases so we can develop effective treatments? In this lesson, you will explore how a disease is transmitted and then modify software code to design your own diseases that you will track to see if they respond the way that you expect.

Engineers play an important role in the tracking and modeling of diseases. Biomedical engineers work with doctors to exploit weaknesses in diseases and develop treatments. This might occur by discovering how a disease is transmitted, how a particular disease originated, and how a disease affects the body. Software engineers model how diseases are transmitted. These software models produce simulations with different infection rates and travel patterns to help us understand how a disease might spread.

To begin, you will work in groups to discuss and record information that you know about getting sick.

(Divide the class into groups and provide each group with a topic such as duration, symptoms, who they got it from, number in household who are sick, etc. After several minutes of discussion, give each group its turn to contribute towards building a class knowledge base of disease transmission, so as to compile this information for future reference.)

Next, let's look at some actual influenza data from the U.S. Centers for Disease Control and Prevention (CDC) by week to see how the flu progressed. This presentation contains 33 images for consecutive weeks that show the progression of the geographic disease spread.

(Show students the PowerPoint presentation. After looking at the CDC data, ask students the following questions to help guide a class discussion on disease transmission and whether any other data or information needs to be added to the list.)

Cutaway drawings of two people standing side by side with particles from one person's sneeze being breathed into the nose and lungs of the other person.
Airborne disease transmission via sneezing.
copyright
Copyright © 2013 U.S. Centers for Disease Control, Wikimedia Commons {PD} http://commons.wikimedia.org/wiki/File:Disease_transmission_sneezing.png

  • What patterns do you see in getting sick? (Expected answers and observations: Contact is important, one person is sick first, then others follow, proximity is a factor, etc. The data show how adjacent states become infected, indicating that the disease is being transmitted from person to person.)
  • How do diseases spread? (Answers: Droplet contact - coughing or sneezing on another person; direct physical contact - by touching an infected person, including sexual contact; indirect contact - by touching contaminated soil or a contaminated surface; airborne transmission - when microorganism remains suspended in the air for long periods of time; fecal-oral route - from contaminated food or water; vector borne transmission - carried by insects or infected animals.)
  • What might you do to keep from getting sick? (Possible answer: Minimize contact, wash hands, keep your hands away from your face, etc.)

Next, you will investigate how infectious disease strategies are affected by various movement patterns in a population using a pre-made Android application, Passing the Bug Disease Transmission (apk file), and stock movement information. Then, from the tab marked "Analyze" at the top of the screen, select one of the sample simulations or another simulation, as directed. You may then select a given user to be infected and change the level of infectiousness. A level of 0% means a disease is not communicable and infectiousness of 100% means each contact will result in passing the disease.

You may work individually or in small groups and run the given simulations for a particular set of contacts and record the results and note any patterns. Each group will receive two worksheets to help track the information. You will use the data collected on these worksheets to look at the transmission algorithm in a stepwise fashion followed by analysis of results.

To conclude, you will be given a new disease with different characteristics (infectiousness) and you will predict the new results before running the simulations. Refer to the associated activity Simulating the Bug for more extension learning and design cycle applications. 

Lesson Background and Concepts for Teachers

Disease Transmission: Disease transmission is the passing of a communicable disease from one infected host to another person who may be uninfected or previously infected. The transmission of disease can happen through physical contact, air, water, orally, sexually or other mediums. The host does not have to have disease symptoms in order to transmit it to another person.

Modeling and Simulation: Engineers are on the forefront of helping to predict and stop the spread of disease. Software engineers create models that simulate the spread of disease with different infection rates, travel patterns and lethality calculations. These simulations are critical to understanding where diseases come from and how they might progress. Biomedical engineers collaborate with doctors to understand how diseases interact with the human body, understand how they are transmitted and develop cures.

Trends: The general trend in disease transmission has been investigated. We know that isolated rural areas typically have a suite of pathogens that the community is well-exposed to and immunity to infection has reduced the disease to a low level or the disease has saturated the community. In cases in which a few migrant individuals are present, a regular influx of new pathogens will keep spreading through the population. In densely populated urban areas, disease often spreads through its members at an almost exponential rate in early stages due to the high number of contact events.

Infectious vs. Non-Infectious: The two major classifications of disease are non-infectious and infectious. Non-infectious diseases include those that are either related to genetics (such as sickle-cell anemia or ALS) or environment (such as allergies or obesity). Infectious diseases are those that are caused by pathogens that are typically organisms such as bacteria (such as the common cold), fungi (such as athlete's foot), protists (such as malaria) or viruses (such as AIDS) in a host organism. Infectious diseases may be passed from one organism to another much more quickly than non-infectious genetic diseases that can only be passed to offspring.

Disease Transmission Factors: Diseases employ many strategies to be transmitted from hosts. Several factors that contribute to transmission include:

  • Method of transmission: air, water, direct contact, vectors and others
  • Infectiousness: how easily the pathogen is transmitted
  • Incubation time: how long the disease takes to develop or become communicable
  • Symptoms: may spread the disease or keep others away
  • Course of infection: how long the disease is communicable

Example Disease Strategies: Diseases may exhibit strategies from "slow to spread with minor symptoms" (such as cold sores) or "fast to spread with severe symptoms" (such as Ebola). Generally, the most successful diseases are "quick to spread with minor symptoms." Influenza is an excellent example of this, with millions of cases per year throughout the planet. Even though Ebola has only a 30% survival rate, its extreme symptoms and quick course of infection keep the disease from becoming a worldwide epidemic.

Lesson Simulation: This simulation uses Bluetooth discovery between devices as a vector to disease. All contact events are logged in chronological order. Later analysis allows users to assign "infectiousness" settings that use a pseudorandom number generator to create a number between zero and 100. If the number generated is less than the "infectiousness" level, the transmission succeeds and the uninfected individual is tagged as infected. If the number generated is greater than the "infectiousness" level, the uninfected individual remains uninfected. For additional resources, refer to the website listed in the Additional Multimedia Support section.

Vocabulary/Definitions

communicable: Able to be passed from one organism to another.

epidemiology: The study of the patterns involving health events such as disease.

host: An organism that is infected with a pathogen.

immunity: The ability of an organism to resist infection.

infectious disease: A disease that is caused by an organism such as bacteria or viruses invading another organism.

pathogen: An organism that causes a disease.

transmission: The process of transferring a pathogen from one host to another.

vector: A different species of organism that can move a pathogen between hosts.

Assessment

Formative Assessment

Observations: As students are engaged in learning activities, ask yourself (or students) questions such as the following:

  • Do students understand the individual factors that help or impede disease transmission?
  • Can students state in what circumstances a particular trait would be beneficial to transmission / disease survival?
  • Can students explain the meanings of the disease transmission vocabulary?

Summative Assessment

Essay Questions: Assign students to individually complete one or more of the following essay questions about disease transmission. Review their answers to gauge their mastery of the subject matter.

  1. Given a particular movement pattern for a population, what strategies might a disease employ to best infect the population? (Example answer: A disease that is highly infective will be more successful in a rapidly moving population, whereas a disease in a population with slower moving members may be successful with a less-aggressive transmission.)
  2. Find information on the characteristics of a real disease and describe how well it would do in the different population movements. Report your findings. (Example answer: Ebola is a highly infectious disease transmitted through contact with infected bodily fluids. It has a short infectivity cycle and high mortality rates in humans; along with this is a suite of very noticeable symptoms. In a slow-moving population, the epidemic burns out very quickly. In populations in which members move more rapidly, it may spread more than in an isolated population, but the symptoms readily lead to the avoidance of infected persons, leading to a slowing/ending of the epidemic.)
  3. Describe how to best stop the spread of a disease given a certain population movement case. (Example answer: In highly mobile populations, it is easier to identify and isolate members of the population that are infected. In less-mobile populations, preventing contact with uninfected persons entering the area may control a disease.)
  4. Consider the Android app you used in the lesson. Explain how software engineers can be involved in understanding and preventing the spread of disease. (Example answer: Software engineers take existing information about a known disease and use it to develop models that can be used to predict future disease behavior. Different parameters are developed [likelihood of transmission, mode of transmission, travel patterns, lethality, etc.] that can be varied to see different mutations of the disease and make predictions about the future of the disease.)

Additional Multimedia Support

Google App Engine - database for simulations - use the default server (data remains for 15 days) located at http://ret2012btdb.appspot.com/. All source code and applications are available here, too.

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Copyright

© 2013 by Regents of the University of Colorado; original © 2012 Board of Regents, University of Nebraska

Contributors

Douglas Bertelsen

Supporting Program

IMPART RET Program, College of Information Science & Technology, University of Nebraska-Omaha

Acknowledgements

The contents of this digital library curriculum were developed as a part of the RET in Engineering and Computer Science Site on Infusing Mobile Platform Applied Research into Teaching (IMPART) Program at the University of Nebraska-Omaha under National Science Foundation RET grant number CNS 1201136. However, these contents do not necessarily represent the policies of the National Science Foundation, and you should not assume endorsement by the federal government.

Last modified: June 27, 2019

Hands-on Activity Simulating the Bug

Quick Look

Grade Level: 11 (9-12)

Time Required: 1 hours 15 minutes

Expendable Cost/Group: US $0.00

The activity also requires non-expendable (reusable) computers and Android devices; see the Materials List for details.

Group Size: 3

Activity Dependency: None

A screen capture image shows the pattern of disease transmission generated using a mobile Android app.
Screenshot showing who was infected.
copyright
Copyright © 2012 Douglas Bartelsen, University of Nebraska

Summary

Students modify a provided App Inventor code to design their own diseases. This serves as the evolution step in the software/systems design process. The activity is essentially a mini design cycle in which students are challenged to design a solution to the modification, implement and test it using different population patterns The result of this process is an evolution of the original app.

Engineering Connection

Engineers follow a design process to solve problems. The software/systems engineering design process includes the steps of analysis, design, implementation, testing and evolution. This activity focuses on the evolution step, which is often overlooked by practitioners.

Epidemiologists track the spread of diseases using data from doctors, hospitals and other sources. With enough data, they can develop models that predict the speed and breadth of an epidemic. With these models in hand, software engineers create programs to display and analyze current and past data. Software engineers collaborate with epidemiologists to improve or adjust the models as necessary, as new data suggest changes. These models enable public health officials to track infections and more importantly, attempt to prevent or reduce the impact of diseases on individuals.

Learning Objectives

After this activity, students should be able to:

  • Follow the design process to modify an App Inventor app.
  • Analyze data collected by an Android app manually or by developing an algorithm, and identify how this analysis compares to the same data analyzed by the application.

Materials List

Each group needs:

For the teacher's use:

Worksheets and Attachments

Visit [www.teachengineering.org/curriculum/print/uno_bug_lesson01] to print or download.

Pre-Req Knowledge

A working knowledge of App Inventor, which can be gained by completing many of the tutorials on the MIT website listed in the Additional Multimedia Support section. Several other lessons in the TeachEngineering collection use App Inventor. For example, Program Analysis Using App Inventor is an excellent lesson for students or teachers to learn the ins and outs of App Inventor.

Introduction/Motivation

The world around us is very complex with large numbers of variables and objects, even in some small-scale systems. Scientists and engineers use models to simplify the task of understanding how these systems function or designing software and hardware to solve problems involving these systems.

One such complex system in biology is a population. Tracking each individual would be time-consuming and calculation-intensive. Epidemiologists develop models to predict how diseases spread in populations; then they test the models and improve them as more data is collected and compared to predictions.

A circular diagram shows the steps of: Requirement Analysis, Design, Implementation, Testing, and Evolution. In the center: SDLC: Software/System Development Life Cycle.
The steps of the software development cycle.
copyright
Copyright © 2012 Cliffydcw Wikimedia Commons http://commons.wikimedia.org/wiki/File:SDLC_-_Software_Development_Life_Cycle.jpg

In general, disease transmission models can be applied to different areas, but when drilling down to the specific neighborhoods or individuals, models often fail in their predictions. Thus, the models for small, isolated populations are different than those for large, dense urban populations.

In this activity, you will play the part of an epidemiologist and software engineer by collecting data and writing an algorithm to help you analyze it. You will design a modification to a disease (provided) by modifying an Android app using App Inventor. In doing so you will apply the software/systems design process, which is cyclical with all steps being equally important. The activity will focus you on the evolution phase in which a solution (in this case an Android app) will be modified to make it apply in a different way/situation. This is similar to how software engineers collaborate with epidemiologists to analyze large amounts of data and make predictions on the spread of diseases. Then you will discuss ways of reducing the spread of disease.

Diseases often evolve and change into different strains that require different medical treatments. An example of this is influenza, which continually has different strains enter into existence or disappear, only to re-emerge later. These new (and old) strains must be tracked and simulated. The well-known breakout of the H1N1 flu is one instance in which a new strain emerged and great effort and expense was employed to simulate the spread of the disease in order to develop a treatment.

In this activity, you will simulate part of the job of a software engineer. Software engineers produce models that can be used to predict patterns in disease transmission, determine lethality of the disease, and learn the origins of the disease. These models are critical for the development of cures. Biomedical engineers work with doctors to discover how the disease spreads, how it affects the human body and develop cures. How do you think these models are developed? Does one model fit all diseases or do they need to be customized?

Procedure

Teacher Background Information: App Inventor Attachment Information

  • App Inventor base app source: Simulating the Bug Empty Algorithm Source (zip) - This is the source code for the algorithm designers that students may modify in App Inventor. It requires App Inventor.
  • App Inventor base app binary: Simulating the Bug Empty Algorithm Binary (apk) - This pre-built App Inventor app has no algorithm; it is provided to show/test default behavior. It requires an Android device or emulator.
  • App Inventor example app source: Simulating the Bug Full Algorithm Source (zip) - This is the source code for the bare-bones algorithm that students may modify in App Inventor. It requires App Inventor.
  • App Inventor example app binary: Simulating the Bug Full Algorithm Binary (apk) - This is a pre-built App Inventor app that will apply the bare-bones algorithm to a given dataset. It requires an Android device or emulator.

Before the Activity

  • Install App Inventor on the computers that student groups will use to modify a disease and then track the results. They will also need the apk and zip files mentioned above.
  • Make copies of the Disease Transmission Tracking Worksheet (which students use to manually record contact events to manually analyze or to help with algorithm creation) and the Disease Transmission Tracking Results (which students use to manually track infection events from the tracking worksheet or to check algorithm results). Instructions for using sheets: Students can use the tracking worksheet as a practice exercise to help develop an algorithm for checking and passing on the infection. You may simulate a small-scale study with them in the classroom and using physical proximity (closer than arm-length to designate a contact event) before using the application with Bluetooth. They may then use the tracking results sheet to assist them in data organization.
  • Review the App Inventor Cheatsheet, which outlines how to create a bare-bones algorithm with App Inventor. The cheatsheet is intended to inform the teacher on what constitutes a working algorithm, but may be used with students who have not been exposed to designing algorithms. This algorithm can also serve as a skeleton on which to add more functionality, such as disease immunity or recuperation. Customize its use to the needs of your students.

With the Students

  1. Divide the class into groups of three.
  2. Direct student teams to use App Inventor to design their own diseases with unique transmission characteristics by altering the full algorithm version (use the Simulating the Bug Full Algorithm Source and Simulating the Bug Full Algorithm Binary) through step-by-step procedures for calculations that take into account different disease properties such as ease of transmission, length of contact required, and possibly accounting for immunity.
  3. Next, have groups test the disease algorithm's success using the Android data collection app or by using some of the pre-loaded examples that may be selected from the "Analyze" screen (general movement patterns provided) from the app, or by using data that was collected in class using the associated lesson's disease transmission app (apk) during the Passing the Bug lesson.
  4. Direct groups to record the success of their diseases for different population movement patterns. The simplest way to do this is to run the analysis program and record the maximum number of infected individuals or by determining the amount of time it takes to infect a given fraction of the population to become infected. Graphing the number of infections as a function of time can perform more detailed analysis of the transmission pattern. As an example, constraining contact patterns in a hallway often give different results than those in an open gym. Typical patterns:
  • mall, compact group: steep-sloped linear or sigmoidal
  • individuals in a linear pattern: flatter-sloped linear
  • small groups with traveling infected: stepped increase as new groups are infected
  1. Depending on infectiousness and minimum number of contacts, some diseases may transmit better if individuals are in contact for longer periods of time rather than brief contacts with wide-ranging movement.
  2. As time permits, further activities include comparing with other students and/or customizing their diseases for different simulations. For example, you can change the infectiveness of your disease and test how a disease progresses in the different population structures (urban, rural, world-traveler) if it is highly infectious or more difficult to spread.
  3. Conclude with a brief writing assignment, as described in the Assessment section.

Vocabulary/Definitions

communicable: Able to be passed from one organism to another.

epidemiology: The study of the patterns involving health events such as disease.

host: An organism that is infected with a pathogen.

immunity: The ability of an organism to resist infection.

infectious disease: A disease that is caused by an organism such as bacteria or viruses invading another organism.

pathogen: An organism that causes a disease.

transmission: The process of transferring a pathogen from one host to another.

vector: A different species of organism that can move a pathogen between hosts.

Assessment

Pre-Activity Assessment

Questions: As a quiz or discussion questions, ask students about how the design process relates to creating and testing software.

  • What are the steps that software engineers follows in the software/systems design process? (Answer: Problem analysis, design, implementation, testing and evolution.)
  • Why is the evolution phase so important to software engineers? (Answer: This is the phase when solutions can be applied to fit different problems. Past experiences and solutions can be used to help solve different problems. By beginning with a similar solution, new solutions are easier to develop.)
  • Why does the design process work well in the evolution phase? (Answer: Evolving a solution is a logical conclusion for the designed solution. To properly complete the evolution phase, similar problems must be analyzes, solutions designed, implemented and tested.)

Post-Activity Assessment

Writing: Assign students to complete the following writing prompts:

  1. Explain how you applied the design process in this activity. (Example answer: The design process was applied in two ways. First, it was partially applied by focusing on the evolution step. To accomplish the evolution step, a second mini design process was completed when I analyzed the changes I wanted to make. I designed a solution and implemented it. Analysis of the results of the modification was like the testing phase.)
  2. Explain how you modified the disease that is simulated in the App Inventor app in this activity and the results of your analysis. (Answers may vary widely from the example answers. Example answer 1: I required that my disease was only capable of being transmitted to users having an odd number. This simulated a population in which half of the members were immune to the disease, which resulted in it being much more difficult to transmit. Example answer 2: My algorithm counted the number of contacts between infected and uninfected users and only passed the disease on after three contact events. This made my disease easier to spread in groups with little movement and more difficult to spread to users moving quickly through an area.)
  3. Relate your experience in this activity to the real world. How important do you think software engineering and the development of these models and simulations are in the research and prevention of diseases, spread of diseases, epidemics? (Example answer: The development of these simulations and models is critical to understanding how diseases are transmitted and how diseases will likely progress. If the medical community has a glimpse, albeit an educated guess, they are able to determine if quarantines are needed, how to educate the populace and to hopefully develop cures more quickly.)

Troubleshooting Tips

A description of the different methods in the App Inventor code is available by clicking on the question mark on the algorithm block in App Inventor.

Additional Multimedia Support

See additional resources at the MIT App Inventor website, http://appinventor.mit.edu/, including instructions and tutorials for installing App Inventor (see http://appinventor.mit.edu/explore/setup-mit-app-inventor.html).

Subscribe

Get the inside scoop on all things TeachEngineering such as new site features, curriculum updates, video releases, and more by signing up for our newsletter!
PS: We do not share personal information or emails with anyone.

Copyright

© 2013 by Regents of the University of Colorado; original © 2012 Board of Regents, University of Nebraska

Contributors

Douglas Bertelsen

Supporting Program

IMPART RET Program, College of Information Science & Technology, University of Nebraska-Omaha

Acknowledgements

The contents of this digital library curriculum were developed as a part of the RET in Engineering and Computer Science Site on Infusing Mobile Platform Applied Research into Teaching (IMPART) Program at the University of Nebraska-Omaha under National Science Foundation RET grant number CNS 1201136. However, these contents do not necessarily represent the policies of the National Science Foundation, and you should not assume endorsement by the federal government.

Last modified: May 22, 2019