Summary
Overview
What exactly is a vaccine? Can vaccines prevent outbreaks? How effective does a vaccine need to be to help a population during an outbreak? Students will explore these questions and more in this lesson plan by first learning the biology behind vaccines. They will then use SimPandemic, a free online tool, to model different vaccine parameters to understand how vaccines affect both individuals and populations during a COVID-19 outbreak.
Remote learning adaptation: This lesson plan can be conducted remotely. Students can work independently on the Explore section of the lesson plan using the Student Worksheet as a guide. The Engage and Reflect sections can either be dropped entirely, done in writing remotely, or be conducted over a video chat.
Learning Objectives
- Explain how vaccines interact with the immune system.
- Differentiate between how vaccines protect individuals and populations.
- Investigate how parameters like vaccine effectiveness and percentage of the population that has been vaccinated can affect the outcomes of viral outbreaks.
NGSS Alignment
This lesson helps students prepare for these Next Generation Science Standards Performance Expectations:- MS-LS2-1. Analyze and interpret data to provide evidence for the effects of resource availability on organisms and populations of organisms in an ecosystem.
- MS-LS2-4. Construct an argument supported by empirical evidence that changes to physical or biological components of an ecosystem affect populations.
- HS-LS2-8. Evaluate evidence for the role of group behavior on individual and species' chances to survive and reproduce.
| Science & Engineering Practices | Disciplinary Core Ideas | Crosscutting Concepts | |||
| Science & Engineering Practices | MS Developing and Using Models. Develop and/or use a model to generate data to test ideas about phenomena in natural or designed systems, including those representing inputs and outputs, and those at unobservable scales HS Developing and Using Models. Develop, revise, and/or use a model based on evidence to illustrate and/or predict the relationships between systems or between components of a system |
Disciplinary Core Ideas | MS LS2.A: Interdependent Relationships in Ecosystem. Organisms, and populations of organisms, are dependent on their environmental interactions both with other living things and with nonliving factors. HS LS2.D: Social Interactions and Group Behavior. Group behavior has evolved because membership can increase the chances of survival for individuals and their genetic relatives. |
Crosscutting Concepts | MS Cause and Effect. Cause and effect relationships may be used to predict phenomena in natural or designed systems. Systems and System Models. Models can be used to represent systems and their interactions—such as inputs, processes, and outputs—and energy and matter flows within systems. HS Cause and Effect. Cause and effect relationships can be suggested and predicted for complex natural and human designed systems by examining what is known about smaller scale mechanisms within the system. Systems and System Models. When investigating or describing a system, the boundaries and initial conditions of the system need to be defined and their inputs and outputs analyzed and described using models. |
Materials
- Computer with internet connection
- Student worksheet
Background Information for Teachers
This section contains a quick review for teachers of the science and concepts covered in this lesson.Vaccines are a key part of preventative medicine. They prime an individual's acquired immune system so that it has antibodies to recognize and fight off a potential pathogen without ever having to experience the harmful, or even deadly, symptoms of the disease.
There are several ways to create vaccines, including using weakened (sometimes called attenuated) versions of the pathogen, a dead pathogen, or only subunits of the pathogen that present antigens that the immune system can react against. All vaccines, regardless of how they are produced, have to go through extensive testing to prove both their effectiveness and their safety. Because vaccines are given to healthy people as a preventative measure, they are held to high standards of safety and probability that they provide more benefit than risk. Prior to approval, vaccines are tested in thousands of individuals to ensure there are no major side effects; minor side effects, like fever or muscle soreness, are okay.
In public health, vaccines are considered to act at two different levels: 1) the individual level and 2) the population level. As an individual, once you are vaccinated, immunity does not set in immediately. There is a period of several days or weeks during which your body may mount an immune response to the vaccine. If a vaccine is effective, this immune response will be sufficient to build long-term memory and immunity to the pathogen. During that time, individuals are not immune, and can still contract the disease, until the immune response has taken place. Furthermore, there is a chance that the vaccine will not work for an individual. A vaccine's effectiveness is measured by the percentage of people who successfully become immune. The effectiveness of the measles vaccine is approximately 98% after two doses. In contrast, the yearly vaccine for the flu virus has ranged from 10% to 60% since 2010.
For those who cannot be vaccinated (often infants or those who are immunocompromised) or for whom the vaccine is not effective (many vaccines are less effective in elderly populations), vaccines can still be helpful at a population level. How impactful vaccines are at a population level is directly correlated to both their effectiveness and the percentage of the population that has been vaccinated. The higher the percentage of vaccinated people in the population, the larger the pool of immune individuals. Immune individuals cannot catch or spread a disease and, subsequently, slow or even halt the spread of an outbreak. In this lesson plan, students will explore this phenomenon by running simulations using SimPandemic.
You will see that students obtain slightly different results, even when they have the same inputs for SimPandemic. Many events in the real world and in a simulation of the real world are based on chance. When you become infected in the real world, you often don't know when or where the infection occurred. Perhaps someone sneezed when you were randomly walking by them. A simulation cannot predict that you were going to get infected (except in special cases), but it can predict fairly well that someone would get infected. In SimPandemic there are many events where the simulation literally rolls virtual dice to determine when an infected individual will transmit the disease to another (all within the bounds specified by the input parameters). To better understand the assumptions and parameters involved in SimPandemic, read the FAQ.
