Total Laboratory Minutes: 120 Spread of Infectious Disease Introduction Epidemiologists study the causes and the spread of diseases through populations. By doing this, they can help to control and prevent diseases. Though epidemiologists may study diseases not caused by microbes, the simulation you will be doing is a simple model of a microbial epidemic. Infectious diseases are caused by pathogenic microorganisms, such as bacteria, viruses, parasites or fungi; the diseases can be spread, directly or indirectly, from one person to another. Zoonotic diseases are infectious diseases of animals that can cause disease when transmitted to humans. R0, pronounced “R naught,” is a mathematical term that indicates how contagious an infectious disease is. It’s also referred to as the reproduction number. As an infection is transmitted to new people, it reproduces itself. R0 tells you the average number of people who will contract a contagious disease from one person with that disease. It specifically applies to a population of people who were previously free of infection and haven’t been vaccinated. ● Measles – 12-18 ● Chickenpox – 10-12 ● Polio – 10-12 ● HIV/AIDS – 2-5 ● SARS – 0.19-1.08 ● MERS – 0.3-0.8 ● Common Cold – 2-3 ● Ebola – 1.56-1.9 ● Seasonal Influenza – 0.9-2.1 ● 1918 Influenza Pandemic – 1.4-2.8 ● 2009 Influenza Pandemic – 1.4.1.6 ● COVID19 – 0.4-9.0 The current R-naught for the Delta variant falls between five and nine and the Omicrom variant between seven and eight according to recent documents from the United States Centers for Disease Control and Prevention (U.S. CDC). Skill This lab will simulate the spread of an infectious disease in which the disease can spread from one infected person to other people, who in turn infect others. For this simulation, we will assume that: ● There is only ONE patient zero ● The disease spreads through contact with an infected individual Total Laboratory Minutes: 120 Procedure Part A: 1. Each student will receive a cup filled with a clear solution and a fictitious name written on the side. This solution represents body fluids. Only one person in the group will have a cup that has been “infected”. 2. At the signal you will have 6 minutes to interact with 3 different people, one at a time. To interact with another student, pour all of your solution into your partner’s cup. Then have your partner pour all of the mixed solution back into your empty cup. Finally, pour half of the mixed solution back into your partner’s empty cup. NOTE: Try to interact with people from different “parts” of the room. The difficulty of determining “patient zero” becomes exponentially more difficult if you simply do a “round robin” interaction within a trio! 3. Record the names of the people you interact with in the correct order in Data Table 1. You may want to look at the other person's chart before you interact to make sure you do not have any of the same names as they do in previous interactions. If you do, consider interacting with another person. 4. Predict how many people you think will be infected after each student has interacted with three other students. Record this number in the Data Table 2. 5. Each student cup will now be tested with an “infection indicator”. If you have exchanged solutions with someone who was infected or if you were originally infected, your solution will fizz. If you are not infected, your solution will not fizz. 6. Class data for infected and non-infected people will be collected as a group. Record the number of people affected in the data table. 7. Based on the results of the round with three interactions, students with infected cups will be asked to name the students in order that they exchanged with and those names are written down on the board. Record these lists in the Class Data section. Use this information to create a flowchart that represents the spread of the infection. Part B: 8. Epidemiologists can often narrow the possible “patient zero” to two different individuals, but are unable to with certainty state who the original “patient zero” was. They can sometimes examine titer levels of antibodies in each of the patients to help determine “patient zero”. In theory “patient zero” has been infected longer and may have more antibodies. Since this is a simulation we have the luxury to repeat the experiment a second time. During this simulation we will repeat steps 1-8 interacting with three DIFFERENT people. In the end only one name will appear again. 9. Record the names of those you interact with in Data table 3. Remember you should compare your tables during your interaction to not have overlap. Additionally, you should aim to interact with different people then you did in Part A as much as possible. Total Laboratory Minutes: 120 Results & Analysis Data Table 1: Order of People in Contact for Part A with 3 Interactions Interaction Name 1 2 3 Data Table 2: Number of Infected People: Part A Number of Interactions Estimated Number of People Infected Actual Number of People Affected 3 Data Table 3: Order of People in Contact for Part B with 3 Interactions Interaction Name 1 2 3 Data Table 4: Number of Infected People: Part B Number of Interactions 3 Estimated Number of People Infected Actual Number of People Affected Total Laboratory Minutes: 120 Class Data: Part A Infected people Who they interacted with Final Summary Flow chart for Disease Transmission The flow chart should only contain infected individuals Name of Person with First Infected Cup ____________________________ Total Laboratory Minutes: 120 Class Data: Part B Infected people Who they interacted with Final Summary Flow chart for Disease Transmission The flow chart should only contain infected individuals Name of Person with First Infected Cup ____________________________ Total Laboratory Minutes: 120 Analysis Questions 1.In some ways, the spread of an infectious disease is similar to population growth. Suppose that a single bacterium is placed in a container with a lot of food. Every 30 minutes, each bacterium in the container divides into two bacteria. Therefore, population size doubles every 30 minutes. Complete this table to show how many bacteria there will be at each time if the number of bacteria doubles every 30 minutes. 3. Time 0 min. 30 min. # Bacteria 1 2 1 hr. 1 hr. 30 min. 2 hr. 2 hr. 30 min. 3 hr. 3 hr. 30 min. 4 hr. 4 hr. 30 min. Fill in the “Increase in # bacteria” blanks. Increase in # bacteria ___ ___ ___ ___ ___ ___ ___ ___ ____ 4. Why did population size increase slowly at the beginning and more rapidly at later times? 5. Create an appropriate scale for the dependent axis with no breaks 6. Plot the number of bacteria and connect the points to show the population growth curve. 7. Title the Graph 8. In this example, population size doubled every 30 minutes. This type of population growth is called ___________________ growth. _____ 5 hr. Total Laboratory Minutes: 120 9. A real population of bacteria cannot keep increasing exponentially forever. Why not? 10. List 2 non-infectious diseases. ____________________________ ____________________________ 11. What are 3 ways that infectious diseases are transmitted? 12. What is the single best way to prevent the spread of an infectious disease? 13. In addition to exposure to germs or pathogens, what other factors influence your risk of getting an infectious disease? In other words, why don’t you get sick every time you come into contact with a pathogen? 14. What is contained in a vaccination that helps to control the spread of different infectious diseases?
