Disease

In this lesson you will study the role that contagious disease can play in the growth and stability of a population. You will use a simulation program from Gingerbooth.com; the same organization that created the Food Web program you used earlier this year. Take notes as you read this information and answer the questions listed in each lesson. 

Link to Excel spreadsheet: Disease Book.

Lesson One: Getting To Know The Disease Simulation

This lesson is designed simply to get familiar with the controls of the simulation program. The following lessons will ask you to set the controls to specific values in order to test our class hypotheses. Go to the Gingerbooth.com web site and select the "Disease Lab" simulation. On the right side of the screen you should see a box with the population filled with dots (green = healthy but at risk, red = sick and contagious, gray = recovered and immune). Above this section you will see the statistics for the population; "sick days" means the total number of days each individual was sick added up over the total population. "per capita" refers to the average number of days individuals were sick. On the left hand side of the screen are your controls. You can select the disease (Kold, flu, red death), population density (we will always use medium for these lessons) and the population mixing (we will always use medium for these lessons). The graph will track the population for 100 days. Using the "details" you can control how long a person is contagious, the rate of transmission, and the death rate.

The Excel spreadsheet available for your data. Be sure that you save this to a file on your computer or an USB drive. Don't try to use the on line file; you cannot save it for future use. This spreadsheet will be the "Results" section of your lab report.

Using Kold as your disease, run the program several times using various settings from the Details panel. Once you are comfortable with the simulation program, we can move onto the next lesson.

Lesson Two: Role of Sick Days
Sick days refers to the number of days a person with the disease is sick and contagious. 

Hypothesis 1: As the number of sick days increases the total number and per capita sick days will increase as will the number of deaths. In other words, if individuals stay sick for a longer period of time, the total number of days people in the population are sick will increase and more people will die.

Test: Keep transmission rates and death rates at the default values of 20% and 3%. Run the simulation at sick day values of 3, 6, and 9 days. Run three replicates at each value for a total of nine simulations.

Record your data on the Excel data sheet. This spread sheet will automatically calculate the averages for the three replicates you did at each of the three values for sick days and then produce a bar graph of these data. Be sure you enter your data in the correct boxes (Hypothesis 1: 3 sick days, 6 sick days, and 9 sick days).

  1. Does the data support the hypothesis that increasing the number of days each individual is sick will also increase the total number of sick days in the population? Explain your answer using the data and graphs you have recorded.
  2. Does the data support the hypothesis that increasing the number of days each individual is sick will also increase the number of deaths in the population? Explain your answer using the data and grahs you have recorded.
  3. Explain why school and business administrators often will encourage their employees to stay home if they begin to feel sick rather than waiting until they come down with more serious symptoms at school or work. Be sure you relate your answer to the data you have collected.

Lesson Three: Role of Transmission Rate
Transmission rate refers to the probability of catching the disease from an infect person.

Hypothesis 2: As transmission rates increases the total number and per capita sick days will increase but death will remain the same. In other words, if it is easier to transmit the disease to another person, the total number of days people in the population are sick will increase, but the number of people who die will not significantly change.

Test: Keep sick days at the default value of 3 days and the death rate at the default value of 3%. Run the simulation at transmission rates of 10%, 20%, and 40%. Run three replicates at each value for a total of nine simulations.

Record your data on the Excel data sheet. This spread sheet will automatically calculate the averages for the three replicates you did at each of the three values for transmission rate and then produce a bar graph of these data. Be sure you enter your data in the correct boxes (Hypothesis 2: 10% transmission, 20% transmission, and 40% transmission).

  1. Do your results support the two hypotheses regarding the effect of transmission rates on total sick days and deaths in the population? Explain your answer using the data and graphs you have recorded.
  2. Some diseases such as the flu and measles have extremely high transmission rates. Use the data you have collected to explain why these diseases are often found among school aged children.

Lesson Four: Role of Death Rates
Death rate refers to the probability that a person who has contracted the disease dies.

Hypothesis 3 : As death rate increases the number of deaths in the population will increase but sick days will stay the same. In other words, if the chance that an individual who is sick will die increases, the total number of days people in the population are sick will not change, but the number of people who die will increase.

Test: Keep sick days at the default value of 3 days and transmission rate at the default of 20%. Run the simulation at death rates of 3%, 6%, and 9%. Run three replicates at each value for a total of nine simulations.

Record your data on the Excel data sheet. This spread sheet will automatically calculate the averages for the three replicates you did at each of the three values for death rates and then produce a bar graph of these data. Be sure you enter your data in the correct boxes (Hypothesis 3: 3% death rate, 6% death rate, and 9% death rate).
  1. Do the data support your hypotheses regarding the effect of death rates on total number of sick days and deaths in the population? Explain your answer using the data and graphs you recorded.
  2. Although it may seem a cruel way to look at things, in some cases it is a good thing that diseases that have a very high death rate (eg Ebola, smallpox) kill their victims quickly. Using the your results, explain why a very high death rate may actually slow the spread of a disease.
Lesson Five: Does Vaccination Help Control the Spread of Disease
In this lesson you will explore the role of vaccination have in controlling the spread of disease in the population.

Go to the top of the screen and find the box titled "Virgin Field" (this means that no one in the population has had the disease and no one is immune). Click on this box and select "Vaccinations." Notice that your control box now has an additional option to vaccinate the population.

Hypothesis 4: In this lesson you propose your own hypothesis. Suggest what will happen to the total number of sick days and the number of deaths in the population as the percentage of vaccinated individuals increases from 0% to 50%. In other words, propose a hypothesis that predicts what will happen to the total number of days people in the population are sick and what will happen to the number of people who die in the population as the the percent of people vaccinated increases from 0% to 50%.

Control Group: First you need to establish a control group. Set your values as follows: Sick days 3, Transmission rate 20%, and Death rate 6%. Be sure you keep these settings the same for all of the simulations in this lesson. Run this control simulation three times and record your data on the Excel data sheet.

Test: Now run the program using the same the default settings you used above with 5%, 10%, 25% and 50% vaccinations. Run 3 replicates for each value, record your data, and evaluate your hypothesis.

Record your data on the Excel data sheet. This spread sheet will automatically calculate the averages for the three replicates you did at each of the four values for % vaccinations and then produce a bar graph of these data. Be sure you enter your data in the correct boxes (Hypothesis 4: 0% vaccination, 5% vaccination, 10% vaccination, 25% vaccination, and 50% vaccination).
  1. Clearly state your hypotheses.
  2. Do your results support your hypotheses? Explain using the data and graphs you have recorded.
  3. Does the rate of vaccination have a directly proportional effect on sick days or death? In other words, does a 10% vaccination rate have twice the effect as a 5% rate or does a 50% rate have five times the effect as a 10% rate? Explain using your results.
  4. If you were a medical consultant for the Boston school system, what minimum vaccination rate among the school children would you recommend to reduce the spread of diseses such as chicken pox and measles? Explain using your results.