Influenza and Average Contagion Rate
Population Dynamics Disease Lab http://www.learner.org/courses/envsci/interactives/disease/counter_virus_1.php A. LESSON #1: The Virgin Field
Most diseases begin with what is called "the virgin field"—a scenario in which humans have no natural or man-made immunity to the disease. To see the progress of a disease in a particular community, start by predicting how many sick days will be reported when you run the Kold disease through a medium-sized population, and record your prediction in the data table. In this first run-through, we'll assume that the population does not move around the field; they interact with their neighbors, but do not travel long distances.
Make sure the tableau is set to virgin and run the simulator to 100 days (click on Run button) three times and answer the following:
1. Do you get the exact same results each time? How do the results compare to each other and to your prediction? What factors might contribute to susceptibility to the disease?
2. If the contagion rate is calculated as the number of new cases per day per total population, what would the average contagion rate be for Kold?
Unlike some of the other interactive labs, this model has some randomness built in to reflect the real spread of a disease, which is a matter of probabilities. Despite this variability, you can get a sense for what effect each factor has on disease spread.
Before running the simulator, predict whether the sick days per capita will be higher or lower with low population density.
Record your prediction in the data table and then run the simulator to 100 days three times, recording the data each time.
Make a prediction for high population density; record it in the data table, and run the simulator three times, recording that data in the table. Answer the following:
3. What could be done to prevent the spread of disease in a low population density?
4. What kinds of challenges would high population density present to these precautions?
5. If
Most diseases begin with what is called "the virgin field"—a scenario in which humans have no natural or man-made immunity to the disease. To see the progress of a disease in a particular community, start by predicting how many sick days will be reported when you run the Kold disease through a medium-sized population, and record your prediction in the data table. In this first run-through, we'll assume that the population does not move around the field; they interact with their neighbors, but do not travel long distances.
Make sure the tableau is set to virgin and run the simulator to 100 days (click on Run button) three times and answer the following:
1. Do you get the exact same results each time? How do the results compare to each other and to your prediction? What factors might contribute to susceptibility to the disease?
2. If the contagion rate is calculated as the number of new cases per day per total population, what would the average contagion rate be for Kold?
Unlike some of the other interactive labs, this model has some randomness built in to reflect the real spread of a disease, which is a matter of probabilities. Despite this variability, you can get a sense for what effect each factor has on disease spread.
Before running the simulator, predict whether the sick days per capita will be higher or lower with low population density.
Record your prediction in the data table and then run the simulator to 100 days three times, recording the data each time.
Make a prediction for high population density; record it in the data table, and run the simulator three times, recording that data in the table. Answer the following:
3. What could be done to prevent the spread of disease in a low population density?
4. What kinds of challenges would high population density present to these precautions?
5. If