This model simulates the impacts of hospital inpatient capacity, isolation, and quarantine on the infectious disease outbreak dynamics, such as the COVID-19 pandemic. The infected cases include both carriers, the infected people who have not shown symptoms, and sick, the infected people who have shown symptoms.
Grades: 9-12;
The model starts with a human population in which all individuals are healthy but susceptible (green persons) to the incoming pathogen. Once a carrier (also green but can be shown as gray by the "show-carriers?" switch) appears in the population, it will pass the disease to one of the susceptible people nearby (within a radius of 1.5) at the transmission rate of 90%. The infected people are able to transmit the disease for 14 days if they are not hospitalized or isolated. The infected people do not show symptoms in the first three days but are still contagious. After three days, infected people are more likely to show symptoms as time passes. Once they show symptoms, they are sick, indicated by an orange color. Depending on the settings, the sick can be hospitalized, isolated, or left by themselves. By the 15th day of being infected, the sick people either die (disappear from the model) at the mortality rate of 20% or recover and become immunized (blue color). If sick people are hospitalized, their mortality rate is lowered to 10%.
To simplify the model, this model uses a fixed transmission rate and mortality rate, 90% and 20%, respectively.
Buttons, Sliders, and Switches:
The “population size” slider is self-explanatory. So are the buttons of “Set up/Reset”, “Run/Pause”, and “Run one day”
The “mobility” slider controls how far an individual can move each time. Smaller mobility means people come into contact with fewer other people.
The " hospitalization?" switch can enable and disable hospitalization. The hospital inpatient capacity is set as 5% of the population size. This is actually higher than the USA average hospital inpatient capacity, which is about 0.3%.
The " show-carriers?" switch may make the carriers visible or invisible.
The " %-isolated" slider set how many percent of sick people who are not hospitalized are isolated. Sick people stop infecting susceptible people once isolated.
The " %-quarantined " slider set how many percent of carriers are quarantined. Carriers stop infecting susceptible people once quarantined.
The “+1 infected case” button adds a carrier into the population.
The "Watch 1 infected case " button allows you to focus on a single infected person, either a carrier or a sick person.
First, choose the factors, such as population size, mobility level, hospitalization on or off, etc.
Click on "Set up/Reset", then "Run/Pause". The model is initially set to stop on the 180th day. Change the number in "Time" if you want to run the model for a longer or shorter time period.
Observe the infection changes in the population in the plot and monitors.
Use "Run one day" to run the model in a controlled way and collecting day-by-day data.
THINGS TO TRY
There are so many things you can try in this model. Here are only very a few quick ideas:
How many people die when hospitalization is available vs. unavailable?
How does hospitalization affect the number of deaths in the outbreak?
How does hospitalization affect the duration of the outbreak?
How does the isolation rate affect the number of deaths in the outbreak?
How does the isolation rate affect the duration of the outbreak?
How does the quarantine rate affect the number of deaths in the outbreak?
How does the quarantine rate affect the duration of the outbreak?
How do infections change in the population when isolation, quarantine, or low mobility is practiced 2 days, 3 days, or a week after introducing the carrier?
How do infections change in the population if we only isolate the sick people but do nothing to the carriers?
Can we both lower the number of deaths and shorten the duration of the outbreak? How?
Dr. Lin Xiang creates this module at the University of Kentucky in 2019. If you mention this model in a publication, we ask that you include the citations below.
Xiang, L. (2020). Infectious Disease Outbreak-HealthCare, Isolation and Quarantine. Department of STEM Education, University of Kentucky, Lexington, KY.
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