"QuizID"	"AppID"	"AppTitle"	"TaskID"	"TaskText"	"RecordID"	"Record"	"Type"	"Note"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	1	"Run the simulation with 999 susceptible individuals and 1 initially infected host. Set the simulation duration to 10 years. Consider density-dependent transmission, with a transmission rate of _b~d~_ = 0.005, and an area of size 2. Assume that the duration of the infectious period is 15 days long (and that there are 30 days in a month). Turn off births, deaths and waning immunity for now. If you did it correctly, your outbreak should end with around 626 susceptible individuals still remaining. Take a look at the force of infection (FOI) equation for density-dependent transmission. The FOI value changes throughout the outbreak because it has _I_ in the equation. But the other parts of the equation remain constant. Compute the FOI value for the settings here at the start of the outbreak (where I=1)."	"T1R1"	"Force of infection at start"	"Numeric"	"Report all digits"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	1	"Run the simulation with 999 susceptible individuals and 1 initially infected host. Set the simulation duration to 10 years. Consider density-dependent transmission, with a transmission rate of _b~d~_ = 0.005, and an area of size 2. Assume that the duration of the infectious period is 15 days long (and that there are 30 days in a month). Turn off births, deaths and waning immunity for now. If you did it correctly, your outbreak should end with around 626 susceptible individuals still remaining. Take a look at the force of infection (FOI) equation for density-dependent transmission. The FOI value changes throughout the outbreak because it has _I_ in the equation. But the other parts of the equation remain constant. Compute the FOI value for the settings here at the start of the outbreak (where I=1)."	"T1R2"	"FRACTION of susceptible (Sfinal/Sinitial) at end of simulation"	"Rounded_Numeric"	"Round to 2 significant digits (0.XX)"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	2	"Now switch the scenario to frequency-dependent from density-dependent transmission. Set _b~f~_ = 2.5. The value of _b~d~_ does not matter since only one type of transmission is turned on at any time. Leave all other settings as before. Before you run the simulation, compute the force of infection for frequency-dependent transmission for the chosen parameter values. Compare to the value from the previous task. Based on that, what do you expect to get for the outbreak? Run the simulation to confirm your expectation."	"T2R1"	"Force of infection at start"	"Numeric"	"Report all digits"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	2	"Now switch the scenario to frequency-dependent from density-dependent transmission. Set _b~f~_ = 2.5. The value of _b~d~_ does not matter since only one type of transmission is turned on at any time. Leave all other settings as before. Before you run the simulation, compute the force of infection for frequency-dependent transmission for the chosen parameter values. Compare to the value from the previous task. Based on that, what do you expect to get for the outbreak? Run the simulation to confirm your expectation."	"T2R2"	"FRACTION of susceptible at end of simulation"	"Rounded_Numeric"	"Round to 2 significant digits (0.XX)"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	3	"Let's assume we are now in a location with twice the number of people as before (_S~0~_ = 1999), living in the same area. All other quantities (rate of transmission, recovery time, etc.) are assumed to be the same. Take a look at the FOI equation for density-dependent transmission. Based on its value for this new scenario, how do you expect the outbreak to change if transmission is density-dependent? Note that you will need to consider not only the FOI at the start (with _I_=1), but also how _I_, and thus the FOI, change over the course of the outbreak, and how this is impacted by a change in population size. Run the simulation to check your expectations."	"T3R1"	"Force of infection at start"	"Numeric"	"Report all digits"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	3	"Let's assume we are now in a location with twice the number of people as before (_S~0~_ = 1999), living in the same area. All other quantities (rate of transmission, recovery time, etc.) are assumed to be the same. Take a look at the FOI equation for density-dependent transmission. Based on its value for this new scenario, how do you expect the outbreak to change if transmission is density-dependent? Note that you will need to consider not only the FOI at the start (with _I_=1), but also how _I_, and thus the FOI, change over the course of the outbreak, and how this is impacted by a change in population size. Run the simulation to check your expectations."	"T3R2"	"FRACTION of susceptible at end of simulation"	"Rounded_Numeric"	"Round to 2 significant digits (0.XX)"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	4	"Repeat what you did for the previous task, now assuming that transmission is frequency-dependent."	"T4R1"	"Force of infection at start"	"Numeric"	"Report all digits"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	4	"Repeat what you did for the previous task, now assuming that transmission is frequency-dependent."	"T4R2"	"FRACTION of susceptible at end of simulation"	"Rounded_Numeric"	"Round to 2 significant digits (0.XX)"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	5	"If you double the population size as you just did, how do you need to adjust the area to obtain an outbreak of the same relative size (same fraction that become infected/remain susceptible) for density-dependent transmission? Try with the simulation and see if your expectation is correct."	"T5R1"	"The area used to get the same final fraction susceptible as in task 1."	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_directtransmission"	"directtransmission"	"Direct Transmission"	6	"Keep exploring by trying different parameters and transmission settings and see how they influence results. You can also go beyond a single outbreak and turn on births/deaths (which can impact population size) or waning immunity. As you continue your exploration, think about real infectious diseases that might be approximated by either one of the transmission types, and what approximate choices for the model parameters would describe those IDs."	"T6R1"	"Nothing"	"None"	""
