"QuizID"	"AppID"	"AppTitle"	"TaskID"	"TaskText"	"RecordID"	"Record"	"Type"	"Note"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	1	"Start with 1000 susceptibles, 1 initially infected presymptomatic host, _P~0~_, simulation duration of 200 days. Assume that only symptomatic individuals transmit, at rate _b~I~_ = 0.001. Assume that the duration of the presymptomatic, asymptomatic and symptomatic periods are all 5 days long. (Hint: The parameters _g~P~_, _g~A~_, and _g~I~_ are the inverses of these periods.) Assume that there are no asymptomatic infections, _f_=0, and nobody dies due to disease _d_=0. Make sure the results agree with model settings. For instance you shouldn't get any deaths, and no asymptomatic infected. If you did it correctly, your outbreak should end with around 7 susceptibles remaining. From the graph, contemplate how you would estimate the day at which the outbreak peaks. What's the problem? How would you solve it? Rerun the simulation, with the same input settings (i.e. don't change anything, just hit the Run Simulation button again). Do you see any changes in the results? Why (not)? (This will be different once we move to the stochastic models)."	"T1R1"	"Total number of recovered (at end of simulation)"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	1	"Start with 1000 susceptibles, 1 initially infected presymptomatic host, _P~0~_, simulation duration of 200 days. Assume that only symptomatic individuals transmit, at rate _b~I~_ = 0.001. Assume that the duration of the presymptomatic, asymptomatic and symptomatic periods are all 5 days long. (Hint: The parameters _g~P~_, _g~A~_, and _g~I~_ are the inverses of these periods.) Assume that there are no asymptomatic infections, _f_=0, and nobody dies due to disease _d_=0. Make sure the results agree with model settings. For instance you shouldn't get any deaths, and no asymptomatic infected. If you did it correctly, your outbreak should end with around 7 susceptibles remaining. From the graph, contemplate how you would estimate the day at which the outbreak peaks. What's the problem? How would you solve it? Rerun the simulation, with the same input settings (i.e. don't change anything, just hit the Run Simulation button again). Do you see any changes in the results? Why (not)? (This will be different once we move to the stochastic models)."	"T1R2"	"Number susceptible left at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	2	"Assume now that after the pre-symptomatic stage, half of the infected move on to become symptomatic while the other half is asymptomatic. Set the model parameter controlling the fraction who become asymptomatic accordingly. Don't change any other assumption. Do you expect to get a change in the outbreak size? Why? Compute the total number of infected as you did for the _Basic SIR_ app. To do so, look at the diagram for the model and make sure you understand how individuals can flow through the system. That information will help you compute the total (cumulative) number infected (both symptomatic and asymptomatic)."	"T2R1"	"Number susceptible left at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	2	"Assume now that after the pre-symptomatic stage, half of the infected move on to become symptomatic while the other half is asymptomatic. Set the model parameter controlling the fraction who become asymptomatic accordingly. Don't change any other assumption. Do you expect to get a change in the outbreak size? Why? Compute the total number of infected as you did for the _Basic SIR_ app. To do so, look at the diagram for the model and make sure you understand how individuals can flow through the system. That information will help you compute the total (cumulative) number infected (both symptomatic and asymptomatic)."	"T2R2"	"Total/cumulative number who got infected"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	3	"Now assume that asymptomatic individuals transmit at the same rate as symptomatic individuals. Change _b~A~_ accordingly. Leave everything else as before. How do you expect the results to change? (Try to make as precise/quantitative a prediction as you can). Compare your results to the first task and make sure you understand why you get the results you do."	"T3R1"	"Number recovered at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	3	"Now assume that asymptomatic individuals transmit at the same rate as symptomatic individuals. Change _b~A~_ accordingly. Leave everything else as before. How do you expect the results to change? (Try to make as precise/quantitative a prediction as you can). Compare your results to the first task and make sure you understand why you get the results you do."	"T3R2"	"Number susceptible left at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	3	"Now assume that asymptomatic individuals transmit at the same rate as symptomatic individuals. Change _b~A~_ accordingly. Leave everything else as before. How do you expect the results to change? (Try to make as precise/quantitative a prediction as you can). Compare your results to the first task and make sure you understand why you get the results you do."	"T3R3"	"Total deaths"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	4	"Next, let's assume that half the symptomatic infected die. Change the corresponding parameter in the model to reflect this new assumption. Leave everything else as in task 3. How do you expect the results to change?"	"T4R1"	"Number of recovered at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	4	"Next, let's assume that half the symptomatic infected die. Change the corresponding parameter in the model to reflect this new assumption. Leave everything else as in task 3. How do you expect the results to change?"	"T4R2"	"Number susceptible left at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	4	"Next, let's assume that half the symptomatic infected die. Change the corresponding parameter in the model to reflect this new assumption. Leave everything else as in task 3. How do you expect the results to change?"	"T4R3"	"Total deaths"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	5	"Set all 3 transmission parameters (_b~P~_, _b~A~_, and _b~I~_) to 0.0005, leave everything else as before. Note that this lowers the transmission rate of the asymptomatic and symptomatic groups by a factor of 2, but now pre-symptomatic individuals are also infectious. What do you expect will happen to the peak of _P_ and _I_ as well as the total number of individuals who got infected (i.e., _R_ + _D_ at the end of simulation), compared to the previous task?"	"T5R1"	"Max number (peak) of pre-symptomatic (P)"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	5	"Set all 3 transmission parameters (_b~P~_, _b~A~_, and _b~I~_) to 0.0005, leave everything else as before. Note that this lowers the transmission rate of the asymptomatic and symptomatic groups by a factor of 2, but now pre-symptomatic individuals are also infectious. What do you expect will happen to the peak of _P_ and _I_ as well as the total number of individuals who got infected (i.e., _R_ + _D_ at the end of simulation), compared to the previous task?"	"T5R2"	"Max number (peak) of symptomatic infected (I)"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	5	"Set all 3 transmission parameters (_b~P~_, _b~A~_, and _b~I~_) to 0.0005, leave everything else as before. Note that this lowers the transmission rate of the asymptomatic and symptomatic groups by a factor of 2, but now pre-symptomatic individuals are also infectious. What do you expect will happen to the peak of _P_ and _I_ as well as the total number of individuals who got infected (i.e., _R_ + _D_ at the end of simulation), compared to the previous task?"	"T5R3"	"Number susceptible left at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	5	"Set all 3 transmission parameters (_b~P~_, _b~A~_, and _b~I~_) to 0.0005, leave everything else as before. Note that this lowers the transmission rate of the asymptomatic and symptomatic groups by a factor of 2, but now pre-symptomatic individuals are also infectious. What do you expect will happen to the peak of _P_ and _I_ as well as the total number of individuals who got infected (i.e., _R_ + _D_ at the end of simulation), compared to the previous task?"	"T5R4"	"Total deaths"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	6	"Further explore how changes in the infectiousness of the different groups (_b~P~_, _b~A~_, _b~I~_) and the average time a person spends in each of those states (_g~P~_, _g~A~_, _g~I~_) affects the infection dynamics. Every time, think about what you expect to get, then run the simulation, compare your expectations with the results. Then make sense of it."	"T6R1"	"Nothing"	"None"	""
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	7	"Using the settings from task 5, but now assume that 90% of infections are asymptomatic. How do things change?"	"T7R1"	"Max number of pre-symptomatic (P)"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	7	"Using the settings from task 5, but now assume that 90% of infections are asymptomatic. How do things change?"	"T7R2"	"Max number of symptomatic infected (I)"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	7	"Using the settings from task 5, but now assume that 90% of infections are asymptomatic. How do things change?"	"T7R3"	"Number susceptible left at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	7	"Using the settings from task 5, but now assume that 90% of infections are asymptomatic. How do things change?"	"T7R4"	"Total deaths"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_idcharacteristics"	"idcharacteristics"	"Characteristics of ID"	8	"Further explore how changes in the fraction becoming asymptomatic and fraction dying does (or does not) affect the infection dynamics. Every time, think about what you expect to get, then run the simulation, compare your expectations with the results. Then make sense of it."	"T8R1"	"Nothing"	"None"	""
