"QuizID"	"AppID"	"AppTitle"	"TaskID"	"TaskText"	"RecordID"	"Record"	"Type"	"Note"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	1	"Set the simulation the following simulation parameter values 1000 susceptibles, 1 infected, tfinal = 100 days, _g_=0.5, and _b_=0.001. Run the simulation, you should get an outbreak. Use the final size equation linking R~0~ and the fraction of susceptible hosts left at the end of the outbreak to compute the reproductive number (see the information in the _Model_ tab)."	"T1R1"	"Day at which outbreak peaks"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	1	"Set the simulation the following simulation parameter values 1000 susceptibles, 1 infected, tfinal = 100 days, _g_=0.5, and _b_=0.001. Run the simulation, you should get an outbreak. Use the final size equation linking R~0~ and the fraction of susceptible hosts left at the end of the outbreak to compute the reproductive number (see the information in the _Model_ tab)."	"T1R2"	"Susceptible at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	1	"Set the simulation the following simulation parameter values 1000 susceptibles, 1 infected, tfinal = 100 days, _g_=0.5, and _b_=0.001. Run the simulation, you should get an outbreak. Use the final size equation linking R~0~ and the fraction of susceptible hosts left at the end of the outbreak to compute the reproductive number (see the information in the _Model_ tab)."	"T1R3"	"The value for R~0~"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	2	"Use the equation that expresses R~0~ as a function of the model parameters. Using the values of the model parameters from task 1, compute R~0~. Check that it agrees with what you found in the previous task."	"T2R1"	"The value for R~0~"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	3	"Double the value of the transmission parameter, _b_. Leave everything else as before. Before you run the simulation, use the equation to compute R~0~. Then run the simulation and compute R~0~ using the final outbreak size. Make sure the two numbers approximately agree."	"T3R1"	"The value for R~0~"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	4	"Double the rate of the recovery parameter, _g_. Leave everything else unchanged. Think about your expectations for R~0~ and the resulting outbreak dynamics. Run the simulation to check your expectations. Use the final outbreak size to compute R~0~."	"T4R1"	"Day at which outbreak peaks"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	4	"Double the rate of the recovery parameter, _g_. Leave everything else unchanged. Think about your expectations for R~0~ and the resulting outbreak dynamics. Run the simulation to check your expectations. Use the final outbreak size to compute R~0~."	"T4R2"	"Susceptible at end of simulation"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	4	"Double the rate of the recovery parameter, _g_. Leave everything else unchanged. Think about your expectations for R~0~ and the resulting outbreak dynamics. Run the simulation to check your expectations. Use the final outbreak size to compute R~0~."	"T4R3"	"The value for R~0~"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	5	"Another way to estimate R~0~ is to determine the rate of increase in infected hosts at the beginning of the outbreak. During the initial phase, new infections increase exponentially according to _I(t)=I~0~ exp(rt)_, with _r_ being the rate of growth. Usually, for any real outbreak, you do not know the number of infected at the start, I~0~, or the exact time the outbreak starts. It is still possible to estimate _r_ by obtaining two values of _I_ at two time points during that initial growth rate, i.e. _I~1~_ at time _t~1~_ and _I~2~_ at time _t~2~_. One obtains equations _I~1~=I~0~ exp(r t~1~)_ and _I~2~=I~0~ exp(r t~2~)_. By solving one of these equations for _I~0~_ and substituting into the other, we get _I~2~= I~1~ exp(r (t~2~ - t~1~))_. By solving the model for _r_ and entering numbers for _I~1~_ and _I~2~_ and times _t~1~_ and _t~2~_ we can figure out _r_. Let's try that out. Set the model parameters back to those given in task #1. Let's try using the new method for estimating R~0~. Run the model with tfinal = 1 and tfinal = 2 and record the number of infected at the end of the simulation each time. Then substitute all the values into the equation you found for _r_ and thus compute the growth rate. For this model, the growth rate and R~0~ are related through _R~0~ = 1+rD_, where _D_ is the average duration of the infectious period (i.e. the inverse of the recovery rate). Use this to determine R~0~. You should get essentially the same answer (up to some rounding differences) as for task #1. Note that the choice of _t~1~_ and _t~2~_ can influence the results. Earlier times are better since once the number of susceptibles starts to drop markedly, the growth of infected slows down and is not exponential anymore."	"T5R1"	"The value for R~0~"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	6	"What is the value of the reproductive number _R_ at the time the outbreak peaks? (It's only called R~0~ at the beginning for a fully susceptible population). Explain how you can find that value for R, both using intuitive reasoning and using the equation for R~0~ given above (R~0~ = 1+rD). For some hints, note that at the peak numbers of infected are briefly flat, i.e. there is no more growth (what does that mean for _r_?). Also, there is no decline yet, for the infected to stay exactly the same, the average number of infections produced by one infected person before they recover needs to have a very specific value. What is that value? Note that at this R value, the outbreak wanes, but people still get infected. What R value would you need to halt any further infections completely?"	"T6R1"	"R value at which number of infected neither grows nor declines"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	6	"What is the value of the reproductive number _R_ at the time the outbreak peaks? (It's only called R~0~ at the beginning for a fully susceptible population). Explain how you can find that value for R, both using intuitive reasoning and using the equation for R~0~ given above (R~0~ = 1+rD). For some hints, note that at the peak numbers of infected are briefly flat, i.e. there is no more growth (what does that mean for _r_?). Also, there is no decline yet, for the infected to stay exactly the same, the average number of infections produced by one infected person before they recover needs to have a very specific value. What is that value? Note that at this R value, the outbreak wanes, but people still get infected. What R value would you need to halt any further infections completely?"	"T6R2"	"R value to completely halt any further infections"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	7	"What would happen if a new ID came along that had an R~0~ value that was the same as the one you just determined in the previous question, namely the value of R at the peak of an outbreak? Test this with the simulation. Set everyting as in task 1, then reduce transmission rate by half, which should get you the right R~0~ (you can check by plugging the parameter values into the R~0~ equation). Run the simulation and observe what the model produces. You should not see any outbreak."	"T7R1"	"Nothing"	"None"	""
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	8	"A) R~0~ quantifies the level of transmissibility of an ID, which determines how many people will become infected or what level of intervention is needed to stop/prevent an outbreak. However, it is important to be aware that R~0~ says nothing about the timing/dynamics of the outbreak. Set parameter values as in #1. Also increase simulation time to 200 so we can make sure the outbreak is over. Run an outbreak, pay attention to the time of peak and duration of the outbreak (the latter is somewhat ill-defined, so just come up with a rough number). 
B) Now increase the infectious duration by a factor of 4 (rate reduced by a factor of 4) and adjust the infectiousness-level such that you get the same R~0~ as before. Run again and compare the results concerning total outbreak size and timing of outbreak."	"T8R1"	"Number susceptible left at end of outbreak (part A)"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	8	"A) R~0~ quantifies the level of transmissibility of an ID, which determines how many people will become infected or what level of intervention is needed to stop/prevent an outbreak. However, it is important to be aware that R~0~ says nothing about the timing/dynamics of the outbreak. Set parameter values as in #1. Also increase simulation time to 200 so we can make sure the outbreak is over. Run an outbreak, pay attention to the time of peak and duration of the outbreak (the latter is somewhat ill-defined, so just come up with a rough number). 
B) Now increase the infectious duration by a factor of 4 (rate reduced by a factor of 4) and adjust the infectiousness-level such that you get the same R~0~ as before. Run again and compare the results concerning total outbreak size and timing of outbreak."	"T8R2"	"Day the outbreak peaked (part A)"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	8	"A) R~0~ quantifies the level of transmissibility of an ID, which determines how many people will become infected or what level of intervention is needed to stop/prevent an outbreak. However, it is important to be aware that R~0~ says nothing about the timing/dynamics of the outbreak. Set parameter values as in #1. Also increase simulation time to 200 so we can make sure the outbreak is over. Run an outbreak, pay attention to the time of peak and duration of the outbreak (the latter is somewhat ill-defined, so just come up with a rough number). 
B) Now increase the infectious duration by a factor of 4 (rate reduced by a factor of 4) and adjust the infectiousness-level such that you get the same R~0~ as before. Run again and compare the results concerning total outbreak size and timing of outbreak."	"T8R3"	"Number susceptible left at end of outbreak (part B)"	"Rounded_Integer"	"Report the rounded integer"
"DSAIDE_reproductivenumber1"	"reproductivenumber1"	"Reproductive Number 1"	8	"A) R~0~ quantifies the level of transmissibility of an ID, which determines how many people will become infected or what level of intervention is needed to stop/prevent an outbreak. However, it is important to be aware that R~0~ says nothing about the timing/dynamics of the outbreak. Set parameter values as in #1. Also increase simulation time to 200 so we can make sure the outbreak is over. Run an outbreak, pay attention to the time of peak and duration of the outbreak (the latter is somewhat ill-defined, so just come up with a rough number). 
B) Now increase the infectious duration by a factor of 4 (rate reduced by a factor of 4) and adjust the infectiousness-level such that you get the same R~0~ as before. Run again and compare the results concerning total outbreak size and timing of outbreak."	"T8R4"	"Day the outbreak peaked (part B)"	"Rounded_Integer"	"Report the rounded integer"
