## What to do

### A few general notes

- Some of the tasks below (and in future apps) are fairly open-ended. The idea is that these tasks give you something to get started, but you should feel free to explore the simulations any way you want. Play with them, query them, go through iterations of thinking what you expect, observing it, and if discrepancies occur, figure out why. Essentially, the best way to use these apps is to do your own science/research with them.

- This and most other simulations/apps in DSAIDE do not have natural time units (unless specifically stated). You could, therefore, assume that your model runs in units of days or weeks/months/years, based on what’s most suitable for the disease you want to study. You have to make sure that all your parameters are in the right time units. Always make sure to check if a given simulation can handle different time units or assumes specific ones.

The tasks below are described in a way that assumes everything is in units of DAYS (rate parameters, therefore, have units of inverse days). If any quantity is not given in those units, you need to convert it first (e.g. if it says a week, you need to convert it to 7 days).

### Task 1:

- Run the simulation with a population size, S0, of 1000, 1 initially infected host, I0, simulation duration 100 days, recovery rate g=0.5 per day, and infectiousness b=0.001. You will get an outbreak of some - currently unspecified - infectious disease.
- Record the number and fraction of susceptible/infected/recovered remaining at the end of the outbreak.
- From the graph, get a (rough) estimate of the day at which the outbreak peaks.
- Contemplate the fact that the outbreak ends even though there are still susceptible remaining, i.e. not everyone got infected.
- Rerun the simulation, with the same values you just had. Does anything change? Why (not)?

### Task 2:

- Double the value of the transmission rate, b. Leave everything else the same.
- What do you expect to get for the number/fraction of S/I/R at the end of the outbreak and the time at which the outbreak peaks?
- Run the simulation with the doubled transmission rate, record the same values (final S/I/R and outbreak peak) as above.
- Compare your expectations with the results. How do they agree/disagree? Does it make sense? Anything surprising happening?

### Task 3:

- Now, double the rate of recovery, g, leave everything as in #2.
- How do you expect the results to change? (Try to make your prediction as precise/quantitative as you can.)
- Run the simulation with these new parameter settings, record the same values as above.
- Compare your expectations with the results. How do they agree/disagree? Does it make sense? Anything surprising happening?

### Task 4:

- Now, double the number of susceptibles, S0, leave everything else as you just had.
- How do you expect the results to change?
- Run the simulation with these new parameter settings, record the same values as above.
- Compare your expectations with what results. How do they agree/disagree? Does it make sense? Anything surprising happening?

### Task 5:

- Keep playing around with changing any of the parameters and starting conditions.
- Every time, think about what you expect to get, then run the simulation, compare your expectations with the results. Then make sense of it.
- What is the minimum and maximum number of outbreaks you can get? Why is that?