## What to do

All parameters described below and in the model are assumed to be in units of (inverse) days

### Task 1:

- Set the model parameters such that it corresponds to the following setting:
  - 500 susceptible and 1 initially untreated infected host. No other infected hosts.
  - Simulation duration approximately half a year.
  - Assume that untreated individuals transmit at rate 0.001, treated at rate 0.0005 and resistant at rate 0.0008.
  - Assume that the duration of the infectious period for untreated is 5 days long, 4 days for treated and 5 days for resistant.
  - Set number of simulations to 20.
- With parameters set to correspond to the scenario just described, run the simulation.
- You should see some simulations with outbreaks and some without. For those with outbreaks, you should have around 10-100 susceptible left at the end.

### Task 2:

- With everything as before, set the initial number of untreated infected hosts to 10.
- Run simulations. You should pretty much always get outbreaks. Record the average number of susceptibles left.

### Task 3:

- Now turn on treatment. With settings as above, run the simulation with fraction receiving treatment at 0, 0.25, 0.5, 0.75 and 1.
- Observe what happens to the susceptibles at the end of the outbreak as you change treatment. Draw conclusions about the usefulness of treatment.

### Task 4:

- Now allow resistance to be generated during treatment, with the fraction of resistant generation set to 0.2.
- Set treatment to 0. Contemplate what you expect to see. Run simulations to check.
- Now turn on treatment. With settings as above, run the simulation with fraction receiving treatment at 0.25, 0.5, 0.75 and 1.

### Task 5:

- Repeat task 3 with number of simulations at 50. Record the average number of susceptibles at the end of each of the 5 treatment levels.
- Set rate of transmission of resistant hosts to the same as that for untreated hosts, 0.001 and turn resistance generation on to 0.3.
- Repeat running 50 simulations at a time (you can repeat a few times to get a better idea about random variation). Record the average number of susceptibles at the end of each of the 5 treatment levels.
- In your head or on a piece of paper, sketch out the relation between treatment level and number of susceptibles left at the end in the absence and presence of resistance evolution. What do you conclude from that?

### Task 6:

- Keep exploring.
- Turn on resistance generation by treated and untreated.
- Explore how population size, rate of resistance generation and fitness of the different strains affect outcomes.