## What to do

The tasks below are described in a way that assumes everything is in units of MONTHS (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 year, you need to convert it to 12 months).

### Task 1:

- Set the model parameters such that it corresponds to the following setting:
  - A starting population of 1000 individuals, 999 susceptible and 1 initially infected host.
  - Simulation duration, tmax approximately 10 years.
  - Consider density-dependent transmission, with a transmission rate of bd = 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.
- With parameters set to correspond to the scenario just described, run the simulation.
- Record the number and fraction of susceptible/infected/recovered remaining at the end of the outbreak. You should be left with 625 susceptibles.

### Task 2:

- Now switch to frequency-dependent transmission, set bf = 2.5. Keep everything else as before.
- Think about your expectations, run the simulation and compare your expectations with the results.
- Anything surprising happening? Do you understand why you see what you see?

### Task 3:

- Let’s assume we are now in a location with twice the number of people as before (S0 = 1999) , living in roughly the same area.
- Implement that in the simulation by changing population size, keep all other settings as above.
- What do you expect to see for the frequency and density dependent scenarios? Run simulations and check. Pay attention to both the numbers and fractions of S/I/R individuals at the end of the outbreak.

### Task 4:

- If you double the population size as you just did, how do you need to adjust the area to obtain the same sized outbreak with regard to the fraction of people getting infected/remaining susceptible for density-dependent transmission?
- Try with the simulation and see if your expectation is correct.

### Task 5:

- 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.