Initial Conditions

The initial_conditions block seeds the model's compartments at the start of the simulation. Two methods are supported: percentage (default) and absolute. If you omit the block entirely, epydemix's built-in default is used.

percentage

Specify the share of the population in each compartment as a percentage (not a fraction). The values are divided by 100 internally, distributed proportionally across age groups, and whatever is left over goes to the first compartment of the preset (usually Susceptible).

Field	Type	Notes
method	"percentage"	Default.
initial_percentages	{compartment: number}	Percentages of total population. 0.1 = 0.1%, 10.0 = 10%.

Example: seed 0.1% as infected

curl -X POST https://epyscenario-api.isi.it/api/v1/simulations \
-H "Content-Type: application/json" \
-d '{
  "model": {
    "preset": "SIR",
    "parameters": {"R0": 2.5, "infectious_period": 10.0}
  },
  "population": {"name": "United_States"},
  "simulation": {"start_date": "2024-01-01", "end_date": "2024-04-01", "Nsim": 10},
  "initial_conditions": {
    "method": "percentage",
    "initial_percentages": {"Infected": 0.1}
  }
}'

Example: seed multiple compartments

The remainder (after Infected and Recovered) lands in Susceptible. Here 1% infected, 30% already recovered (e.g. modeling a population with prior immunity), and 69% susceptible.

curl -X POST https://epyscenario-api.isi.it/api/v1/simulations \
-H "Content-Type: application/json" \
-d '{
  "model": {
    "preset": "SIR",
    "parameters": {"R0": 2.5, "infectious_period": 10.0}
  },
  "population": {"name": "United_States"},
  "simulation": {"start_date": "2024-01-01", "end_date": "2024-04-01", "Nsim": 10},
  "initial_conditions": {
    "method": "percentage",
    "initial_percentages": {"Infected": 1.0, "Recovered": 30.0}
  }
}'

The percentage of each compartment is split across age groups in proportion to each group's share of the total population, so larger age groups receive proportionally more seed counts.

absolute

Specify exact counts per compartment per age group. You are responsible for making the counts sum to the population in each age group; nothing is auto-filled.

Field	Type	Notes
method	"absolute"
compartments	{compartment: number[]}	One array per compartment. Array length must equal the population's number of age groups.

Example: explicit per-age counts

The five-bin default for United_States has age groups [0-19, 20-49, 50-64, 65-74, 75+]. The arrays below seed 100 / 200 / 500 / 500 / 200 infected per age group; the rest of each group sits in Susceptible.

curl -X POST https://epyscenario-api.isi.it/api/v1/simulations \
-H "Content-Type: application/json" \
-d '{
  "model": {
    "preset": "SIR",
    "parameters": {"R0": 2.5, "infectious_period": 10.0}
  },
  "population": {"name": "United_States"},
  "simulation": {"start_date": "2024-01-01", "end_date": "2024-04-01", "Nsim": 10},
  "initial_conditions": {
    "method": "absolute",
    "compartments": {
      "Susceptible": [83000000, 132000000, 62000000, 32000000, 22000000],
      "Infected":    [100, 200, 500, 500, 200]
    }
  }
}'

If the array length doesn't match the population's age groups, the request is rejected.

Default when omitted

If you omit initial_conditions, ~0.05% of each age group is seeded into Infected and the rest into Susceptible. For the vaccination presets, the seed is split evenly between Exposed and Infected (~0.025% each) and the _vax branch starts at zero.

Notes

• Compartment names in initial_percentages / compartments must match the preset's compartment names (e.g. Susceptible, Exposed, Infected, Recovered, Hospitalized for SEIHR-family presets; _vax twins for the vaccination presets).
• For the vaccination presets, the vaccinated branch (Susceptible_vax, Exposed_vax, …) starts at zero unless you seed it or supply a vaccination block.
• Use Custom Models if you need compartments outside the preset list.