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v0.7.0

Released 2026-05-18 · GitHub Release

Overview​

  • Add the V-SEIHR model preset: Susceptible-Exposed-Infected-Hospitalized-Recovered with a parallel vaccinated branch and two efficacy parameters (VE_S against susceptibility, VE_H against hospitalization)
  • Add a top-level vaccination block to POST /simulations: declarative campaigns that turn a daily dose budget into a per-individual vaccination rate, with age-group targeting, multiple overlapping campaigns, dose sinks, and multi-target flows

Simulations​

POST /api/v1/simulations

New model preset: V-SEIHR​

The new V-SEIHR model preset is a SEIHR model with a vaccinated twin of every compartment (Susceptible_vax, Exposed_vax, Infected_vax, Hospitalized_vax, Recovered_vax). Vaccinated susceptibles see an attenuated force of infection and vaccinated infected hospitalize at a reduced rate:

λivax(t)=(1−VES)⋅λi(t),pHvax=(1−VEH)⋅pH.\lambda^{\text{vax}}_i(t) = (1 - \mathrm{VE_S}) \cdot \lambda_i(t), \qquad p_H^{\text{vax}} = (1 - \mathrm{VE_H}) \cdot p_H.

Vaccinated infectious individuals transmit at the same per-contact rate as unvaccinated; the reduction sits on susceptibility, not transmissibility.

Without a vaccination block the vaccinated branch stays at zero for the whole run and V-SEIHR behaves like plain SEIHR.

See the V-SEIHR preset page for the full transition table, ODE form, parameter reference, and examples.

Vaccination block​

A new top-level vaccination object drives doses through the model:

{
  "model": {
    "preset": "V-SEIHR",
    "parameters": {"R0": 2.5, "VE_S": 0.7, "VE_H": 0.85}
  },
  "population": {"name": "United_States"},
  "simulation": {"start_date": "2025-01-01", "end_date": "2025-06-30", "Nsim": 10},
  "vaccination": {
    "campaigns": [
      {
        "start_date": "2025-02-01",
        "end_date":   "2025-04-30",
        "rollout": {"type": "flat_count", "daily_doses": 100000}
      }
    ]
  }
}

Each campaign turns a daily dose budget dc(t)d_c(t) into a per-individual rate by spreading those doses across the live eligible pool:

rc(t)=dc(t)∑X∈S  ∑j∈AcXj(t).r_c(t) = \frac{d_c(t)}{\displaystyle\sum_{X \in \mathcal{S}}\;\sum_{j \in \mathcal{A}_c} X_j(t)}.

Each transitioning flow surfaces as a regular transition in the response (e.g. Susceptible_to_Susceptible_vax under results.transitions.data); flows with dose sinks emit no transition. The request is echoed back under metadata.vaccination with the resolved flows list.

See the Vaccination overview and Campaigns page for the full details and custom-model usage.

Documentation​

  • New Vaccination guide category with Overview (rate calculation, flows, dose allocation, vaccine efficacy, inspecting the rollout) and Campaigns (per-campaign fields, rollout strategies, multi-campaign stacking, custom-model usage)
  • New V-SEIHR preset page with compartments, transitions, equivalent ODE form, vaccine-efficacy math, parameter table, and three curl examples (with vaccination, without vaccination, with seasonality)
  • Model presets split into per-preset pages under guides/model/presets/ (SIR, SEIR, SIS, V-SEIHR)
  • Parameter docs grouped under guides/model/parameters/ with an Overview and a dedicated Transformations page
  • Updated FAQ with cleaner structure
  • Added full text search