compartmental.lshtm_ode

compartmental.lshtm_ode

Define compartmental TB models.

TB_ODE is a translation of the R model (lshtm_ode.R) into Python, integrated with scipy.odeint. TB_SS is a Starsim implementation of the same compartmental model, with Euler integration.

State and parameter names are aligned with the agent-based tbsim.TB class. The ODE keeps CLEARED split into three sub-states (CLEARED, RECOVERED, TREATED) so that the appropriate reinfection multiplier can be applied to each pathway, matching the per-agent rr_reinfection_cleared / rr_reinfection_rec / rr_reinfection_treat mechanism in tbsim.TB. Treatment dynamics (theta, phi, delta) are off by default — enable explicitly when modelling a post-treatment-era period.

Classes

Name	Description
TB_ODE	Continuous-time compartmental TB model integrated with scipy.odeint.
TB_SS	Compartmental Starsim implementation of the LSHTM TB model (Euler integration).

TB_ODE

compartmental.lshtm_ode.TB_ODE(**kwargs)

Continuous-time compartmental TB model integrated with scipy.odeint.

See default_pars for parameter definitions.

Example

::

from tbsim.compartmental.lshtm_ode import TB_ODE

tb = TB_ODE()
tb.run()
tb.plot()

Methods

Name	Description
plot	Plot all results, each in a separate axes.
run	Integrate the ODE system from start_time to end_time and store results.

plot

compartmental.lshtm_ode.TB_ODE.plot(**kwargs)

Plot all results, each in a separate axes.

run

compartmental.lshtm_ode.TB_ODE.run(start_time=1500, end_time=2020)

Integrate the ODE system from start_time to end_time and store results.

TB_SS

compartmental.lshtm_ode.TB_SS(**kwargs)

Compartmental Starsim implementation of the LSHTM TB model (Euler integration).

Self-contained: does not need a network or People (operates on aggregate compartments).

See default_pars for parameter definitions.

Example:

import starsim as ss
import tbsim.compartmental as tbc
tb = tbc.TB_SS()
sim = ss.Sim(modules=tb, start=1920, stop=2020, dt=0.1, n_agents=1)
sim.run()
sim.plot()

Methods

Name	Description
init_post	Set initial conditions: 1% start in SYMPTOMATIC active TB.
init_results	Initialize results.
plot	Plot all results, each in a separate axes.
step	Euler integration of the ODE system.
update_results	Store the current state.

init_post

compartmental.lshtm_ode.TB_SS.init_post()

Set initial conditions: 1% start in SYMPTOMATIC active TB.

init_results

compartmental.lshtm_ode.TB_SS.init_results()

Initialize results.

plot

compartmental.lshtm_ode.TB_SS.plot(**kwargs)

Plot all results, each in a separate axes.

step

compartmental.lshtm_ode.TB_SS.step()

Euler integration of the ODE system.

update_results

compartmental.lshtm_ode.TB_SS.update_results()

Store the current state.