HIV Scripts

Scripts for running TB-HIV co-infection simulations and scenarios.

scripts.hiv.run_deven_sce.build_tbhiv_sim(include_intv=False, include_cnn=False, hiv_pars=None, hiv_intv_pars=None, Demgs=False) → Sim

Construct a TB-HIV simulation with optional interventions.

scripts.hiv.run_deven_sce.get_scenarios()

Define simulation scenarios.

scripts.hiv.run_deven_sce.main()

scripts.hiv.run_hiv.sim_setup(n_agents=10_000, Intvs=True, Demgs=False, verbose_log=False) → Sim

scripts.hiv.run_tbhiv.build_tbhiv_sim(Intvs=True, tb=True, includehiv=True, Demgs=True, simpars=None) → Sim

Build a TB-HIV simulation with current disease and intervention models.

scripts.hiv.run_tbhiv_scenarios.build_tbhiv_sim(simpars=None, tbpars=None, hivinv_pars=None) → Sim

Build a TB-HIV simulation with current disease and intervention models.

scripts.hiv.run_tbhiv_scenarios.run_scenarios()

scripts.hiv.run_tbhiv_scenarios.plot_results(flat_results, keywords=None, exclude=['15'])

scripts.hiv.shared_functions.make_hiv_interventions(include: bool = True, pars=None)

scripts.hiv.shared_functions.make_hiv(include: bool = True, hiv_pars=None)

scripts.hiv.shared_functions.make_tb(include: bool = True, tb_pars=None)

scripts.hiv.shared_functions.make_tb_hiv_connector(include: bool = True, pars=None)

scripts.hiv.shared_functions.make_demographics(include: bool = False)

scripts.hiv.shared_functions.plot_results(flat_results, keywords=None, exclude=('15',), n_cols=5, dark=True, cmap='tab20', heightfold=3, style='default')

Parameters:

• flat_results (dict[str, dict[str, Result]] - Mapping scenario→{metric→Result(timevec, values)}.)

• keywords (list[str], optional - Only plot metrics containing any of these substrings.)

• exclude (tuple[str], optional - Skip metrics whose name contains any of these substrings.)

• n_cols (int, optional - Number of columns in the subplot grid.)

• dark (If True use greyish dark mode; otherwise default style.)

• cmap (str, optional - Name of the Matplotlib colormap to use.)

scripts.hiv.shared_functions.uncertanty_plot()