TB model scenarios¶

The EMOD tuberculosis model is explained in detail in Tuberculosis model overview. While the various components that comprise the model are explained with examples, it may be more useful to learn the model through hands-on implementation. The following sections will introduce sets of example files that illustrate how the TBHIV_SIM simulation type works on particular topics. All files are available in the downloadable EMODScenarios folder and, in addition to the explanations below, each scenario will have a more detailed README file to cover relevant information.

Because all disease-specific EMOD simulation types are based on the generic model, the Generic model scenarios are helpful in learning the basics of modeling with EMOD, even if you intend to use one of the disease-specific simulation types.

For more information on the software architecture and inheritance, see Overview of EMOD software.

Contents

Disease dynamics
Diagnosis and treatment

Disease dynamics ¶

The following scenarios are focused primarily on the unique disease dynamics of tuberculosis. There is a large amount of heterogeneity in the progression and presentation of TB that must be configured create more realistic simulations. Some of these incorporate interventions, but that is not their primary focus.

Disease progression ¶

Latent tuberculosis infection progresses to TB disease slowly, if at all, in most individuals. EMODScenarios > Scenarios > TB > Disease_Progression illustrates how to configure heterogeneity in disease progression and infectiousness. Individuals with a latent infection will progress to active disease slowly or quickly. Once the infection activates, you can configure some people to experience presymptomatic disease, some to have positive or negative smear tests, and others to have extrapulmonary infection. For detailed information, see Disease progression.

Age-dependent immunity ¶

Because the disease course for TB can differ between children and adults, EMOD has separate configuration parameters for adults and children to facilitate more realistic TB simulations. EMODScenarios > Scenarios > TB > Age_Immunity walks through configuring lifelong immunity, waning immunity, and childhood vaccination. For detailed information, see Age-dependent immunity.

Endemic TB settings ¶

To model a population with endemic TB at a low absolute prevalence, you must run the simulation for a period of time until the disease dynamics reach an equilibrium (aside from stochastic noise). This point in time is known as steady state and the process of running the simulation to that point is known as simulation burn-in. EMODScenarios > Scenarios > TB > Population_Burnin walks through burn-in and population serialization. For detailed information, see Populations with endemic TB.

Diagnosis and treatment ¶

The following scenarios are focused on configuring EMOD to simulate the complex health care systems for diagnosing and treating TB.

Treatment in multiple health care systems ¶

Not all health care systems provide effective diagnosis or treatment of tuberculosis. The EMODScenarios > Scenarios > TB > Health_Systems scenario illustrates how you can configure health care systems of differing quality, improve the quality of care for some individuals, or improve the quality of care across the entire health care system. For detailed information, see Treatment in multiple health care systems.

Case finding and cascade of care ¶

Diseases that progress slowly or require long-term treatment, such as tuberculosis or HIV, complicate the health care systems used for diagnosis and treatment. In EMOD, a system of health care can be created by using multiple interventions. Interventions can be linked to create a network of actions and results, where the outcome of one intervention can initiate the start of the next. This creates a cascade of care, where individuals enter the system due to a positive diagnostic test, and then move through the healthcare system created, with options for follow-up tests, and treatment options. Some individuals will exit the care system (e.g. “lost to follow up”), and in some cases, individuals that exit the care system may re-initiate care and return.

The EMODScenarios > Scenarios > TB > Cascade_Of_Care scenario walks through setting up a simple cascade of care that compares active vs. passive case-finding strategies. For detailed information, see Case finding and cascade of care.

Multidrug-resistant TB ¶

One additional complicating factor in health care for TB is that inadequate treatment will not only be ineffective, but may actually lead to multidrug-resistant TB that can be transmitted to others and makes successful treatment more difficult. The EMODScenarios > Scenarios > TB > MDR-TB scenario illustrates how to include drug resistance in TB simulations.

TB with HIV coinfection ¶

In HIV+ individuals, latent TB progresses to active TB disease at a much higher rate. The EMOD TB model can incorporate HIV coinfection to better represent tuberculosis disease dynamics in areas with high HIV prevalence. The model uses HIV prevalence as an input, but it does not simulate the transmission of HIV. The EMODScenarios > Scenarios > TB > HIV_Coinfection illustrates the effect of providing anti-retroviral therapy (ART) to HIV+ individuals on the transmission of TB.