The Asthma Model, and its Scenarios

The Asthma Model

Model Structure

Asthma Models creates three scenarios: Null_Asthma, CR1, and CR3

The Asthma Model refers to a "Model architecture": A structure of states and transitions, which can be used to run different scenarios. A scenario is when the structure has a different set of transition rates between the states.

The Asthma model is used to run two scenarios of treatment coverage: CR1 and CR3. In addition, the Asthma model is also used to run a "Null Scenario": Called Asthma_Null. We will explain the Null Scenario later.

Structure of the Asthma Model

Asthma has three key states, DsFreeSus, AsthmaEpsd, and Deceased. DsFreeSus means "Disease free, susceptible", and this refers to the majority of the population. AsthmaEpsd means "Asthma Episode", and generally refers to people who have asthma and will experience an episode that year. Deceased refers to the people in the model who have died, either through background mortality (DsFreeSus -> Deceased) or through the Asthma episode (AsthmaEpsd -> Deceased).

In addition to these states, there are other "states" which are used to perform calculations, or collect useful statistics about the model. This is something we have chosen to do in our model structure, so it's visible to users, but it is not strictly necessary. For example, we have states for Disability, which collects information about the stock of DsFreeSus, AsthmaEpsd and Deceased and multiplies them against some disability weight. We also have states to calculate births, migration, and the effects of interventions on disability and mortality. Once again, we made these design decisions so that users can see how these work, but they aren't strictly necessary. They can be done elsewhere, and simply rendered as a transition rate.

The Model has two key components

The Asthma model is large, but can be broken down into two components.

The main component moves people between states

The main component has the states we've introduced: DsFreeSus, AsthmaEpsd, Deceased, Disability, Births. Importantly there are some other states which sit between states:

• DsFreeSus Disability sits between DsFreeSus and Disability
• AsthmaEpsd Disability sits between AsthmaEpsd and Disability
• AsthmaEpsd Mortality sits between AsthmaEpsd and Deceased

These states aren't really states in a true sense. Rather, these states set the value of the transition rates around them. So, for example, DsFreeSus Disability is really the transition rate for DsFreeSus -> Disability. In the nomenclature of the Botech protocol, we call this a "Surrogate node". This is a structural decision we have made, but it doesn't change the results. Rather, we do this, so we can show how the calculations work to determine the disability and mortality effects.

The calculation component sets the transition rates

The "Surrogate Nodes" mentioned above, are set by a series of calculations in the model. These calculations follow the common order of operations described in the introduction.

Order of Operations

The Asthma model follows the common order of operations used by all disease models. The key Asthma-specific variations are:

Treatment Effect Calculations (Steps 4-7)

The model calculates effects for four treatments: LowDoseBeclom, HighDoseBeclom, InhaledShortActingBeta, and AsthmaOralPrednisolone.

Step 4 example: LowDoseBeclom_PIN × LowDoseBeclom_Disability_Impact × LowDoseBeclom_Calculated_Coverage

Step 6: Blended disability for AsthmaEpsd uses: dw = 1 - ((1 - healthy_disability) * (1 - asthmaepsd_disability))

Main State Transitions (Step 10)

• DsFreeSus ↔ AsthmaEpsd (incidence and remission of asthma)
• AsthmaEpsd → Deceased (asthma-related mortality)

Interventions

Interventions Table

The modelled treatments for Asthma

For Asthma, there are four treatments. An intervention is something that has an effect on the main components of the model, such as disability, or mortality.

• LowDoseBeclom
  • Name in Spectrum: Low dose inhaled beclometasone + SABA
• HighDoseBeclom
  • Name in Spectrum: High dose inhaled beclometasone + SABA
• InhaledShortActingBeta
  • Name in Spectrum: Inhaled short acting beta agonist for intermittent asthma
• AsthmaOralPrednisolone
  • Name in Spectrum: Oral prednisolone + inhaled salbutamol and ipratroprium

While treatments are always present in the structure of the Asthma model, their coverage differs depending on the scenario.

Treatment Impacts

NOTE - These figures imply a modification of effect sizes. E.g. LowDoseBeclom reduces the CFR of AsthmaEpsd by 50% (-0.5).

Population in Need

NOTE - Refers to the proportion of people in AsthmaEpsd who are "in need" of this treatment. e.g. 30% of AsthmaEpsd are "in need" of InhaledShortActingBeta

The Asthma model scenarios

The Asthma_Null scenario

In the Asthma_Null, the coverage of all treatments is set to its baseline in the first year of the projection, then 0% afterwards.

Scenario CR1 - Acute treatment of asthma exacerbations with inhaled bronchodilators and oral steroids

In CR1:

• LowDoseBeclom continues at its baseline coverage for the entirety of the run
• HighDoseBeclom continues at its baseline coverage for the entirety of the run
• InhaledShortActingBeta continues at its baseline coverage for the entirety of the run
• AsthmaOralPrednisolone is set at its baseline coverage for the first year (2019) of the projection, and then to 95% coverage for the rest of the projection.

Scenario CR3 - Long-term management of asthma with inhaled bronchodilator and low-dose beclometasone

In CR3:

• LowDoseBeclom is set at its baseline coverage for the first year (2019) of the projection, and then to 95% coverage for the rest of the projection.
• HighDoseBeclom is set at its baseline coverage for the first year (2019) of the projection, and then to 95% coverage for the rest of the projection.
• InhaledShortActingBeta is set at its baseline coverage for the first year (2019) of the projection, and then to 95% coverage for the rest of the projection.
• AsthmaOralPrednisolone continues at its baseline coverage for the entirety of the run

Assumptions

NOTE - A document is a difficult place to put entire lists of assumptions, as many of the assumptions we have change over time, and many of the assumptions are arrays of values, which apply to males and females differently, as well as different ages.

Therefore, please look at ./data/asthma.csv as a reference guide for some assumptions. Values for disability weights have come from ./data/Asthma.xlsx which is taken from Spectrum. Furthermore, even though measures of incidence, prevalence, and mortality may appear in this document, the final values were taken from ./data/GBD_Country_DATA.xlsx.

The baseline scenario is the default scenario

The baseline scenario has a coverage rate that is static, and continues from the start year to the end year. This is important, because it completely removes the effect of the Calculation Component. This is because, in essence, the effect of treatments is governed by the calculation: effect = impact * coverage * population in need. However, coverage is no the current coverage, but the difference between the current coverage, and the starting coverage. Therefore: effect = impact * (current_coverage - starting_coverage) * population in need. Because current_coverage - starting_coverage = 0, there is no effect to add to the default values for disability and mortality.

The null scenario reduces the coverage, and therefore the impacts

In the null scenario, all treatments are reduced from the baseline coverage to zero. For example, in Afghanistan, it is assumed that the baseline coverage rate is 5%. Therefore: effect = impact * (0 - 0.05) * population in need = impact * -0.05 * population in need. Therefore, in this country, the null scenario implies a 5% reduction in the impact of the four treatments.

The scale-up scenario increases the coverage, and therefor the impacts

In the scale-up scenario, select treatments (one treatment in CR1, three treatments in CR3) are increased from baseline to 95% for the projection, starting in the second year. For the treatments that aren't selected, they are left at the baseline level, and thus do not contribute to effect calculations. Therefore, for a select treatment in Afghanistan: effect = impact * (0.95 - 0.05) * population in need = impact * 0.9 * population in need.