Epilepsy Model

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1. Overview of the Model

This document describes the WHO - MSD - Epilepsy model, which is a botech implementation of the Spectrum Epilepsy Model.

The primary purpose of this model is to simulate the progression of epilepsy within a population and to understand the potential impact of various interventions. It helps to model how an individual's health status regarding epilepsy can change over time, moving between states such as being healthy, having epilepsy, receiving treatment, or recovering.

By simulating these processes, the model can assist decision-makers in understanding the potential effects of different health programs and interventions aimed at addressing epilepsy. This can help in planning and allocating resources more effectively. The model runs from the year 2025 to 2050.

2. The Model's Building Blocks: Population Groups and How They Connect

The model is constructed from various components that represent different population segments, health states, and influential factors. These are connected to show how the population's health can change.

a. Population Groups and Key Factors (Nodes):

The model uses "states" or "groups" (called nodes) to represent different segments of the population or important factors that influence health.

Key population groups (STATE nodes) in this model include:

  • DsFreeSus: This group represents the healthy population, susceptible to developing epilepsy but currently free of the active condition.
  • EpilepsyEpsd: This group represents individuals who are currently experiencing epilepsy.
  • Deceased-DsFreeSus: This represents individuals from the "DsFreeSus" group who have passed away due to general mortality.
  • Deceased-EpilepsyEpsd: This represents individuals from the "EpilepsyEpsd" group who have passed away.
  • Healthy Years Lived: This is a special state that accumulates the healthy years lived by the population, considering the impact of disability.

Other important nodes represent fixed numbers, rates, or intermediate calculations:

  • CONSTANT nodes: These are fixed values or rates used as inputs. Examples include:

    • Epilepsy_Disability_Weight: A fixed value representing the disability associated with epilepsy.
    • Healthy_Disability_Weight: A fixed value representing the disability for the healthy population (typically zero).
    • EpilepsyEpsd_Incidence_Rate: The baseline rate at which new cases of epilepsy appear in the healthy population, based on data for the specified country and condition.
    • EpilepsyEpsd_Remission: The baseline rate at which individuals with epilepsy might go into remission, based on data for the specified country and condition.
    • EpilepsyEpsd_CFR: The Case Fatality Rate for epilepsy.
    • AntiEpilepticBasicPsych_Disability_Impact: The reduction in disability due to the "Basic psychosocial treatment plus anti-epileptic medication" intervention.
    • AntiEpilepticBasicPsych_Remission_Impact: The increase in remission rate due to the intervention.
    • AntiEpilepticBasicPsych_Coverage: The proportion of the eligible population reached by the "Basic psychosocial treatment plus anti-epileptic medication" intervention. This can change over time.
    • Adherence parameters (e.g., AntiEpilepticBasicPsych-Adherence).

  • SURROGATE nodes: These are temporary holding places for calculations that help the model progress. For example:

    • EpilepsyEpsd Incidence: A temporary store for the number of new epilepsy cases calculated in a time step before they are added to the "EpilepsyEpsd" group.
    • EpilepsyEpsd Remission: A temporary store for the number of people remitting from epilepsy in a time step.
    • EpilepsyEpsd Mortality: A temporary store for calculations related to deaths from epilepsy.
    • DsFreeSus HYL: A temporary calculation for the healthy years lived by the "DsFreeSus" group.

  • FUNCTION nodes: These nodes perform calculations based on their inputs. Examples include:

    • Combined_HYL: Calculates the overall health-adjusted life years, considering disability weights and intervention effects.
    • Disability_Effect_Transform: Calculates the combined effect of interventions on reducing disability.
    • Remission_Effect_Transform: Calculates the combined effect of interventions on increasing remission.
    • Births: Stores the number of births occurring in the population during a time step.

b. Connections and Movements (Links):

"Links" show how people move between population groups or how factors influence each other.

Key connections in the model include:

  • Population Dynamics:

    • DsFreeSus -> Births and EpilepsyEpsd -> Births: These links calculate the number of births from individuals in the "DsFreeSus" (healthy) and "EpilepsyEpsd" groups, respectively. This is based on fertility rates from the specified country. The total births are stored in the "Births" node.
    • Births -> DsFreeSus: New male and female births are added to the "DsFreeSus" (healthy) population group. This uses sex ratio data for the specified country.
    • Migration - DsFreeSus and Migration - EpilepsyEpsd: These links adjust the number of people in the "DsFreeSus" and "EpilepsyEpsd" groups to account for people moving into or out of the area, based on national migration data.
    • BackgroundMortality DsFreeSus (DsFreeSus -> Deceased-DsFreeSus) and Background Mortality EpilepsyEpsd (EpilepsyEpsd -> Deceased-EpilepsyEpsd): These links move individuals from the "DsFreeSus" and "EpilepsyEpsd" groups to their respective "Deceased" states. This movement is based on general death rates obtained for the specified country. People are removed from the source group.

  • Epilepsy Progression and Recovery:

    • Prevalence DsFreeSus -> EpilepsyEpsd: This link represents the initial allocation of the population into the "EpilepsyEpsd" state based on existing prevalence data for the specified country and condition. People are moved out of "DsFreeSus".
    • EpilepsyEpsd_Incidence_Rate influences EpilepsyEpsd Incidence -> EpilepsyEpsd: New cases of epilepsy arise from the "DsFreeSus" group and move to the "EpilepsyEpsd" group. The rate is determined by EpilepsyEpsd_Incidence_Rate. (Note: Source file links EpilepsyEpsd Incidence to AsthmaEpsd, assumed to be EpilepsyEpsd).
    • EpilepsyEpsd_Remission rate influences EpilepsyEpsd Remission -> DsFreeSus: Individuals in the "EpilepsyEpsd" group can go into remission and move back to the "DsFreeSus" group. The base rate is determined by EpilepsyEpsd_Remission and can be modified by intervention effects on remission. (Note: Source file links EpilepsyEpsd Remission target as AsthmaEpsd, assumed to be DsFreeSus).
    • EpilepsyEpsd_CFR influences Case Fatality EpilepsyEpsd (EpilepsyEpsd -> Deceased-EpilepsyEpsd): This pathway represents deaths due to epilepsy, using the Case Fatality Rate via the EpilepsyEpsd Mortality surrogate.

  • Intervention Effects on Disability and Remission: The model includes the "Basic psychosocial treatment plus anti-epileptic medication" intervention (AntiEpilepticBasicPsych).

    • Links like AntiEpilepticBasicPsych_Disability_Impact -> AntiEpilepticBasicPsych_Disability_Effect: The inherent disability reduction efficacy of the intervention is combined with its coverage (AntiEpilepticBasicPsych_Calculated_Coverage) and population in need (AntiEpilepticBasicPsych_PIN) to determine the overall AntiEpilepticBasicPsych_Disability_Effect. This effect then influences the Combined_DW (Combined Disability Weight). Adherence (AntiEpilepticBasicPsych-Adherence -> AntiEpilepticBasicPsych_Disability_Impact) also modifies the intervention's impact.
    • Similar links exist for remission effects (AntiEpilepticBasicPsych_Remission_Impact -> AntiEpilepticBasicPsych_Remission_Effect) which modify the EpilepsyEpsd Remission rate via Remission_Effect_Transform.
    • These effects are aggregated in their respective _Effect_Transform nodes.

  • Calculating Health Outcomes (DALYs, HYL):

    • Epilepsy_Disability_Weight and Healthy_Disability_Weight are used in HYL calculations.
    • DsFreeSus HYL and EpilepsyEpsd HYL (potentially Modified_HYL after intervention effects) contribute to the "Healthy Years Lived" state.
    • Years of Life Lost (YLLs) are calculated when individuals move to Deceased-DsFreeSus (recorded as YLL-DsFreeSus) or Deceased-EpilepsyEpsd (recorded as YLL-EpilepsyEpsd).
    • Years Lived with Disability (YLDs) are calculated for DsFreeSus (YLD-DsFreeSus) and EpilepsyEpsd (recorded as YLD-EpilepsyEpsd, based on Combined_DW).
    • DALYs (Disability-Adjusted Life Years) are then calculated by summing the relevant YLL and YLD components into a "DALYs" node.

  • Resource Utilization:

    • Links like PopulationReached-AntiEpilepticBasicPsych -> [Resource Node]: When individuals receive the intervention (represented by PopulationReached-AntiEpilepticBasicPsych), this triggers resource use. The model calculates demand for personnel time and medicines, which are then translated into costs.

This structure allows the model to simulate how the population moves between health states, how interventions affect these transitions and outcomes, and what resources are consumed.

3. How the Model Simulates Changes Over Time (Subroutines)

The model simulates changes year by year (or for other defined time periods) by following a sequence of steps, called "subroutines." Here's what happens in each main step:

  1. Flush unneeded values: This step resets or clears out temporary values from the previous time period to prepare for new calculations.
  2. Generate the population: This step sets up the initial numbers of people in the main healthy population group ("DsFreeSus") at the beginning of a time period.
  3. Allocate prevalence: This step distributes the initial population into the "EpilepsyEpsd" state based on existing disease prevalence at the start of the simulation (for the first year) or adjusts based on incidence in subsequent years.
  4. Generate the base values of the surrogate nodes: Calculates starting values for temporary holding places used in calculations.
  5. Generate the base values of the function nodes for constants: Sets up initial values for nodes that perform calculations based on other inputs.
  6. Generate the values of the constants: Loads or calculates fixed input values like disability weights, baseline incidence/remission rates, CFR, and intervention characteristics.
  7. Multiply impact (efficacy) by the adherence: Adjusts the effectiveness of interventions based on how well people adhere to treatment.
  8. Calculate the Incidence Surrogate: Computes the number of new epilepsy cases based on the incidence rate.
  9. Calculate the remission surrogate: Computes the number of people remitting from epilepsy based on the remission rate.
  10. Calculate Coverage: Determines the actual coverage levels for the intervention, considering baseline, target, and scale-up parameters.
  11. Calculate Disability Effects: Computes the impact of the intervention on reducing the disability associated with epilepsy.
  12. Add remission impact to remission effect: Combines the inherent remission efficacy of the intervention with other factors.
  13. Modify remission effect by coverage: Adjusts the overall remission effect based on the proportion of the population reached by the intervention.
  14. Modify remission effect by PIN: Further refines the remission effect based on the proportion of the population in need of the intervention.
  15. Add calculated remission impact to transform: Aggregates the remission effects.
  16. Modify remission surrogate by remission effect: Adjusts the number of people remitting based on the combined impact of the intervention.
  17. Remove Disability Effects from 1.0: This step calculates a factor representing the remaining disability after accounting for intervention effects.
  18. Calculate Healthy and Epilepsy HYL: Calculates Health-Adjusted Life Years for healthy individuals and those with epilepsy, considering their respective disability weights.
  19. Calculated Combined HYL: Aggregates HYL contributions, potentially modified by intervention effects on disability.
  20. Calculate Combined DW: Calculates the overall disability weight experienced by those with epilepsy, considering intervention effects.
  21. Modify Combined DW with intervention effects: Adjusts the disability weight based on the effectiveness of the intervention in reducing disability.
  22. Calculated Modified HYL: Calculates the final Health-Adjusted Life Years for those with epilepsy after accounting for intervention-modified disability.
  23. Calculate DsFreeSus Disability Surrogate: Calculates HYL for the healthy, susceptible population.
  24. Calculated Epilepsy HYL Surrogate: Calculates HYL for the population with epilepsy, considering modified disability.
  25. Calculate Mortality Surrogate (Add CFR to Surrogate): Incorporates the base case fatality rate into the calculation of disease-specific deaths.
  26. Record Births to Birth Node: The model calculates the number of births occurring in the population and stores this total.
  27. Main Routine (Synchronous transfer): In this core step, the model applies rates and proportions to simulate people moving between groups (e.g., from healthy to having epilepsy, from epilepsy to remission, or to a deceased state). This also includes background mortality and applying migration effects.
  28. Push EpilepsyEpsd to Population Reached: Determines the number of individuals with epilepsy who are eligible for and could potentially receive the intervention.
  29. Modify Population Reached by PIN and Coverage: Calculates the actual number of people reached by the intervention by applying the population in need (PIN) proportions and the calculated coverage rates.
  30. Record HYL: The model updates the total "Healthy Years Lived" by summing contributions from different population groups.
  31. Add prevalence to YLD nodes: Calculates the number of people living with disability in each state for YLD calculations.
  32. Multiply YLDs by Disability Weights: Applies the relevant disability weights to the populations in each state to quantify YLDs.
  33. Migration of Populations: Adjusts population numbers in states to account for net migration.
  34. Age the populations: This step simulates the entire population in each state getting older by one time unit (e.g., one year).
  35. Women give birth: New births (calculated earlier) are added to the healthy population group, distributed by sex.
  36. Add values to DALYs: This step aggregates YLDs and YLLs to calculate the total DALYs.
  37. Calculate resource requirements and costs: Based on the number of people receiving the intervention, this step calculates the demand for various resources (personnel time, medicines, visits) and their associated costs.
  38. Record Metrics: This step records important results and numbers from the model for the current time period, such as population sizes in different states, DALYs, HYL, and resource utilization.

This sequence is repeated for each year of the simulation, allowing the model to project changes in population health and intervention impact over time.

4. Resource Requirement Assumptions

The model incorporates specific assumptions about the resources needed for the "Basic psychosocial treatment plus anti-epileptic medication" intervention.

Target Population Node in Model: PopulationReached-AntiEpilepticBasicPsych

Drugs and Supplies Required Per Client (per year):

  • Phenytoin, 100 mg: 5% of clients use this, 3 units/day for 365 days.
  • Carbamazepine, 200mg: 15% of clients use this, 3 units/day for 365 days.
  • Lamotrigine oral 200 mg: 30% of clients use this, 1.5 units/day for 365 days.
  • Valproate, 500 mg: 50% of clients use this, 2.0 units/day for 365 days.

Personnel Time Required per Case (per year):

  • Doctor: Two 10-minute visits with a generalist/primary care doctor.
  • Nurse: Two 10-minute visits with a nurse.

Visits Required per Case (per year):

  • A total of four outpatient visits (two with a doctor and two with a nurse).

5. Coverage Assumptions for Scenarios

The model can be run under different scenarios, each with specific assumptions about the coverage level of the "Basic psychosocial treatment plus anti-epileptic medication" intervention and how it changes over the simulation period (2025-2050). Scale-up is generally from 2025 (Year 0 / Index 0) to 2030 (Year 5 / Index 5).

Scenario: Default Scenario

Description: Where default coverage rates stay the same.

  • Intervention: Basic psychosocial treatment plus anti-epileptic medication
    • Baseline Coverage: 40.0%
    • Target Coverage: 40.0%
    • Scale-up Period: from 2025 to 2030 (coverage remains constant at baseline; Scale-up Start Year Index 0, Scale-up End Year Index 5)

Scenario: Basic psychosocial treatment plus anti-epileptic medication

Description: Scaling up the intervention to target coverage.

  • Intervention: Basic psychosocial treatment plus anti-epileptic medication
    • Baseline Coverage: 40.0%
    • Target Coverage: 80.0%
    • Scale-up Period: from 2025 to 2030 (Scale-up Start Year Index 0, Scale-up End Year Index 5)

Issues for Authors

  1. Node Name Mismatches in Links (Section 2.b):
    • The source document mentions EpilepsyEpsd Incidence -> AsthmaEpsd. It is assumed AsthmaEpsd here is a placeholder and should refer to EpilepsyEpsd.
    • Similarly, the target of the link from EpilepsyEpsd Remission surrogate is described as AsthmaEpsd. It is assumed AsthmaEpsd here should refer to DsFreeSus. These assumptions have been incorporated into the reformatted text but should be verified.
  2. Scale-Up Index vs. Year: The Epilepsy documentation uses "Scale-up Start/End Year Index" (0 and 5). This has been interpreted as Year 1 (2025) and Year 6 (2030) of the simulation respectively, implying a 5-year scale-up period to reach the target by the start of the 6th year. This interpretation should be confirmed.
  3. Clarity on "State holding the balance of the healthy population" for DsFreeSus: While DsFreeSus is generally understood as the healthy susceptible pool, the original phrasing ("State holding the balance of the healthy population") is slightly different from other models. The interpretation as "healthy susceptible" has been maintained for consistency.
  4. Resource Linkage Naming: The source document mentions model equivalents for drug resources (e.g., Receiving Phenytoin, 100mg). These more specific node names are useful for modelers but have been summarized under the drug name in the reformatted Section 4 for brevity, aligning with the style of other documents. The link to Doctor Minutes and Nurse Minutes via specific outpatient visit nodes is also implied.
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