Disease and Economic Burden Calculator (DEB-Cal)

Prevalence, DALYs & Economic Burden forecasting tool

Welcome to the Self-harm Prevalence, DALYs & Economic Burden forecasting tool

Deliberate self-harm represents a substantial public health crisis in India, disproportionately impacting the younger, economically productive age cohorts. This tool implements a rigorous, methodology-driven mathematical model to forecast age-standardised prevalence rates and evaluate the macroeconomic direct and indirect burden in India from 2021 to 2035.

Research Context: This framework utilizes the human capital approach to attribute economic values to lost DALYs based on cohort-specific productivity weights and per-capita GDP/GNI indicators, matching peer-reviewed methodologies in musculoskeletal health economics.

auto_storiesHow to Use the Forecasting tool

  1. Switch to Forecasting tool Tab: Click on the "Forecasting tool" tab in the navigation menu above to access the interactive calculator dashboard.
  2. Configure Settings: The country is preset to India. You can choose from multiple oral conditions using the dropdown. You can choose the active sex (Male, Female, or Total) using the selector dropdown to load respective curves.
  3. Adjust Economic Metrics: Switch between GNI-based and GDP-based calculations using the Economic Metric basis dropdown. Standard Indian per-capita indicators ($2,170 GNI and $2,240 GDP) are used automatically.
  4. Run Simulations: Customize historical rates, cohort productivity weights, and annual cohort DALYs directly in the tables, then click "Compute Projections" to fit the best ARIMA model and update the forecasts, charts, and tables instantly.
  5. Export Results: Print the formatted reports directly to an A4 portrait PDF or export the full simulation datasets to Excel.

settingsTechnical Specifications

  • ARIMA Engine: Built with a custom JS implementation of auto.arima. The engine dynamically checks differencing, fits parameter configurations, and evaluates model fit using Bayesian Information Criterion (BIC), Mean Absolute Percentage Error (MAPE), and RMSE.
  • Interactive Charting: Implements Chart.js to render time-series forecasts with semi-transparent confidence interval ribbon bands for upper and lower 95% limits.
  • Data Exchange & SheetJS: Integrated with xlsx.js to enable client-side Excel ingestion (Excel upload parses columns) and structured Excel outputs.
  • Fluent Styling Architecture: Styled with vanilla HTML5 and CSS3 (custom CSS variables, glassmorphic cards, Fluent UI fonts, hover micro-animations) to match high-end corporate web dashboards.

calculateMathematical Model & Formulas

This tool computes the direct medical burden and indirect productivity losses using a Cost-of-Illness (COI) framework. Direct treatment costs and indirect productivity losses are scaled dynamically over the forecast horizon.

Direct Economic Burden:
Direct Costt = Patientst × Treatment Cost × (1 + Inflation rate)t

Where:
• t represents the forecast year offset (t = 0 for 2021, t = 1 for 2022, ..., up to 2035).
• Patient case count is derived from prevalence rate projections:
Patientst = (Prevalence Ratet / 100,000) × Populationt

Indirect Economic Burden (GNI / GDP basis):
Indirect Costt = Σi (DALYsi,t × Productivity Weighti) × (GNI or GDP per Capita) × (1 + Inflation rate)t

Where:
• i represents each individual cohort age group (e.g. 0-14, 15-39, etc.).
• t represents the forecast year offset (t = 0 for 2021, t = 1 for 2022, ...).
• DALYs per cohort are scaled dynamically:
DALYsi,t = DALYsi,2021 × (Patientst / Patients2021)