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Getting Started

This guide will help you get started with the Health Service Disruption Mapping application.

Accessing the Application

The application is hosted on Hugging Face Spaces:

https://huggingface.co/spaces/CIJBoulange/health-disruption-mapping

First Load

The app may take 30-60 seconds to wake up if it hasn't been used recently.

Data Source

This app visualizes outputs from the FASTR Analytics Platform.

The FASTR Analytics Platform is a web-based tool designed to support data quality assessment, adjustment, and analysis for routine health data. It allows users to upload and analyze data from various sources, including DHIS2, with built-in statistical methods to generate an adjusted dataset and run priority analyses on selected indicators.

Data Flow

graph LR
    A[HMIS Data] --> B[M1: Data Quality Assessment]
    B --> C[M2: Data Quality Adjustment]
    C --> D[M3: Service Utilization]

    C -->|M2 output| E[Year-on-Year Tab]
    D -->|M3 output| F[Disruption Map]
    D -->|M3 output| G[Multi-Indicator]
    D -->|M3 output| H[Heatmap]

Interface Overview

The application has several tabs:

Disruption Map

Main choropleth map view for a single health indicator. Shows percent change between actual and expected service delivery across administrative areas. Use this for focused analysis of one indicator at a time.

Input: M3 (Service Utilization) output

Multi-Indicator

Side-by-side comparison of 2 indicators on the same map layout. Useful for identifying patterns across related services (e.g., comparing ANC1 and facility deliveries).

Input: M3 (Service Utilization) output

Year-on-Year Change

Compares service utilization between the current year and the previous year. Shows whether services are recovering, stable, or declining compared to the same period last year.

Input: M2 (Data Quality Adjustment) output

Options:

  • Adjusted vs Raw: Toggle between outlier-adjusted values or raw reported values. Adjusted values correct for reporting anomalies identified in M1.
  • Period selection: Compare specific months or cumulative year-to-date totals
  • Indicator: Select which health service to analyze

Use case: Track recovery after a disruption event, monitor seasonal patterns, or assess whether interventions are having an impact compared to the baseline year.

Heatmap

Matrix visualization showing all indicators across all administrative areas. Quickly identify which services and locations have the most severe disruptions.

Input: M3 (Service Utilization) output

Data Table

Raw data view in tabular format. Filter, sort, and export the underlying numbers.

Language Toggle

Click the EN/FR button in the sidebar to switch between English and French. All labels, legends, and map titles will update accordingly.

Basic Workflow

  1. Select Country: Choose from the dropdown menu
  2. Upload Data: Upload your M3 disruption CSV file
  3. Select Parameters: Choose year and indicator
  4. View Map: The map automatically updates
  5. Export: Download the map as PNG

Next Steps