Dengue Epi-Scanner App

This H2O Wave application analyzes the expansion of dengue and chikungunya in Brazil using up-to-date incidence data from Infodengue.

Getting Started

You can set up your development environment using either Python venv (simplest) or Conda/Mamba (best for handling system dependencies like GEOS or libpq).

Option 1: Standard Python venv (Recommended)

This approach is best if you already have the necessary system libraries (or if your OS handles them automatically via wheels).

# Create and activate virtual environment
python -m venv .venv
source .venv/bin/activate

# Install Poetry and dependencies
pip install poetry
poetry install --with dev

Option 2: Conda / Mamba (Best for Complex System Deps)

Use this if you encounter issues with libraries like geopandas or psycopg2.

• Miniforge or Anaconda installed

# Install base environment (Python + system libs + poetry)
mamba env create -f conda/env-base.yaml
conda activate episcanner

# Install project dependencies via Poetry
poetry install --with dev

Populate the data/ directory

python ./epi_scanner/management/cli.py [disease]

Then start the app:

wave run --no-reload --no-autostart epi_scanner.app

Running with containers (Makim)

Pre-requisites

• Docker installed and running
• Miniforge installed
• Poetry installed

Makim is used to standardize helper commands for local, CI, and production container workflows.

Start the app (dev profile)

# Start/build the container stack for the Wave app
makim episcanner.deploy --profile dev --service wave

Wait for the service to become healthy

makim episcanner.container-wait --service wave

Stop and remove containers/volumes

makim episcanner.down --profile dev --service wave

Tip: You can replace dev with ci or prod depending on your target environment.

Data Update

The data update is now generated by the epi_scanner-downloader tool.

For more information, please see the epi_scanner-downloader repository.