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ClimAID - Climate Change impact using AI on Diseases

ClimAID is an integrated toolkit for modeling, forecasting, and projecting climate-sensitive diseases such as dengue and malaria using machine learning and climate model ensembles.

  • ClimAID has inbuilt climate data for South Asian countries, namely India, Nepal, Bhutan, Sri Lanka, Myanmar, Afghanistan, Pakistan and Bangladesh.

  • ClimAID support data from other countries through the global mode on the browser interface.


What you can do

  • Analyze historical disease patterns
  • Integrate climate variables (temperature, rainfall, humidity)
  • Automatically detect optimal lag effects using AutoML
  • Train hybrid ML models
  • Generate CMIP6-based future projections
  • Identify outbreak risk under climate change scenarios
  • Generate automated policy reports using the integrated C-DSI or local LLM models.

Quick Example using Codes

from climaid.climaid_model import DiseaseModel

dm = DiseaseModel(
    district='IND_Mumbai_MAHARASHTRA',
    disease_file="dengue_data.xlsx",
    disease_name="Dengue"
)

dm.optimize_lags()
dm.train_final_model()

Workflow

ClimAID has two interfaces,

  • ClimAID Browser Interface (For both South Asian + Global countries)

    For initialisation through terminal, use

        climaid browse
    
  • ClimAID Wizard Interface (For South Asian countries)

    For initialisation through terminal, use

        climaid wizard
    

Documentation

The full documentation is available here: https://sam-as.github.io/ClimAID/


Designed for

  • Epidemiologists
  • Climate scientists
  • Public health analysts
  • Data scientists

Dependencies & License

Dependencies

  • Core Requirements

    pandas  
    numpy  
    geopandas  
    matplotlib  
    scikit-learn  
    xarray  
    regionmask  
    plotly  
    xgboost  
    optuna
    
  • Additional Utilities

    These packages support extended functionality and will be auto-installed.

    requests
    joblib
    fastapi
    uvicorn
    typer
    markdown
    fastparquet
    python-multipart
    seaborn
    openpyxl
    
  • Optional (LLM Support)

    To enable local LLM-based report generation:

    pip install climaid[full]
    

    Includes:

    ollama 
    

License

Designed by Avik Kumar Sam & Harish C. Phuleria as an open-access software.


Release files for climaid 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Table of built distributions (wheels) for climaid 0.1.2
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