laser-measles

PyPI Package latest release MIT License Documentation Status

laser-measles is a spatial epidemiological modeling toolkit that helps researchers and public health teams simulate measles transmission, evaluate vaccination strategies, and plan outbreak responses. It translates surveillance data and demographic information into projections that inform immunization planning and resource allocation — with a focus on settings where measles remains a leading cause of vaccine-preventable death.

Developed by the Institute for Disease Modeling (IDM) at the Gates Foundation, laser-measles is built on the open-source LASER framework.

Installation

pip install laser-measles

Recommended stable release: version 0.13 — the current validated and supported version:

pip install "laser-measles>=0.13,<1.0"

For development installation:

pip install -e ".[dev]"

Getting started

The recommended first example is the Quick Start Tutorial.

Model types

laser-measles provides three modeling approaches:

  • ABM (Agent-Based Model): Individual-level simulation with stochastic agents and daily timesteps. Best for detailed heterogeneity and contact structure.
  • Biweekly Compartmental Model: Population-level SIR dynamics with 2-week timesteps. Recommended for scenario building and policy analysis.
  • Compartmental Model: Population-level SEIR dynamics with daily timesteps. Recommended for parameter estimation and outbreak modeling.
from laser.measles.abm import ABMModel, ABMParams

params = ABMParams(num_ticks=365, seed=42, start_time="2000-01")
model = ABMModel(scenario, params)
model.run()

Documentation

Full documentation is available at laser.idmod.org/laser-measles.

AI-assisted code generation & ChatBot (Jenner)

jenner-measles-mcp is a Model Context Protocol (MCP) server that lets Claude and other MCP-compatible tools search the laser-measles documentation and generate model code from natural-language prompts. See InstituteforDiseaseModeling/laser-mcp for setup, supported clients, and the deployed endpoint.

Foundation employees can use JENNER-Measles-GPT here.

Contributing

Contributions are welcome. See CONTRIBUTING.md for development setup, testing, and submission guidelines.

Bug reports and feature requests can be filed on the GitHub issue tracker.

License

MIT License — Copyright (c) 2026, Gates Foundation

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Credits

Author: Christopher Lorton, Jonathan Bloedow, Katherine Rosenfeld, Kevin McCarthy

Maintainer: Christopher Lorton

GitHub Statistics

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License expression

MIT
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Requires

Python >=3.10

Provides Extra

dev docs examples full

Tags

measles spatial modeling laser

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