Model of Inter-Generational Health, Transmission, and Interventions (MIGHTI)

Warning! MIGHTI is still in the early stages of development. It is being shared solely for transparency and to facilitate collaborative development. It is not yet ready to be used for real research or policy analysis without careful validation.

MIGHTI is an agent-based modeling framework designed to simulate the dynamics of infectious diseases, non-communicable diseases (NCDs), and their interactions over time. MIGHTI builds on the Starsim architecture.

Documentation: See the MIGHTI Wiki for usage instructions and examples.

Requirements

• Python 3.9–3.13 (CI runs on Python 3.12)
• NumPy >= 2.0 (required by STIsim 1.4.0+; older NumPy may crash on argsort(..., stable=True))
• Starsim 3.0.x (tested with starsim==3.0.3)
• STIsim 1.4.0 (tested with STIsim==1.4.0)

Installation

MIGHTI is not yet available on PyPI, but you can install it directly from GitHub:

git clone https://github.com/starsimhub/mighti.git
cd mighti

For a fully reproducible environment (recommended), install pinned dependencies:

pip install -r requirements.txt
pip install -e .

If you installed with pip install -e . but are seeing an error like TypeError: argsort() got an unexpected keyword argument 'stable', your NumPy is too old. Fix with:

pip install -U "numpy>=2.0.0"

Running an Example

python mighti_main.py

This will run a sample simulation that includes demography, HIV, and NCD modules. The example script saves a quick-check plot into the outputs/ folder.

Usage and Documentation

MIGHTI is based on Starsim, please refer to Starsim documentation for additional information.

Data policy (raw vs curated)

MIGHTI main is released as a modeling platform/library plus small example driver scripts. To keep releases lightweight and reduce licensing/provenance risk, we follow this convention:

• Included in releases: - Curated, minimal example inputs in data/processed/ (enough to run the example scripts) - Small fixtures in tests/test_data/ used by the automated test suite
• Not included in stable releases: - data/raw/ and associated cleaning/pre-processing scripts and raw source files

If you need to rebuild curated inputs from raw sources, see data/raw/README.md and related tooling in this repository (development use).

Public API and Stability

MIGHTI is still evolving. To make it safe for others to build on, we define a stable public API surface and treat everything else as internal/experimental.

Stable entrypoints (preferred usage)

• Import MIGHTI as a namespace package:

import mighti as mi

• Use namespaces for most functionality (stable module-level entrypoints):

# Diseases
t2d = mi.diseases.Type2Diabetes(...)

# Analyzers
prev = mi.analyzers.PrevalenceAnalyzer_HIV(...)

# Connectors / interactions
conn = mi.interactions.NCDHIVConnector(...)

# Social determinants of health (SDoH)
housing = mi.sdoh.NeighbourhoodSituation(...)

# Interventions
art = mi.interventions.ARTwithCASM(...)

Plotting policy

Plotting utilities are available, but are intentionally not imported into the top-level namespace. Import explicitly when needed:

from mighti.analysis.plotting import plot_mean_prevalence

Backwards compatibility

Some older code may still work with mi.SomeClass due to a temporary compatibility shim. New code should prefer the namespace style above.

Internal/experimental (may change without notice)

• Anything in mighti.calibration and most stored calibration artifacts
• Service-use analyzers in mighti.analyzers.analyzer_serviceuse (currently stubs)
• Scripts in the repo root (e.g., mighti_main.py) are examples/drivers, not API contracts

Contributing

Contributions to the MIGHTI project are welcome! Please read CONTRIBUTING.rst for details on our code of conduct, and the process for submitting pull requests.

Disclaimer

This code was developed by researchers at NYU, IDM, and collaborators. It is shared under the MIT License to foster reproducibility and future development. No guarantees are made regarding functionality or support. You are free to fork and modify the code under the terms of the license.

References

The MIGHTI framework incorporates data from the following public sources:

• Demography data: World Population Prospects 2024 https://population.un.org/wpp/downloads?folder=Standard%20Projections&group=Mortality
• Disease data: Global Burden of Disease Study (GBD) https://vizhub.healthdata.org/gbd-results/
• HIV data: • Demographic and Health Surveys (DHS) https://dhsprogram.com/pubs/pdf/FR202/FR202.pdf
  • Swaziland HIV Incidence Measurement Survey (SHIMS) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5291824/