EMOD-Generic-Scripts

See documentation at https://emod-hub.github.io/EMOD-Generic-Scripts/ for additional information.

Contents:

Directory	Description
env_Alma10 env_Amazon2023 env_Debian13 env_Fedora42 env_Rocky10 env_Ubuntu26	Definition files for Apptainer containers with various operating systems. Produces the the EMOD executable and schema file; creates an environment for running EMOD on COMPS with the python packages available to the embedded python interpreter. All files remain on COMPS and are provided to the various workflows as Asset Collection IDs.
local_python	Contains additional python scripts with helper functions common to all of the workflows.
model_covariance01	Demonstration simulations for heterogeneity in individual behavior.
model_covid01	Baseline simulations for SARS-CoV-2 in EMOD. Collab with MvG.
model_demographics01	Example demographics for UK measles simulations.
model_demographics_wpp01	Example demographics using UN WPP data as inputs.
model_measles_cod01	Documentation.
model_measles_gha01	Examination of RDT use and measles outbreak response using Ghana as an example context.
model_measles_nga01	Documentation.
model_measles_nga02	Documentation.
model_measles01	Estimates of measles burden under various policies for age of MCV1.
model_network01	Demonstration simulations for transmission of infectivity on a network.
model_polio_nga01	Example outbreak simulations for cVDPV2 in Nigeria.
model_rubella01	Projections of rubella infections and estimates of CRS burden following RCV introduction.
model_transtree01	Demonstration of the infector labeling feature and generation of explicit transmission networks.
refdat_mcv1	IHME MCV1 coverage estimates used to construct input files for EMOD simulations.
refdat_namesets	Namesets used for region identification.
refdat_poppyr	UN WPP age structured population estimates used to construct input files for EMOD simulations.
refdat_sias	Documentation.

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To get started:

1. Create and activate a virtual environment.

2. Install requirements:

   pip install .
   

3. Run an experiment (requires COMPS credentials):

   cd EMOD-Generic-Scripts/model_covariance01/experiment_covariance01
    python make01_param_dict.py
    python make02_lauch_sims.py
    python make03_pool_brick.py
   

4. Make figures:

   cd EMOD-Generic-Scripts/model_covariance01/figure_attackfrac01
   python make_fig_attackrate.py
   

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To build the documentation locally, do the following:

1. Create and activate a virtual environment.

2. Navigate to the root directory of the repo and enter the following

   pip install .[docs]
   mkdocs build
   

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Disclaimer

The code in this repository was developed by IDM and other collaborators to support our joint research on flexible agent-based modeling. We've made it publicly available under the MIT License to provide others with a better understanding of our research and an opportunity to build upon it for their own work. We make no representations that the code works as intended or that we will provide support, address issues that are found, or accept pull requests. You are welcome to create your own fork and modify the code to suit your own modeling needs as permitted under the MIT License.

Project status

EMOD-Hub projects are provided as open source software under the MIT License for community use, research, and development.

Unless otherwise noted, these projects are no longer actively maintained or supported by IDM or the Gates Foundation.

Community contributions are welcome, and trusted collaborators may review and merge pull requests, but no guarantees are made regarding support, pull request review, security response, maintenance, or release timelines.