{"id":18989759,"url":"https://github.com/cdcgov/ww-inference-model","last_synced_at":"2025-04-22T11:12:01.468Z","repository":{"id":246101138,"uuid":"820071157","full_name":"CDCgov/ww-inference-model","owner":"CDCgov","description":"An in-development R package and a Bayesian hierarchical model jointly fitting multiple \"local\" wastewater data streams and \"global\" case count data to produce nowcasts and forecasts of both observations","archived":false,"fork":false,"pushed_at":"2024-12-28T23:18:55.000Z","size":2031,"stargazers_count":23,"open_issues_count":79,"forks_count":7,"subscribers_count":9,"default_branch":"main","last_synced_at":"2025-04-17T00:14:17.587Z","etag":null,"topics":["bayesian-inference","cmdstanr","forecasting","hierarchical-models","real-time-analytics","stan","wastewater-based-epidemiology"],"latest_commit_sha":null,"homepage":"https://cdcgov.github.io/ww-inference-model/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CDCgov.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS.md","contributing":".github/CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":".github/CODEOWNERS","security":null,"support":".github/SUPPORT.md","governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-06-25T18:31:46.000Z","updated_at":"2025-01-17T11:09:52.000Z","dependencies_parsed_at":"2024-06-25T21:41:04.816Z","dependency_job_id":"6085d975-aada-4219-862b-019b693ebd25","html_url":"https://github.com/CDCgov/ww-inference-model","commit_stats":null,"previous_names":["cdcgov/ww-inference-model"],"tags_count":2,"template":false,"template_full_name":"CDCgov/template","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CDCgov%2Fww-inference-model","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CDCgov%2Fww-inference-model/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CDCgov%2Fww-inference-model/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CDCgov%2Fww-inference-model/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CDCgov","download_url":"https://codeload.github.com/CDCgov/ww-inference-model/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250228640,"owners_count":21395958,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bayesian-inference","cmdstanr","forecasting","hierarchical-models","real-time-analytics","stan","wastewater-based-epidemiology"],"created_at":"2024-11-08T17:07:48.864Z","updated_at":"2025-04-22T11:12:01.437Z","avatar_url":"https://github.com/CDCgov.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# `wwinference`: joint inference and forecasting \u003cbr /\u003e from wastewater and epidemiological count data  \u003ca href=\"https://cdcgov.github.io/ww-inference-model/\"\u003e\u003cimg src=\"man/figures/logo.svg\" align=\"right\" height=\"139\" alt=\"wwinference website\" /\u003e\u003c/a\u003e\n\n\u003e [!CAUTION]\n\u003e This package is still in development.\n\u003e Note the package is still flagged as in development, though the authors plan on using it for production work in the coming weeks.\n\u003e All development is in public as part of the Center for Forecasting and Outbreak Analytics' goals around open development.\n\u003e Questions and suggestions are welcome through GitHub issues or a PR.\n\u003e\n\n## Overview\n\nThis project is an in-development R package, `{wwinference}` that estimates latent incident infections from wastewater concentration data and data on epidemiological count data, with an initial assumed structure that the wastewater concentration data comes from subsets of the population contributing to the \"global\" epidemiological count data, such as hospital admissions.\nIn brief, our model builds upon [EpiNow2](https://github.com/epiforecasts/EpiNow2/tree/main), a widely used [R](https://www.r-project.org/) and [Stan](https://mc-stan.org/) package for Bayesian epidemiological inference.\nWe modify EpiNow2 to add a model for the observed viral RNA concentration in wastewater, adding hierarchical structure to link the subpopulations represented by the observed wastewater concentrations in each wastewater catchment area.\n\nThe intention is for {wwinference} to provide a user-friendly R-package interface for running forecasting models that use wastewater concentrations combined with other more traditional epidemiological signals such as cases or hospital admissions.\nIt aims to be a re-implementation of the modeling components contained in the [wastewater-informed-covid-forecasting](https://github.com/CDCgov/wastewater-informed-covid-forecasting) project repository, with\nan emphasis here on making it easier for users to supply their own data.\n\nWe recommend reading the [model definition](model_definition.md) to learn more about how the model is structured and running the [\"Getting Started\" vignette](vignettes/wwinference.Rmd) for an example of how to fit the model to simulated data of COVID-19 hospital admissions and wastewater concentrations.\nThis will help make clear the data requirements and how to structure this data to fit the model.\n\n## Project Admins\n- Kaitlyn Johnson (kaitejohnson)\n- Dylan Morris (dylanhmorris)\n- George Vega Yon (gvegayon)\n- Sam Abbott (seabbs)\n- Damon Bayer (damonbayer)\n\n# Package workflow\nThe following depicts the suggested workflow for fitting the wastewater-informed forecasting model. See the [\"Getting Started\" vignette](https://cdcgov.github.io/ww-inference-model/articles/wwinference.html) for a full example.\n![](./man/figures/wwinference_workflow.png)\n\n# Installing and running code\n\n## Install R\nTo run our code, you will need a working installation of [R](https://www.r-project.org/) (version `4.1.0` or later). You can find instructions for installing R on the official [R project website](https://www.r-project.org/).\n\n## Install `cmdstanr` and `CmdStan`\nWe do inference from our models using [`CmdStan`](https://mc-stan.org/users/interfaces/cmdstan) (version `2.35.0` or later) via its R interface [`cmdstanr`](https://mc-stan.org/cmdstanr/) (version `0.8.0` or later).\n\nOpen an R session and run the following command to install `cmdstanr` per that package's [official installation guide](https://mc-stan.org/cmdstanr/#installation).\n\n```R\ninstall.packages(\"cmdstanr\", repos = c(\"https://mc-stan.org/r-packages/\", getOption(\"repos\")))\n```\n\n`cmdstanr` provides tools for installing `CmdStan` itself. First check that everything is properly configured by running:\n\n```R\ncmdstanr::check_cmdstan_toolchain()\n```\n\nYou should see the following:\n```\nThe C++ toolchain required for CmdStan is setup properly!\n```\n\nIf you do, you can then install `CmdStan` by running:\n```R\ncmdstanr::install_cmdstan()\n```\nIf installation succeeds, you should see a message like the following:\n```\nCmdStan path set to: {a path on your file system}\n```\n\nIf you run into trouble, consult the official [`cmdstanr`](https://mc-stan.org/cmdstanr/index.html) website for further installation guides and help.\n\n## Install `wwinference`\n\nOnce `cmdstanr` and `CmdStan` are installed, the next step is to install the package, `wwinference`.\nThe package provides tools for specifying and running the model, and installs other needed dependencies.\nThe package can be installed directly from github by running the following within an R session:\n```R\ninstall.packages(\"remotes\")\nremotes::install_github(\"CDCgov/ww-inference-model\")\n```\nConfirm that package installation has succeeded by running the following within an R session:\n\n```R\nlibrary(wwinference)\n```\n\n## Contributing to this package\nWe welcome and encourage contributions. Open an issue in the repository to request changes.\nTo contribute, fork the repository locally and open a pull request into the `main` branch.\n\n## Public Domain Standard Notice\nThis repository constitutes a work of the United States Government and is not\nsubject to domestic copyright protection under 17 USC § 105. This repository is in\nthe public domain within the United States, and copyright and related rights in\nthe work worldwide are waived through the [CC0 1.0 Universal public domain dedication](https://creativecommons.org/publicdomain/zero/1.0/).\nAll contributions to this repository will be released under the CC0 dedication. By\nsubmitting a pull request you are agreeing to comply with this waiver of\ncopyright interest.\n\n## Contributing Standard Notice\nAnyone is encouraged to contribute to the repository by [forking](https://help.github.com/articles/fork-a-repo)\nand submitting a pull request. (If you are new to GitHub, you might start with a\n[basic tutorial](https://help.github.com/articles/set-up-git).) By contributing\nto this project, you grant a world-wide, royalty-free, perpetual, irrevocable,\nnon-exclusive, transferable license to all users under the terms of the\n[Apache Software License v2](http://www.apache.org/licenses/LICENSE-2.0.html) or\nlater.\n\nAll comments, messages, pull requests, and other submissions received through\nCDC including this GitHub page may be subject to applicable federal law, including but not limited to the Federal Records Act, and may be archived. Learn more at [http://www.cdc.gov/other/privacy.html](http://www.cdc.gov/other/privacy.html).\n\n## License Standard Notice\nThe repository utilizes code licensed under the terms of the Apache Software\nLicense and therefore is licensed under ASL v2 or later.\n\nThis source code in this repository is free: you can redistribute it and/or modify it under\nthe terms of the Apache Software License version 2, or (at your option) any\nlater version.\n\nThis source code in this repository is distributed in the hope that it will be useful, but WITHOUT ANY\nWARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A\nPARTICULAR PURPOSE. See the Apache Software License for more details.\n\nYou should have received a copy of the Apache Software License along with this\nprogram. If not, see http://www.apache.org/licenses/LICENSE-2.0.html\n\nThe source code forked from other open source projects will inherit its license.\n\n## Privacy Standard Notice\nThis repository contains only non-sensitive, publicly available data and\ninformation. All material and community participation is covered by the\n[Disclaimer](DISCLAIMER.md)\nand [Code of Conduct](code-of-conduct.md).\nFor more information about CDC's privacy policy, please visit [http://www.cdc.gov/other/privacy.html](https://www.cdc.gov/other/privacy.html).\n\n## Records Management Standard Notice\nThis repository is not a source of government records, but is a copy to increase\ncollaboration and collaborative potential. All government records will be\npublished through the [CDC web site](http://www.cdc.gov).\n\n## Additional Standard Notices\nPlease refer to [CDC's Template Repository](https://github.com/CDCgov/template) for more information about [contributing to this repository](https://github.com/CDCgov/template/blob/main/CONTRIBUTING.md), [public domain notices and disclaimers](https://github.com/CDCgov/template/blob/main/DISCLAIMER.md), and [code of conduct](https://github.com/CDCgov/template/blob/main/code-of-conduct.md).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcdcgov%2Fww-inference-model","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcdcgov%2Fww-inference-model","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcdcgov%2Fww-inference-model/lists"}