PyRenew-HEW

| hewr | pyrenew-hew | pipelines | | ---- | ----------- | --------- | | | | |

The PyRenew-HEW project aims to create short-term forecasts of respiratory disease burden using the PyRenew library and several data sources:

• [x] Hospital Admissions from the National Healthcare Safety Network
• [x] Emergency Department Visits from the National Syndromic Surveillance Program
• [x] Wastewater virus concentration from the National Wastewater Surveillance System

This is a work in progress, and not all data sources are currently integrated into the model.

This repository contains code for the PyRenew-HEW model itself, as well as pipelines for running the model in production, and utilities for working with model outputs.

Containers

The project uses GitHub Actions for automatically building container images based on the project's Containerfile. The images are currently hosted on Github Container Registry and are built and pushed via the containers.yaml GitHub Actions workflow.

Images can also be built locally. The Makefile contains several targets for building and pushing images. Although the Makefile uses Docker as the default engine, the ENGINE environment variable can be set to podman to use Podman instead, for example:

```bash ENGINE=podman make container_build

Equivalent to:

podman build . -t pyrenew-hew -f Containerfile

```

Container images pushed to the Azure Container Registry are automatically tagged as either latest (if the commit is on the main branch) or with the branch name (if the commit is on a different branch). After a branch is deleted, the image tag is remove from the registry via the delete-container-tag.yaml GitHub Actions workflow.

Running Model Pipelines

[!NOTE]

Please contact a project maintainer if you believe you need access to pipelines.

Specific environment setup steps required can be found in the Routine Forecasting Standard Operating Procedure.

Additionally, pipelines as written can only be run within CFA's Virtual Analyst Platform.

Pipelines can be run interactively or non-interactively: - pipelines/azure_command_center.py is now the preferred method of running model fit pipeline jobs interactively. - The Makefile also provides targets that will run pipelines non-interactively. Run make help for more information.

General Disclaimer

This repository was created for use by CDC programs to collaborate on public health related projects in support of the CDC mission. GitHub is not hosted by the CDC, but is a third party website used by CDC and its partners to share information and collaborate on software. CDC use of GitHub does not imply an endorsement of any one particular service, product, or enterprise.

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