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README.md

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+# EPI-Eval
+
+A curated collection of large epidemiological datasets, normalized to a single
+schema so they can be searched, joined, and benchmarked against each other.
+
+## What we track
+
+Time-series surveillance data on infectious disease — primarily respiratory
+viruses (flu, COVID-19, RSV) and arboviral disease (dengue, Zika,
+chikungunya), with smaller coverage of notifiable, mortality, wastewater, and
+behavioural / search signals. Sources come from CDC, WHO, ECDC, PAHO, OWID,
+and national public-health agencies; we re-publish them as Parquet with a
+consistent set of row-level columns (`date`, `location_id`, `location_level`,
+optional `condition` / `case_status` / `as_of`) and a metadata header
+describing pathogens, geography, cadence, and per-column units.
+
+## Why
+
+Forecasting and modeling work routinely stalls on data plumbing — finding the
+canonical version of a series, normalizing geography codes, reconciling
+reporting cadences, tracking when a source was last revised. The goal of this
+org is to do that work once, in the open. 
+
+## Schema
+
+Every dataset card on this org uses the same frontmatter format
+([schema v0.1](https://github.com/ChrisHarig/apart-forecasting-tool/blob/main/upload_pipeline/schema/schema_v0.1.md)),
+validated against a controlled vocabulary
+([`vocabularies.yaml`](https://github.com/ChrisHarig/apart-forecasting-tool/blob/main/upload_pipeline/schema/vocabularies.yaml)).
+Curated metadata (pathogens, license, units) lives alongside computed metadata
+(time coverage, row count, observed cadence) generated at ingest.
+
+## Contributing a dataset
+
+The ingest pipeline is in
+[`apart-forecasting-tool/upload_pipeline`](https://github.com/ChrisHarig/apart-forecasting-tool/tree/main/upload_pipeline).
+A new dataset is one `ingest.py` + `card.yaml` under
+`upload_pipeline/sources/<source_id>/`; the validator confirms schema fit
+before upload. Each new truth dataset auto-creates an empty
+`<id>-predictions` companion at upload time.
+
+## Datasets (21)
+
+### Respiratory
+
+| Dataset | Pathogens | Geography | Cadence |
+| --- | --- | --- | --- |
+| [CDC FluSurv-NET — weekly flu hospitalisation rates](https://huggingface.co/datasets/EPI-Eval/delphi-flusurv) | influenza | US | weekly |
+| [CDC NHSN Hospital Respiratory Data (HRD)](https://huggingface.co/datasets/EPI-Eval/nhsn-hrd) | influenza, sars-cov-2, rsv | US | weekly |
+| [CDC NREVSS — weekly RSV test specimens and positives](https://huggingface.co/datasets/EPI-Eval/cdc-nrevss-rsv) | rsv | US | weekly |
+| [COVID Tracking Project — US states daily (archived)](https://huggingface.co/datasets/EPI-Eval/covid-tracking-project) | sars-cov-2 | US | daily |
+| [COVID-19 Forecast Hub — hospital admissions target](https://huggingface.co/datasets/EPI-Eval/covid19-forecast-hub) | sars-cov-2 | US | weekly |
+| [ECDC ERVISS — ILI/ARI primary-care consultation rates](https://huggingface.co/datasets/EPI-Eval/ecdc-erviss) | influenza, sars-cov-2, rsv | multiple (30 countries) | weekly |
+| [Flu MetroCast Hub — sub-state flu hosp forecast target](https://huggingface.co/datasets/EPI-Eval/flu-metrocast-hub) | influenza | US | weekly |
+| [FluSight Forecast Hub — flu hospital admission target](https://huggingface.co/datasets/EPI-Eval/flusight-forecast-hub) | influenza | US | weekly |
+| [JHU CSSE COVID-19 — global daily (archived)](https://huggingface.co/datasets/EPI-Eval/jhu-csse-covid) | sars-cov-2 | multiple | daily |
+| [NYT COVID-19 — US county daily](https://huggingface.co/datasets/EPI-Eval/nyt-covid) | sars-cov-2 | US | daily |
+| [OWID COVID-19 — global daily compiled](https://huggingface.co/datasets/EPI-Eval/owid-covid) | sars-cov-2 | multiple | daily |
+| [PHAC Respiratory Virus Detection Surveillance — Canada weekly](https://huggingface.co/datasets/EPI-Eval/canada-fluwatch) | influenza, influenza-a, influenza-b +7 | CA | weekly |
+| [RSV Forecast Hub — RSV hospital admissions target](https://huggingface.co/datasets/EPI-Eval/rsv-forecast-hub) | rsv | US | weekly |
+| [UKHSA Dashboard — England COVID-19 daily metrics](https://huggingface.co/datasets/EPI-Eval/ukhsa-covid-daily) | sars-cov-2 | GB | daily |
+| [UKHSA Dashboard — England flu / COVID-19 / RSV weekly](https://huggingface.co/datasets/EPI-Eval/ukhsa-respiratory) | influenza, sars-cov-2, rsv | GB | weekly |
+
+### Syndromic / ED
+
+| Dataset | Pathogens | Geography | Cadence |
+| --- | --- | --- | --- |
+| [CDC NSSP / ESSENCE — ED visits for ILI / COVID / RSV](https://huggingface.co/datasets/EPI-Eval/cdc-nssp) | influenza, sars-cov-2, rsv | US | weekly |
+
+### Arboviral
+
+| Dataset | Pathogens | Geography | Cadence |
+| --- | --- | --- | --- |
+| [OpenDengue — national dengue case counts (V1.3)](https://huggingface.co/datasets/EPI-Eval/opendengue) | dengue | multiple | irregular |
+
+### Mobility & contact
+
+| Dataset | Pathogens | Geography | Cadence |
+| --- | --- | --- | --- |
+| [Google Community Mobility Reports — global daily](https://huggingface.co/datasets/EPI-Eval/global-mobility) | — | multiple | daily |
+
+### Search & behavioural
+
+| Dataset | Pathogens | Geography | Cadence |
+| --- | --- | --- | --- |
+| [Wikipedia pageviews — disease-article daily views](https://huggingface.co/datasets/EPI-Eval/wikipedia-pageviews) | influenza, sars-cov-2, rsv +6 | multiple | daily |
+
+### Notifiable / other
+
+| Dataset | Pathogens | Geography | Cadence |
+| --- | --- | --- | --- |
+| [OWID Mpox — global daily compiled](https://huggingface.co/datasets/EPI-Eval/owid-mpox) | mpox | multiple | daily |
+| [WHO Global TB — annual country estimates](https://huggingface.co/datasets/EPI-Eval/who-tb-burden) | tuberculosis | multiple | annual |
+
+## Predictions
+
+Each truth dataset has a companion `EPI-Eval/<id>-predictions` repo that
+accumulates community-submitted forecasts. Schema is long-format: one row per
+`(target_date, [dim values…], quantile, value)`, with `quantile = NULL`
+reserved for the point estimate. Forecasters submit through the
+[EPI-Eval dashboard](https://github.com/ChrisHarig/apart-forecasting-tool);
+a maintainer reviews each PR before merging, and merged predictions show up
+on the corresponding truth dataset's *Show predictions* toggle in the
+dashboard, with a per-submitter leaderboard (MAE / WIS / rWIS / coverage).
+
+## Status
+
+Active. Coverage and dataset list grow through PRs to the upload pipeline.
+