---
layout: default
title: Covid Positive
parent: Curated Assets
nav_order: 3
permalink: /docs/curated_assets/covid_positive
---

# Covid Positive

<a href="https://github.com/BHFDSC/hds_curated_assets/blob/main/curate_covid_positive.py" class="btn btn-primary fs-5 mb-4 mb-md-0 mr-2" target="_blank">View code on GitHub</a>

The ***covid_positive*** table is a consolidated table for positive COVID-19 case records derived from antigen testing, primary and secondary care data (including SGSS, Pillar 2 antigen testing, GDPPR, HES APC (diagnosis) and CHESS). Positive COVID-19 records are extracted from each dataset and records with a distinct person ID and non-null dates are retained. The tables from each extraction are then combined to create a unified dataset of all COVID-19 positive records. 

The output table includes six columns: 

- **person_id**
- **date**
- **code**
- **description**
- **covid_status** (confirmed/suspected)
- **data_source** 

{: .note }
The methodology for curating the table is further outlined <a href="https://www.thelancet.com/journals/landig/article/PIIS2589-7500(22)00091-7/fulltext" target="_blank">in this paper</a>.


The table is saved to the DSA schema **dsa_391419_j3w9t_collab**. The archived_on_date is in the format **YYYY_MM_DD**.

{: .highlight-title }
> Table Name
>
> >
> hds_curated_assets__covid_positive_archived_on_date

The below code will load the hes_apc_diagnosis table as at October 2024 using PySpark:

{% highlight markdown %}
```python
import pyspark.sql.functions as f
dsa = f'dsa_391419_j3w9t_collab'
covid_positive = spark.table(f'{dsa}.hds_curated_assets__covid_positive_2024_10_24')
```
{% endhighlight %}