bolster.data_sources.nisra.drug_related_deaths

NISRA Drug-Related and Drug Misuse Deaths Data Source.

Provides access to NISRA’s annual statistics on drug-related deaths and deaths due to drug misuse in Northern Ireland via the NISRA PxStat API. Two geographic breakdowns are available: HSC Trust and Local Government District.

NISRA distinguishes two related measures:

Drug-related deaths (DRDCOUNT): All deaths where a drug was implicated, including prescription medicines, controlled drugs, and accidental/intentional poisonings.
Drug misuse deaths (MISUSECOUNT): A narrower subset where the underlying cause is drug abuse/dependence or the death involved a controlled substance.

Original data source:

https://www.nisra.gov.uk/statistics/death-statistics/drug-related-and-drug-misuse-deaths

PxStat matrices used:

DTHSDRHSCT — annual deaths by HSC Trust (6 trusts + NI total)
DTHSDRLGD — annual deaths by LGD (11 districts + NI total)

Update Frequency: Annual (typically May) Geographic Coverage: Northern Ireland

Example

>>> from bolster.data_sources.nisra import drug_related_deaths as drd
>>> df = drd.get_latest_drug_related_deaths()
>>> {"year", "geography", "statistic", "value"}.issubset(df.columns)
True
>>> len(df) > 0
True

Attributes

`logger`
`DimensionType`

Functions

`get_latest_drug_related_deaths`([dimension, force_refresh])	Download and return the latest NISRA drug-related deaths data.
`validate_data`(df)	Validate a parsed drug-related deaths DataFrame.

Module Contents

bolster.data_sources.nisra.drug_related_deaths.logger[source]

bolster.data_sources.nisra.drug_related_deaths.DimensionType[source]

bolster.data_sources.nisra.drug_related_deaths.get_latest_drug_related_deaths(dimension='all', force_refresh=False)[source]

Download and return the latest NISRA drug-related deaths data.

Fetches data from the NISRA PxStat API. Both available geographic breakdowns are returned for dimension='all'.

Note

force_refresh is accepted for API compatibility but is ignored — the PxStat API is called directly with no local cache layer.

Parameters:

dimension (DimensionType) –
Geographic breakdown to return. One of:
- "hsct" — 5 HSC Trusts + NI total
- "lgd" — 11 Local Government Districts + NI total
- "all" — dict containing both breakdowns (default)
force_refresh (bool) – Ignored. Retained for API compatibility.

Returns:

DataFrame with columns:

year: Registration year (int)

geography_code: geography identifier code

geography: geography name label

statistic: "drug_related" or "drug_misuse"

value: Count of deaths (int, NaN where suppressed)

For "all": {"hsct": DataFrame, "lgd": DataFrame}

Return type:

For "hsct" or "lgd"

Raises:

ValueError – If dimension is not a supported value.

Example

>>> df = get_latest_drug_related_deaths("hsct")
>>> {"year", "geography", "statistic", "value"}.issubset(df.columns)
True
>>> data = get_latest_drug_related_deaths("all")
>>> sorted(data.keys())
['hsct', 'lgd']

bolster.data_sources.nisra.drug_related_deaths.validate_data(df)[source]

Validate a parsed drug-related deaths DataFrame.

Parameters:: df (pandas.DataFrame) – DataFrame from get_latest_drug_related_deaths() with a single geographic dimension.
Returns:: True if validation passes, False otherwise.
Return type:: bool

Example

>>> import pandas as pd
>>> validate_data(pd.DataFrame())
False