---
language:
  - en
  - th
license: cc-by-4.0
tags:
  - thailand
  - bangkok
  - road-safety
  - traffic-injuries
  - injury-surveillance
  - public-health
  - tabular-data
  - csv
dataset_type: tabular
pretty_name: Thailand Road-Traffic Injury Aggregates (2018)
---

# Thailand Road-Traffic Injury Aggregates (2018)

**Canonical dataset page (EN/TH):** https://bangkokfamilylawyer.com/datasets-injury-th/  
**DOI (this version):** https://doi.org/10.5281/zenodo.17538573  
**Concept DOI (latest):** https://doi.org/10.5281/zenodo.17538574  

**Author:** Jean Maurice Cecilia Menzel  
**Publisher:** AppDevBangkok / UdonLaw  
**License:** CC BY 4.0

This repository provides aggregated indicators derived from Thailand’s official Injury Surveillance
data (Department of Disease Control, Ministry of Public Health) for **calendar year 2018**.

All outputs are privacy-preserving aggregates; individual-level records are **not** included.

## Contents

Key CSV files (2018 slice):

- `province_2018.csv` — Cases by province.
- `bkk_quarter_2018.csv` — Bangkok cases by quarter.
- `age_bins_2018.csv` — Cases by age group.
- `sex_2018.csv` — Cases by sex.
- `mode_mix_bkk_2018.csv` — Mode / road-user mix for Bangkok.
- `top10_provinces_2018.csv` — Top 10 provinces by case count.
- `bkk_top_amphoe_2018.csv` — Leading Bangkok districts.
- `qa_year_counts_2018.csv` — Year-level row counts (QA).
- `qa_coverage_province_2018.csv` — Coverage / completeness indicators.
- `qa_summary.json` — Human-readable QA summary.

File names may be extended as new QA tables or visualizations are added.

## Source Data

Source dataset (not redistributed here):

- **Injury Surveillance – DDC**  
  Injury Prevention Division, Department of Disease Control, Ministry of Public Health, Thailand.  
  Catalog: https://data.go.th/en/dataset/injury-surveillance

The original dataset remains under its own terms and conditions.
This repository only provides derived aggregates.

## Methodology (summary)

- Filtered to events in **2018**.
- Robust date parsing with support for Thai formats and Buddhist Era → Gregorian conversion.
- Records with invalid or missing core fields are excluded from aggregates.
- Aggregations computed by:
  - Province and (for Bangkok) district
  - Quarter (Q1–Q4)
  - Age groups
  - Sex
  - Selected mode / road-user categories
- Small cells may be combined or omitted to reduce re-identification risk.

For full details, see the canonical documentation at:

> https://bangkokfamilylawyer.com/datasets-injury-th/

## How to use

Example (Python):

```python
import pandas as pd
from datasets import load_dataset

ds = load_dataset(
    "appdevbangkok/thailand-road-traffic-injury-aggregates-2018",
    split="train"
)
# or load specific CSVs directly via raw URLs if preferred