Training Course on Coding Historical Causes of Death

The recently launched ICD10h coding system is designed to support historical demographers and historians in coding historical causes of death. Widespread adoption of this system across diverse countries and linguistic contexts will significantly enhance the comparability of research on historical cause-specific mortality patterns, while preserving the integrity of the historical context.

With the coding manual and the English historical causes of death strings file, researchers can begin coding causes of death. However, this process also involves tidying, parsing, and determining primary causes of death. This training course will guide participants through each of these essential steps.

Over the course of 2 days, participants will explore best practices for tidying cause-of-death data, including identifying the key elements of written strings that are crucial for coding and determining which aspects should be flagged within datasets. We will also focus on effective parsing strategies, addressing how to parse natural causes of death and distinguishing the parsing and coding of violent causes. Additionally, time will be dedicated to the actual coding process—how to select the appropriate code and achieve this efficiently.

We invite researchers at all stages of their academic careers to apply, with a special emphasis on PhD candidates working with historical causes of death. Applicants should possess a basic understanding of historical causes of death and bring their own dataset of causes to work on during the course.

A maximum of 20 participants will be selected, of whom around ten will be eligible for reimbursement of their travel expenses, based on the COST-Action regulations.

To apply, please apply using this form, providing following information:

• Your name and affiliation
• Career stage
• A brief summary of your research and dataset
• A short motivation for attending the course
• Whether you want to apply for reimbursement

We look forward to receiving your applications

Applications should be submitted before 1^st April 2025. Successful applicants will be informed by email on, or before 25^th April 2025.