Public Health and Epidemiology Informatics

Summary

Objective: To identify notable research contributions relevant to public health and epidemiology informatics (PHEI) documented in peer-reviewed articles published in 2024.

Methods: A broad search of high-quality biomedical informatics and public health journals was conducted to identify peer-reviewed articles published in 2024 that represent significant contributions to the PHEI discipline and broader field of biomedical and health informatics. The selection process comprised three steps: 1) candidate best papers were first selected by the two section editors; 2) a diverse, international group of external informatics subject matter experts reviewed each candidate best paper; and 3) the final selection of four best papers plus one honorable mention paper was conducted by the editorial committee of the Yearbook. The section editors attempted to balance selection by authors' global region and areas within the PHEI discipline.

Results: Selected best papers represent studies that advanced knowledge surrounding the intersection of public health, epidemiology, and informatics methods and applications. In general, papers identified in the search fell into one of the following categories: 1) data management for public health; 2) disease surveillance methods; and 3) infrastructure to support 1 and 2. The best papers spanned several disease targets, including diabetes, influenza-like illnesses, hepatitis C, and COVID. These papers also addressed specialized informatics methods, such as artificial intelligence and machine learning, as well as approaches to data analysis and federated electronic health record systems for public health surveillance.

Conclusion: Although the selected papers are notable, there is still much to be done in the domain of informatics that serves epidemiology and public health. This is especially true in epidemiologic surveillance, in which public health authorities seek to rapidly identify and respond to emerging infectious diseases, and the monitoring of chronic, non-communicable diseases such as those identified in the best papers.