CC BY-NC-ND 4.0 · Yearb Med Inform 2020; 29(01): 231-234
DOI: 10.1055/s-0040-1702020
Section 11: Public Health and Epidemiology Informatics
Synopsis
Georg Thieme Verlag KG Stuttgart

Public Health and Epidemiology Informatics: Recent Research Trends Moving toward Public Health Data Science

Sébastien Cossin
1  Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
2  Centre Hospitalier Universitaire de Bordeaux, Service d’Information Médicale, Bordeaux, France
,
Rodolphe Thiébaut
1  Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
2  Centre Hospitalier Universitaire de Bordeaux, Service d’Information Médicale, Bordeaux, France
3  Inria, SISTM, Talence, France
,
Section Editors for the IMIA Yearbook Section on Public Health and Epidemiology Informatics› Author Affiliations
Further Information

Publication History

Publication Date:
21 August 2020 (online)

Summary

Objectives: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.

Methods: PubMed searches of 2019 literature concerning public health and epidemiology informatics were conducted and the returned references were reviewed by the two section editors to select 14 candidate best papers. These papers were then peer-reviewed by external reviewers to allow the Editorial Committee a curated selection of the best papers.

Results: Among the 835 references retrieved from PubMed, two were finally selected as best papers. The first best paper leverages satellite images and deep learning to identify remote rural communities in low-income countries; the second paper describes the development of a worldwide human disease surveillance system based on near real-time news data from the GDELT project. Internet data and electronic health records are still widely used to detect and monitor disease activity. Identifying and targeting specific audiences for public health interventions is a growing subject of interest.

Conclusions: The ever-increasing amount of data available offers endless opportunities to develop methods and tools that could assist public health surveillance and intervention belonging to the growing field of public health Data Science. The transition from proofs of concept to real world applications and adoption by health authorities remains a difficult leap to make.