CC BY-NC-ND 4.0 · Yearb Med Inform 2021; 30(01): 280-282
DOI: 10.1055/s-0041-1726530
Section 11: Public Health and Epidemiology Informatics
Synopsis

Public Health and Epidemiology Informatics: Recent Research Trends

Gayo Diallo
1   INRIA SISTM, Team ERIAS - INSERM Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France
,
Georgeta Bordea
1   INRIA SISTM, Team ERIAS - INSERM Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France
2   Team ERIAS - INSERM BPH Research Center & LaBRI UMR 5800, Univ. Bordeaux, Bordeaux, France
,
Section Editors for the IMIA Yearbook Section on Public Health and Epidemiology Informatics › Author Affiliations

Summary

Objectives: To introduce and analyse current trends in Public Health and Epidemiology Informatics.

Methods: PubMed search of 2020 literature on public health and epidemiology informatics was conducted and all retrieved references were reviewed by the two section editors. Then, 15 candidate best papers were selected among the 920 references. These papers were then peer-reviewed by the two section editors, two chief editors, and external reviewers, including at least two senior faculty, to allow the Editorial Committee of the 2021 International Medical Informatics Association (IMIA) Yearbook to make an informed decision regarding the selection of the best papers.

Results: Among the 920 references retrieved from PubMed, four were suggested as best papers and the first three were finally selected. The fourth paper was excluded because of reproducibility issues. The first best paper is a very public health focused paper with health informatics and biostatistics methods applied to stratify patients within a cohort in order to identify those at risk of suicide; the second paper describes the use of a randomized design to test the likely impact of fear-based messages, with and without empowering self-management elements, on patient consultations or antibiotic requests for influenza-like illnesses. The third selected paper evaluates the perception among communities of routine use of Whole Genome Sequencing and Big Data technologies to capture more detailed and specific personal information.

Conclusions: The findings from the three studies suggest that using Public Health and Epidemiology Informatics methods could leverage, when combined with Deep Learning, early interventions and appropriate treatments to mitigate suicide risk. Further, they also demonstrate that well informing and empowering patients could help them to be involved more in their care process.



Publication History

Article published online:
03 September 2021

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