Public Health and Epidemiology Informatics: Recent Research Trends Moving toward Public Health Data Science
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...
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Published in | Yearbook of medical informatics Vol. 29; no. 1; pp. 231 - 234 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Stuttgart
Georg Thieme Verlag KG
01.08.2020
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Subjects | |
Online Access | Get full text |
ISSN | 0943-4747 2364-0502 |
DOI | 10.1055/s-0040-1702020 |
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Abstract | 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. |
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AbstractList | 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. 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. To introduce and summarize current research in the field of Public Health and Epidemiology Informatics. 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. 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. 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. 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. |
Author | Thiébaut, Rodolphe Cossin, Sébastien |
AuthorAffiliation | 2 Centre Hospitalier Universitaire de Bordeaux, Service d’Information Médicale, Bordeaux, France 1 Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France 3 Inria, SISTM, Talence, France |
AuthorAffiliation_xml | – name: 1 Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France – name: 2 Centre Hospitalier Universitaire de Bordeaux, Service d’Information Médicale, Bordeaux, France – name: 3 Inria, SISTM, Talence, France |
Author_xml | – sequence: 1 givenname: Sébastien surname: Cossin fullname: Cossin, Sébastien email: sebastien.cossin@u-bordeaux.fr organization: Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center – sequence: 2 givenname: Rodolphe surname: Thiébaut fullname: Thiébaut, Rodolphe organization: Inria, SISTM, Talence, France |
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Cites_doi | 10.2196/13142 10.2196/13329 10.1177/1090198119871246 10.1371/journal.pcbi.1007165 10.1007/s00592-019-01350-5 10.3414/ME14-01-0031 10.1126/scitranslmed.aaa3487 10.1093/jamia/ocz112 10.1016/j.addbeh.2017.05.002 10.2196/12394 10.1093/jamia/ocz111 10.2196/12443 10.1017/ice.2018.343 10.1016/j.ophtha.2019.04.008 10.1016/j.jaip.2019.12.007 10.2105/AJPH.2017.304249 10.1017/ice.2019.288 |
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Keywords | epidemiology International Medical Informatics Association medical informatics data science surveillance ethics Public health |
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Objectives
: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.
Methods
: PubMed searches of 2019... Objectives: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics. Methods: PubMed searches of 2019 literature... To introduce and summarize current research in the field of Public Health and Epidemiology Informatics. PubMed searches of 2019 literature concerning public... Objectives : To introduce and summarize current research in the field of Public Health and Epidemiology Informatics. Methods : PubMed searches of 2019... |
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SubjectTerms | Databases, Factual Epidemiology Health Services Accessibility Humans Informatics Natural Language Processing Public Health Section 11: Public Health and Epidemiology Informatics |
Title | Public Health and Epidemiology Informatics: Recent Research Trends Moving toward Public Health Data Science |
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