Some Innovative Approaches for Public Health and Epidemiology Informatics

Abstract

SummaryObjectives: Summarize excellent current research published in 2015 in the field of Public Health and Epidemiology Informatics. Methods: The complete 2015 literature concerning public health and epidemiology informatics has been searched in PubMed and Web of Science, 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 team an enlightened selection of the best papers. Results: Among the 1,272 references retrieved from PubMed and Web of Science, three were finally selected as best papers. The first one presents a language agnostic approach for epidemic event detection in news articles. The second paper describes a system using big health data gathered by a statewide system to forecast emergency department visits. The last paper proposes a rather original approach that uses machine learning to solve the old issue of outbreak detection and prediction. Conclusions: The increasing availability of data, now directly from health systems, will probably lead to a boom in public health surveillance systems and in large-scale epidemiologic studies.

Predicting over-the-counter antibiotic use in rural Pune, India, using machine learning methods

“…ML models have proven to be helpful in the medical and health sciences, particularly in the areas of diagnosis and outcome prediction (27). Previous research has suggested that the application of ML models in the healthcare industry, although still in the early stages, is primarily focused on the early diagnosis of chronic diseases, predicting future disease incidence, conducting epidemiological studies, and facilitating evidence-based decision-making (27)(28)(29)(30)(31)(32). There is also evidence supporting the use of AI and ML models to predict AMR among bacterial species based on whole genome sequencing (12,13,(34)(35)(36)(37)(38).…”

Identifying strategies to overcome roadblocks to utilising near real-time healthcare and administrative data to create a Scotland-wide learning health system

“…An ‘other’ category had existed at that stage, which primarily referred to innovations, exemplars, government directives, etc. A combination of deductive thematic analysis, informed by the literature on harnessing information systems to improve patient care, 65–74 LHS, 4,6,9,10 data privacy legislation, 75–77 and public policy, 78,79 and a more inductive iterative approach that allowed new themes to emerge from the data were used. 80 In the fifth stage, we applied this analytical framework to code further transcripts.…”

The estimated impact of the COVID-19 epidemic in the general population of France

“…We applied the analytical methods used by epidemiological reference observatories in France for the general population, such as the French Syndromic Sentinel Network 10,22 or the Research Institute for the exploitation of health data (IRSAN) 23 . IRSAN has in particular utilised data from the records of the physicians of SOS Médecins since 2012.…”