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Assessing the Digital Advancement of Public Health Systems Using Indicators Published in Gray Literature: Narrative Review

Assessing the Digital Advancement of Public Health Systems Using Indicators Published in Gray Literature: Narrative Review

For each given indicator, provided by included references, we extracted the following information in an Excel file: (1) the reference title and link, (2) the name of the providing organization or authors, (3) the description and definition of the indicator, and (4) the data source of the indicator. Due to the large number of included references, all indicators were extracted by only one author each.

Laura Maaß, Manuel Badino, Ihoghosa Iyamu, Felix Holl

JMIR Public Health Surveill 2024;10:e63031

Fine Detection of Human Motion During Activities of Daily Living as a Clinical Indicator for the Detection and Early Treatment of Chronic Diseases: The E-Mob Project

Fine Detection of Human Motion During Activities of Daily Living as a Clinical Indicator for the Detection and Early Treatment of Chronic Diseases: The E-Mob Project

These metrics could provide a reliable and useful clinical diagnostic and predictive indicator (as an early sign) of the stage and evolution of chronic diseases and related comorbidities and complications. In the longer term, advancement in this direction could potentially influence treatment strategies (posology, timing/chronobiology, and nature of the treatment).

David Thivel, Alice Corteval, Jean-Marie Favreau, Emmanuel Bergeret, Ludovic Samalin, Frédéric Costes, Farouk Toumani, Christian Dualé, Bruno Pereira, Alain Eschalier, Nicole Fearnbach, Martine Duclos, Anne Tournadre

J Med Internet Res 2022;24(1):e32362

Identifying Communities at Risk for COVID-19–Related Burden Across 500 US Cities and Within New York City: Unsupervised Learning of the Coprevalence of Health Indicators

Identifying Communities at Risk for COVID-19–Related Burden Across 500 US Cities and Within New York City: Unsupervised Learning of the Coprevalence of Health Indicators

The project 500 Cities contains disease and health indicator prevalence for 27,648 individual census tracts of the 500 largest cities in the United States, and these prevalences are estimated from the Behavioral Risk Factor Surveillance System [30].

Andrew Deonarine, Genevieve Lyons, Chirag Lakhani, Walter De Brouwer

JMIR Public Health Surveill 2021;7(8):e26604