Related Experiment Video
Updated: Feb 17, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Syndromic surveillance based on emergency department activity and crude mortality: two examples
L Josseran1, Javier Nicolau1, N Caillère1
1Institut de Veille Sanitaire, Saint-Maurice, France.
Abstract:
Recent public health crises have shown the need for readily available information allowing proper management by decision-makers. One way of obtaining early information is to involve data providers who already record routine data for their own use. We describe here the results of a pilot network carried out by the InVS (Institut national de veille sanitaire) which gathered data available in real time from hospital emergency departments and register offices. Emergency departments data were registered from patients' computerised medical files. Mortality data were received from the national institute of statistics (Insee). Data were transmitted automatically on a daily basis. Influenza data from outbreaks in 2004/05 and 2005/06 were compared with data from the sentinel network for the same periods. Environmental health data were compared with meteorological temperatures recorded in Paris between June and August 2006. A mortality analysis was conducted on a weekly basis. Correlation between influenza data from emergency departments and data from Sentiweb (sentinel network) was significant (p<0.001) for both outbreaks. In 2005 and 2006, the outbreaks were described similarly by both sources with identification of the start of the outbreaks by both systems during the same weeks. As for data related to heat, a significant correlation was observed between some diagnoses and temperature increases. For both types of phenomena, mortality increased significantly with one to two weeks lag. To our knowledge, this is the first time that a study using real time morbidity and mortality data is conducted. These initial results show how these data complement each other and how their simultaneous analysis in real time makes it possible to quickly measure the impact of a phenomenon.
More Related Videos
09:08Developing a Salivary Antibody Multiplex Immunoassay to Measure Human Exposure to Environmental Pathogens
Published on: September 12, 2016
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Related Concept Videos
Principles of Disease Surveillance
Steps in Outbreak Investigation
Introduction to Epidemiology
Statistical Methods for Analyzing Epidemiological Data
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Causality in Epidemiology