Pontais Isabelle

In Saint-Martin (31 949 inhabitants) and Saint-Barthelemy (9 625 inhabitants) islands in the French West Indies, the surveillance system is based on several data sources: (1) a syndromic surveillance system based on two emergency departments (ED) of Saint-Barthellemy (HL de Bruyn) and Saint-Martin (CH Fleming) and on mortality (SurSaUD® network [1])); (2) a network of sentinel general practitioners (GP'™s) based on the voluntary participation of 10 GPs in Saint-Martin and 5 in Saint-Barthelemy; (3) the notifiable diseases surveillance system (31 notifiable diseases to individual case-specific form); (4) the regional surveillance systems of leptospirosis and arboviruses based on the biological cases reported by physicians and laboratories of two islands. On September 6, 2017, Hurricane Irma struck Saint-Martin and Saint-Barthelemy islands. Both islands were massively destroyed. This storm led to major material damages, such as power outages, disturbance of drinking water systems, road closures, destruction of medical structures and evacuation or relocation of residents. In this context, the usual monitoring system did not work and life conditions were difficult. The regional unit of French National Public Health Agency set up an epidemiological surveillance by sending epidemiologists in the field in order to collect data directly from ED physicians, GP's and in dispensaries. Those data allowed to describe short-term health effects and to detect potential disease outbreaks in the aftermath of Hurricane Irma. This paper presents results of the specific syndromic surveillance.

Objective: Describe short-term health effects of the Hurricane using the syndromic surveillance system based on emergency departments, general practitioners and dispensaries in Saint-Martin and Saint-Barthelemy islands from September 11, 2017 to October 29, 2017.

As part of the French syndromic surveillance system SurSaUDî, the French Public Health Agency (Sant© publique France) collects daily data from the emergency department (ED) network OSCOUR®. The system aims to timely identify, follow and assess the health impact of unusual or seasonal events on emergency medical activity. Individual ED data contain demographic (age, gender, residence zip code), administrative (dates of attendances and discharge, ED, etc.) and medical information (chief complaint, main and associated medical diagnoses, severity). Medical diagnoses are encoded using the ICD10 classification. Then syndromic groups are built based on these ICD10 codes for ensuring syndromic surveillance in routine. Even if ICD10 is recommended on the national guidelines for coding ED attendances, this thesaurus offers a too large variety of codes. Particularly, it includes lots of diseases that may never be observed or confirmed in ED. This variety let selection of the appropriate codes difficult for physicians in a reactive use and could discourage them to code diagnoses. In order to encourage appropriate and reactive coding practice, we decided in 2017 to produce a new diagnoses thesaurus with a limited list of ICD10 codes. Then a committee of medical and epidemiological experts was created by the Federation of regional emergency observatories (FedORU), to propose an operational thesaurus that includes relevant codes for both ED in a daily routine practice and syndromic surveillance.

Objective: The study aims to evaluate the potential impact of the revision of the thesaurus used by ED physicians to code medical diagnoses, on the syndromic indicators used daily to achieve the detection objective of the French syndromic surveillance system.

Since 2004, the French syndromic surveillance system SurSaUD® coordinated by the French Public Health Agency (Sante publique France) daily collects morbidity data from two data sources: the emergency departments (ED) network Oscour® and the emergency general practitioners associations SOS Medecins. Almost 92% of the French ED attendances are recorded by the system. SOS Medecins network is a group of 62 associations of general practitioners, dispatched all over the territory. Sante publique France received data from 61 out of 62 associations. Both data sources collect medical diagnosis, using ICD10 codes in the ED network and specific medical thesaurus in SOS Medecins associations. These data are routinely analyzed to detect and follow-up various expected or unusual public health events all over the territory. The system is also used for reassurance of decision makers. In that framework, in March 2017, the French Ministry of Health requested Sante publique France to validate a potential scarlet fever outbreak in France.

Objective:

Describe a case study of validation of a scarlet fever outbreak using syndromic surveillance data sources.

The syndromic surveillance SurSaUD® system developed by Sante© publique France, the French National Public Health Agency collects daily data from 4 data sources: emergency departments (OSCOUR® ED network), emergency general practioners (SOS Medecins network), crude mortality (civil status data) and electronic death certification including causes of death. The system aims to timely identify, follow and assess the health impact of unusual or seasonal events on emergency medical activity and mortality. However some information could be missed by the system especially for non-severe (absence of ED consultation) or, in contrast, highly severe purposes (direct access to intensive care units). The French pre-hospital emergency medical service (SAMU) represents a potential valuable data source to complete the SurSaUD® surveillance system, thanks to reactive pre-hospital data collection and a large geographical coverage on the whole territory. Data are still not completely standardized and computerized but a governmental project to develop a national common IT system involving all French SAMU is in progress and will be experimented in the following years.

Objective:

To evaluate whether SAMU data could be relevant for health surveillance and proposed to be integrated into the French national syndromic surveillance SurSaUD® system.