scholarly journals User-friendly Rshiny web applications for supporting syndromic surveillance analysis

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Anne Fouillet ◽  
Marc Ruello ◽  
Lucie Leon ◽  
Cecile Sommen ◽  
Laurent Marie ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Web Applications ◽  
Age Groups ◽  
Data Sources ◽  
Mortality Data ◽  
Syndromic Surveillance System ◽  
R Shiny ◽  
User Friendly

ObjectiveThe presentation describes the design and the main functionalitiesof two user-friendly applications developed using R-shiny to supportthe statistical analysis of morbidity and mortality data from the Frenchsyndromic surveillance system SurSaUD.IntroductionThe French syndromic surveillance system SursaUD® has beenset up by Santé publique France, the national public health agency(formerly French institute for public health - InVS) in 2004. In 2016,the system is based on three main data sources: the attendancesin about 650 emergency departments (ED), the consultations to62 emergency general practitioners’ (GPs) associations SOSMédecins and the mortality data from 3,000 civil status offices [1].Daily, about 60,000 attendances in ED (88% of the nationalattendances), 8,000 visits in SOS Médecins associations (95% ofthe national visits) and 1,200 deaths (80% of the national mortality)are recorded all over the territory and transmitted to Santé publiqueFrance.About 100 syndromic groupings of interest are constructed fromthe reported diagnostic codes, and monitored daily or weekly, fordifferent age groups and geographical scales, to characterize trends,detect expected or unexpected events (outbreaks) and assess potentialimpact of both environmental and infectious events. All-causesmortality is also monitored in similar objectives.Two user-friendly interactive web applications have beendeveloped using the R shiny package [2] to provide a homogeneousframework for all the epidemiologists involved in the syndromicsurveillance at the national and the regional levels.MethodsThe first application, named MASS-SurSaUD, is dedicated to theanalysis of the two morbidity data sources in Sursaud, along with dataprovided by a network of Sentinel GPs [3]. Based on pre-aggregateddata availaible daily at 10:30 am, R programs create daily, weeklyand monthly time series of the proportion of each syndromic groupingamong all visits/attendances with a valid code at the national andregional levels. Twelve syndromic groupings (mainly infectious andrespiratory groups, like ILI, gastroenteritis, bronchiolitis, pulmonarydiseases) and 13 age groups have been chosen for this application.For ILI, 3 statistical methods (periodic regression, robust periodicregression and Hidden Markov model) have been implementedto identify outbreaks. The results of the 3 methods applied to the3 data sources are combined with a voting algorithm to compilethe influenza alarm level for each region each week: non-epidemic,pre/post epidemic or epidemic.The second application, named MASS-Euromomo, allowsconsulting results provided by the model developed by the Europeanproject EuroMomo for the common analysis of mortality in theEuropean countries (www.euromomo.eu). The Euromomo model,initially developed using Stata software, has been transcripted inR. The model has been adapted to run in France both at a national,regional and other geographical administrative levels, and for 7 agegroups.ResultsThe two applications, accessible on a web-portal, are similarlydesigned, with:- a dropdown menu and radio buttons on the left hand side to selectthe data to display (e.g. filter by data source, age group, geographicallevels, syndromic grouping and/or time period),- several tab panels allowing to consult data and statistical resultsthrough tables, static and dynamic charts, statistical alarm matrix,geographical maps,... (Figure 1),- a “help” tab panel, including documentations and guidelines,links, contact details.The MASS-SurSaUD application has been deployed in December2015 and used during the 2015-2016 influenza season. MASS-Euromomo application has been deployed in July 2016 for the heat-wave surveillance period. Positive feedbacks from several users havebeen reported.ConclusionsBusiness Intelligence tools are generally focused on datavisualisation and are not generally tailored for providing advancedstatistical analysis. Web applications built with the R-shiny packagecombining user-friendly visualisations and advanced statistics can berapidly built to support timely epidemiological analyses and outbreakdetection.Figure 1: screen-shots of a page of the two applications

scholarly journals Outbreak of ED visits related to the use of synthetic cannabinoids, Mayotte Island

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Pascal Vilain ◽  
Salamta Bah-Assoumani ◽  
Ali-Mohamed Youssouf ◽  
Laurent Filleul
Keyword(s):  
Public Health ◽  
Behavioral Disorders ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Adverse Reactions ◽  
Health Agency ◽  
Case Definition ◽  
Syndromic Surveillance System ◽  
Ed Visits ◽  
Mental And Behavioral Disorders

ObjectiveTo confirm and to characterize the increase in emergency department (ED) visits related to the use of synthetic cannabinoids (SC)IntroductionOn October 2016, the Indian Ocean Regional Health Agency was alerted about an increase in ED visits related to adverse reactions associated with use of SC on Mayotte Island. In this context, an investigation based on a syndromic surveillance system was implemented by the regional unit of the French national public health agency.MethodsAn extraction of anonymized records routinely collected by the syndromic surveillance system (1) was carried out from January 1st, 2012 to October 30, 2016. ED visits related to the consumption of SC were identified from ICD-10 codes of the principal diagnostic according to two levels of confidence:- a probable case was defined as ED visit coded X69 (Intentional self-poisoning by and exposure to other and unspecified chemicals and noxious substances). This code has been implemented specifically by ED physicians since august 2015;- a suspect case was defined as ED visit coded: F11 (Mental and behavioral disorders due to use of opioids), F12 (Mental and behavioral disorders due to use of cannabinoids), F16 (Mental and behavioral disorders due to use of hallucinogens), F18 (Mental and behavioral disorders due to use of volatile solvents), F19 (Mental and behavioral disorders due to multiple drug use and use of other psychoactive substances).Based on these data, an epidemic curve and a descriptive analysis of ED visits were carried out.ResultsIn total, 146 ED visits related to adverse events associated with use of SC were registered from January 1st, 2012 to October 30, 2016. The epidemic curve shows two waves between 2015 and 2016 with a particularly high peak in August 2015 (Figure 1). In total, 49% (n=72/146) of these ED visits were probably related to adverse reactions associated to use SC and 51% (n=74/146) meet to the suspect case definition. On the surveillance period, men represented 84% of the patients (n=122) and median age (min – max) was 23 (8-62) years old. When the severity score variable was filled (n = 138), a vital emergency was reported for 4% (n = 5) of patients and 19% of patients were hospitalized.ConclusionsData from syndromic surveillance system allowed to confirm an increase in ED visits related to adverse reactions associated with use of SC in Mayotte Island. To our knowledge, it’s the first time that an outbreak related to use SC is described in the Ocean Indian areaThis phenomenon was particularly marked in 2015 with a peak of ED visits on August 2016.After this outbreak, the regional unit of the French national public health agency recommended the pursuit of the coding X69 in principal diagnosis with the following case definition: any patient with an adverse reaction attributed to synthetic cannabinoid use whether suspected by the medical team or declared by the patient himself or if the patient is in possession of the substance; and to raise awareness ED physicians to the notification of these poisonings to the Regional Addictive Surveillance Center.In conclusion, the young population, weakened by a precarious socio-economic situation, is a target for new synthetic drugs and a threat to public health. This emerging risk in Mayotte must be taken into account and must be actively monitored. In this context, collaborative work with the emergency services must continue in parallel with targeted prevention measures.References1. Vilain P, Maillard O, Raslan-Loubatie J, Abdou MA, Lernout T, Filleul L. Usefulness of Syndromic Surveillance for Early Outbreak Detection in Small Islands: The Case of Mayotte. Online Journal of Public Health Informatics. 2013;5(1):e149.

scholarly journals Characterizing the Effects of Extreme Cold Using Real-time Syndromic Surveillance, Ontario, Canada, 2010-2016

2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 48S-52S ◽  
Author(s):  
Nancy VanStone ◽  
Adam van Dijk ◽  
Timothy Chisamore ◽  
Brian Mosley ◽  
Geoffrey Hall ◽  
...  
Keyword(s):  
Public Health ◽  
Acute Care ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Cold Temperature ◽  
Syndromic Surveillance System ◽  
Southern Ontario ◽  
Threshold Temperatures ◽  
Ed Visits ◽  
Extreme Cold

Morbidity and mortality from exposure to extreme cold highlight the need for meaningful temperature thresholds to activate public health alerts. We analyzed emergency department (ED) records for cold temperature–related visits collected by the Acute Care Enhanced Surveillance system—a syndromic surveillance system that captures data on ED visits from hospitals in Ontario—for geographic trends related to ambient winter temperature. We used 3 Early Aberration Reporting System algorithms of increasing sensitivity—C1, C2, and C3—to determine the temperature at which anomalous counts of cold temperature–related ED visits occurred in northern and southern Ontario from 2010 to 2016. The C2 algorithm was the most sensitive detection method. Results showed lower threshold temperatures for Acute Care Enhanced Surveillance alerts in northern Ontario than in southern Ontario. Public health alerts for cold temperature warnings that are based on cold temperature–related ED visit counts and ambient temperature may improve the accuracy of public warnings about cold temperature risks.

scholarly journals Precision public health through clinic-based syndromic surveillance in communities

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Ta-Chien Chan ◽  
Yung-Chu Teng ◽  
Yen-Hua Chu ◽  
Tzu-Yu Lin
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Syndromic Surveillance ◽  
Early Stage ◽  
Age Distribution ◽  
Local Health ◽  
Syndromic Surveillance System ◽  
Taipei City ◽  
Kaohsiung City

ObjectiveSentinel physician surveillance in the communities has played an important role in detecting early aberrations in epidemics. The traditional approach is to ask primary care physicians to actively report some diseases such as influenza-like illness (ILI), and hand, foot, and mouth disease (HFMD) to health authorities on a weekly basis. However, this is labor-intensive and time-consuming work. In this study, we try to set up an automatic sentinel surveillance system to detect 23 syndromic groups in the communites.IntroductionIn December 2009, Taiwan’s CDC stopped its sentinel physician surveillance system. Currently, infectious disease surveillance systems in Taiwan rely on not only the national notifiable disease surveillance system but also real-time outbreak and disease surveillance (RODS) from emergency rooms, and the outpatient and hospitalization surveillance system from National Health Insurance data. However, the timeliness of data exchange and the number of monitored syndromic groups are limited. The spatial resolution of monitoring units is also too coarse, at the city level. Those systems can capture the epidemic situation at the nationwide level, but have difficulty reflecting the real epidemic situation in communities in a timely manner. Based on past epidemic experience, daily and small area surveillance can detect early aberrations. In addition, emerging infectious diseases do not have typical symptoms at the early stage of an epidemic. Traditional disease-based reporting systems cannot capture this kind of signal. Therefore, we have set up a clinic-based surveillance system to monitor 23 kinds of syndromic groups. Through longitudinal surveillance and sensitive statistical models, the system can automatically remind medical practitioners of the epidemic situation of different syndromic groups, and will help them remain vigilant to susceptible patients. Local health departments can take action based on aberrations to prevent an epidemic from getting worse and to reduce the severity of the infected cases.MethodsWe collected data on 23 syndromic groups from participating clinics in Taipei City (in northern Taiwan) and Kaohsiung City (in southern Taiwan). The definitions of 21 of those syndromic groups with ICD-10 diagnoses were adopted from the International Society for Disease Surveillance (https://www.surveillancerepository.org/icd-10-cm-master-mapping-reference-table). The definitions of the other two syndromic groups, including dengue-like illness and enterovirus-like illness, were suggested by infectious disease and emergency medicine specialists.An enhanced sentinel surveillance system named “Sentinel plus” was designed for sentinel clinics and community hospitals. The system was designed with an interactive interface and statistical models for aberration detection. The data will be computed for different combinations of syndromic groups, age groups and gender groups. Every day, each participating clinic will automatically upload the data to the provider of the health information system (HIS) and then the data will be transferred to the research team.This study was approved by the committee of the Institutional Review Board (IRB) at Academia Sinica (AS-IRB02-106262, and AS-IRB02-107139). The databases we used were all stripped of identifying information and thus informed consent of participants was not required.ResultsThis system started to recruit the clinics in May 2018. As of August 2018, there are 89 clinics in Kaohsiung City and 33 clinics and seven community hospitals in Taipei City participating in Sentinel plus. The recruiting process is still ongoing. On average, the monitored volumes of outpatient visits in Kaohsiung City and Taipei City are 5,000 and 14,000 per day.Each clinic is provided one list informing them of the relative importance of syndromic groups, the age distribution of each syndromic group and a time-series chart of outpatient rates at their own clinic. In addition, they can also view the village-level risk map, with different alert colors. In this way, medical practitioners can know what’s going on, not only in their own clinics and communities but also in the surrounding communities.The Department of Health (Figure 1) can know the current increasing and decreasing trends of 23 syndromic groups by red and blue color, respectively. The spatial resolution has four levels including city, township, village and clinic. The map and bar chart represent the difference in outpatient rate between yesterday and the average for the past week. The line chart represents the daily outpatient rates for one selected syndromic group in the past seven days. The age distribution of each syndromic group and age-specific outpatient rates in different syndromic groups can be examined.ConclusionsSentinel plus is still at the early stage of development. The timeliness and the accuracy of the system will be evaluated by comparing with some syndromic groups in emergency rooms and the national notifiable disease surveillance system. The system is designed to assist with surveillance of not only infectious diseases but also some chronic diseases such as asthma. Integrating with external environmental data, Sentinel plus can alert public health workers to implement better intervention for the right population.References1. James W. Buehler AS, Marc Paladini, Paula Soper, Farzad Mostashari: Syndromic Surveillance Practice in the United States: Findings from a Survey of State, Territorial, and Selected Local Health Departments. Advances in Disease Surveillance 2008, 6(3).2. Ding Y, Fei Y, Xu B, Yang J, Yan W, Diwan VK, Sauerborn R, Dong H: Measuring costs of data collection at village clinics by village doctors for a syndromic surveillance system — a cross sectional survey from China. BMC Health Services Research 2015, 15:287.3. Kao JH, Chen CD, Tiger Li ZR, Chan TC, Tung TH, Chu YH, Cheng HY, Liu JW, Shih FY, Shu PY et al.: The Critical Role of Early Dengue Surveillance and Limitations of Clinical Reporting -- Implications for Non-Endemic Countries. PloS one 2016, 11(8):e0160230.4. Chan TC, Hu TH, Hwang JS: Daily forecast of dengue fever incidents for urban villages in a city. International Journal of Health Geographics 2015, 14:9.5. Chan TC, Teng YC, Hwang JS: Detection of influenza-like illness aberrations by directly monitoring Pearson residuals of fitted negative binomial regression models. BMC Public Health 2015, 15:168.6. Ma HT: Syndromic surveillance system for detecting enterovirus outbreaks evaluation and applications in public health. Taipei, Taiwan: National Taiwan University; 2007. 

scholarly journals Flexibility of ED surveillance system to monitor dengue outbreak in Reunion Island

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Pascal Vilain ◽  
Muriel Vincent ◽  
Anne Fouillet ◽  
Katia Mougin-Damour ◽  
Xavier Combes ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Reunion Island ◽  
Regional Office ◽  
Syndromic Surveillance System ◽  
Dengue Outbreak ◽  
Icd 10 ◽  
Réunion Island ◽  
Ed Visits

ObjectiveTo describe the characteristics of ED vitis related to dengue fever and to show how the syndromic surveillance system can be flexible for the monitoring of this outbreak.IntroductionIn Reunion Island, a French overseas territory located in the southwestern of Indian Ocean, the dengue virus circulation is sporadic. Since 2004, between 10 and 221 probable and confirmed autochthonous dengue fever cases have been reported annually. Since January 2018, the island has experienced a large epidemic of DENV serotype 2. As of 4 September 2018, 6,538 confirmed and probable autochthonous cases have been notified1. From the beginning of the epidemic, the regional office of National Public Health Agency (ANSP) in Indian Ocean enhanced the syndromic surveillance system in order to monitor the outbreak and to provide hospital morbidity data to public health authorities.MethodsIn Reunion Island, the syndromic surveillance system called OSCOUR® network (Organisation de la Surveillance Coordonnée des Urgences) is based on all emergency departments (ED)2. Anonymous data are collected daily directly from the patients’ computerized medical files completed during medical consultations. Every day, data files are sent to the ANSP via a regional server over the internet using a file transfer protocol. Each file transmitted to ANSP includes all patient visits to the ED logged during the previous 24 hours (midnight to midnight). Finally, data are integrated in a national database (including control of data quality regarding authorized thesauri) and are made available to the regional office through an online application3.Following the start of dengue outbreak in week 4 of 2018, the regional office organized meetings with physicians in each ED to present the dengue epidemiological update and to recommend the coding of ED visit related to dengue for any suspect case (acute fever disease and two or more of the following signs or symptoms: nausea, vomiting, rash, headache, retro-orbital pain, myalgia). During these meetings, it was found that the version of ICD-10 (International Classification of Diseases) was different from one ED to another. Indeed, some ED used A90, A91 (ICD-10 version: 2015) for visit related to dengue and others used A97 and subdivisions (ICD-10 version: 2016). As the ICD-10 version: 2015 was implemented at the national server, some passages could be excluded. In this context, the thesaurus of medical diagnosis implemented in the national database has been updated so that all codes can be accepted. ED visits related to dengue fever has been then described according to age group, gender and hospitalization.ResultsFrom week 9 of 2018, the syndromic surveillance system was operational to monitor dengue outbreak. The regional office has provided each week, an epidemic curve of ED visits for dengue and a dashboard on descriptive characteristic of these visits. In total, 441 ED visits for dengue were identified from week 9 to week 34 of 2018 (Figure 1). On this period, the weekly number of ED visits for dengue was correlated with the weekly number of probable and confirmed autochthonous cases (rho=0.86, p<0.001). Among these visits, the male/female ratio was 0.92 and median (min-max) age was 44 (2-98) years. The distribution by age group showed that 15-64 year-old (72.1%, n=127) were most affected. Age groups 65 years and more and 0-14 year-old represented respectively 21.8% (n=96) and 6.1% (n=27) of dengue visits. About 30% of dengue visits were hospitalized.ConclusionsAccording Buehler et al., “the flexibility of a surveillance system refers to the system's ability to change as needs change. The adaptation to changing detection needs or operating conditions should occur with minimal additional time, personnel, or other resources. Flexibility generally improves the more data processing is handled centrally rather than distributed to individual data-providing facilities because fewer system and operator behavior changes are needed...” 4.During this dengue outbreak, the syndromic surveillance system seems to have met this purpose. In four weeks (from week 5 to week 9 of 2018), the system was able to adapt to the epidemiological situation with minimal additional resources and personnel. Indeed, updates were not made in the IT systems of each EDs’ but at the level of the national ANSP server (by one person). This surveillance system was also flexible thank to the reactivity of ED physicians who timely implemented coding of visits related to dengue fever.In conclusion, ED surveillance system constitutes an added-value for the dengue outbreak monitoring in Reunion Island. The automated collection and analysis data allowed to provide hospital morbidity (severe dengue) data to public health authorities. Although the epidemic has decreased, this system also allows to continue a routine active surveillance in order to quickly identify a new increase.References1Santé publique France. Surveillance de la dengue à la Réunion. Point épidémiologique au 4 septembre 2018. http://invs.santepubliquefrance.fr/fr/Publications-et-outils/Points-epidemiologiques/Tous-les-numeros/Ocean-Indien/2018/Surveillance-de-la-dengue-a-la-Reunion.-Point-epidemiologique-au-4-septembre-2018. [Accessed September 8, 2018].2Vilain P, Filleul F. La surveillance syndromique à la Réunion : un système de surveillance intégré. [Syndromic surveillance in Reunion Island: integrated surveillance system]. Bulletin de Veille Sanitaire. 2013;(21):9-12. http://invs.santepubliquefrance.fr/fr/Publications-et-outils/Bulletin-de-veille-sanitaire/Tous-les-numeros/Ocean-indien-Reunion-Mayotte/Bulletin-de-veille-sanitaire-ocean-Indien.-N-21-Septembre-2013. [Accessed September 4, 2018].3Fouillet A, Fournet N, Caillère N et al. SurSaUD® Software: A Tool to Support the Data Management, the Analysis and the Dissemination of Results from the French Syndromic Surveillance System. OJPHI. 2013; 5(1): e118.4Buehler JW, Hopkins RS, Overhage JM, Sosin DM, Tong V; CDC Working Group. Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group. MMWR Recomm Rep. 2004;53(RR-5):1-11.

scholarly journals Establishing a nationwide emergency department-based syndromic surveillance system for better public health responses in Taiwan

2008 ◽  
Vol 8 (1) ◽  
Author(s):  
Tsung-Shu Joseph Wu ◽  
Fuh-Yuan Frank Shih ◽  
Muh-Yong Yen ◽  
Jiunn-Shyan Julian Wu ◽  
Shiou-Wen Lu ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Syndromic Surveillance System

scholarly journals Harnessing Syndromic Surveillance Emergency Department Data to Monitor Health Impacts During the 2015 Special Olympics World Games

2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 99S-105S ◽  
Author(s):  
Emily Kajita ◽  
Monica Z. Luarca ◽  
Han Wu ◽  
Bessie Hwang ◽  
Laurene Mascola
Keyword(s):  
Public Health ◽  
Los Angeles ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Los Angeles County ◽  
International Travel ◽  
Poison Control ◽  
Special Olympics ◽  
Syndromic Surveillance System ◽  
Mass Gatherings

Introduction: Mass gatherings that attract a large international presence may cause or amplify point-source outbreaks of emerging infectious disease. The Los Angeles County Department of Public Health customized its syndromic surveillance system to detect increased syndrome-specific utilization of emergency departments (EDs) and other medical encounters coincident to the 2015 Special Olympics World Games. Materials and Methods: We queried live databases containing data on ED visits, California Poison Control System calls, and Los Angeles County coroner-investigated deaths for increases in daily counts from July 19 to August 6, 2015. We chose syndrome categories based on the potential for disease outbreaks common to international travel and dormitory settings, morbidity amplified by high temperatures, and bioterrorism threats inherent to mass gatherings. We performed line-list reviews and trend analyses of total, syndrome-specific, and region-specific daily counts, using cumulative sum-based signals. We also piloted a novel strategy of requesting that ED registrars proactively tag Special Olympics attendees in chief complaint data fields. Results: The syndromic surveillance system showed that the 2015 Special Olympics did not generate large-scale acute morbidities leading to detectable stress on local EDs. We recruited 10 hospitals for proactive patient tagging, from which 16 Special Olympics attendees were detected; these patients reported various symptoms, such as injury, vomiting, and syncope. Practice Implications: As an enhancement to traditional syndromic surveillance, proactive patient tagging can illuminate potential epidemiologic links among patients in challenging syndromic surveillance applications, such as mass gatherings. Syndromic surveillance has the potential to enhance ED patient polling and reporting of exposure, symptom, and other epidemiologic case definition criteria to public health agencies in near-real time.

scholarly journals Development and validation of an automated emergency department-based syndromic surveillance system to enhance public health surveillance in Yukon: a lower-resourced and remote setting

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Etran Bouchouar ◽  
Benjamin M. Hetman ◽  
Brendan Hanley
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Validation Dataset ◽  
Free Text ◽  
Mass Gathering ◽  
Syndromic Surveillance System ◽  
Development And Validation ◽  
Remote Setting

Abstract Background Automated Emergency Department syndromic surveillance systems (ED-SyS) are useful tools in routine surveillance activities and during mass gathering events to rapidly detect public health threats. To improve the existing surveillance infrastructure in a lower-resourced rural/remote setting and enhance monitoring during an upcoming mass gathering event, an automated low-cost and low-resources ED-SyS was developed and validated in Yukon, Canada. Methods Syndromes of interest were identified in consultation with the local public health authorities. For each syndrome, case definitions were developed using published resources and expert elicitation. Natural language processing algorithms were then written using Stata LP 15.1 (Texas, USA) to detect syndromic cases from three different fields (e.g., triage notes; chief complaint; discharge diagnosis), comprising of free-text and standardized codes. Validation was conducted using data from 19,082 visits between October 1, 2018 to April 30, 2019. The National Ambulatory Care Reporting System (NACRS) records were used as a reference for the inclusion of International Classification of Disease, 10th edition (ICD-10) diagnosis codes. The automatic identification of cases was then manually validated by two raters and results were used to calculate positive predicted values for each syndrome and identify improvements to the detection algorithms. Results A daily secure file transfer of Yukon’s Meditech ED-Tracker system data and an aberration detection plan was set up. A total of six syndromes were originally identified for the syndromic surveillance system (e.g., Gastrointestinal, Influenza-like-Illness, Mumps, Neurological Infections, Rash, Respiratory), with an additional syndrome added to assist in detecting potential cases of COVID-19. The positive predictive value for the automated detection of each syndrome ranged from 48.8–89.5% to 62.5–94.1% after implementing improvements identified during validation. As expected, no records were flagged for COVID-19 from our validation dataset. Conclusions The development and validation of automated ED-SyS in lower-resourced settings can be achieved without sophisticated platforms, intensive resources, time or costs. Validation is an important step for measuring the accuracy of syndromic surveillance, and ensuring it performs adequately in a local context. The use of three different fields and integration of both free-text and structured fields improved case detection.

scholarly journals Early evaluation of impacts of cold waves and floods during winter 2018 in France

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Anne Fouillet ◽  
Cecile Forgeot ◽  
Marie-Michele Thiam ◽  
Celine Caserio-Schonemann
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Health Agency ◽  
Health Impact ◽  
Cold Weather ◽  
Cold Wave ◽  
Seine River ◽  
Syndromic Surveillance System ◽  
Paris Area

ObjectiveThe presentation describes the results of the daily monitoring of health indicators conducted by the French public health agency during the major floods and the cold wave that occurred in January 2018 in France, in order to early identify potential impact of those climatic events on the population.IntroductionThe Seine River rises at the north-East of France and flows through Paris before emptying into the English Channel. On January 2018 (from 22th January to 11th February, Weeks 4 to 6), major floods occurred in the Basin of Seine River, after an important rainy period. This period was also marked by the occurrence on the same area of a first cold wave on Week 6 (from 5th to 7th February), including heavy snowfall and ice conditions from 9th to 10th February. A second similar cold wave occured from 28th February and 1st March.Floods of all magnitude are known to have potential health impacts on population [1], both at short, medium and long term both on physical (injuries, diarrhoeal disease, Carbon Monoxyde poisoning, vector-borne disease) and mental health. Extreme cold weather have also the potential to further impact on human health through direct exposure to lower temperatures, and associated adverse conditions, such as snow and ice [2]. Such situations may be particularly associated to direct impact like hypothermia, frostbite and selected bone/joint injuries).MethodsSince 2004, the French Public Health Agency (Santé publique France) set up a national syndromic surveillance system SurSaUD, enabling to ensure morbidity and mortality surveillance [3]. In 2018, morbidity data were daily collected from a network involving about 700 emergency departments (ED) and 58 emergency general practitioners’ associations SOS Médecins. 92% of the national ED attendances and 95% of national SOS Médecins visits are caught by the system.Both demographic (age and gender), administrative (date and location of consultation, transport) and medical information (chief complaint, medical diagnosis using ICD10 codes in ED and specific thesauri in SOS Médecins associations, severity, hospitalization after discharge) are recorded for each patient.The daily and weekly evolution of the number of all-cause ED attendances and SOS Médecins consultations during the flooding period were compared to the evolution on the two previous years. The number of hospitalisations after ED discharge was also monitored. The immediate health impact of floods and cold waves was assessed by monitoring eight syndromic indicators: gastroenteritis, carbon monoxide poisoning, burnt, stress, faintness, drowning, injuries and hypothermia.Analyses were performed by age group (<15 years, 15-64 years, more than 65 years) and at different geographical levels (national, Paris region and districts located in the Basin of Seine River).ResultsIn 2018, syndromic surveillance did not show any major impact on all-cause ED attendances and SOS Médecins consultations from week 4 to week 6, neither in Paris area nor in other areas along the Seine River. The recorded numbers were comparable to the two precedent years in all age groups.A decrease of the all-cause ED attendances was observed during the 1st day with ice conditions in Normandy and Paris, mainly in children and adults aged 15-64 years.During week 6 in Paris area, an increase of ED attendances was observed for injuries (+4% compared to the past weeks – figure 1) and to a lesser extent for hypothermia and frostbite (16 attendances compared to less than 9 for the past weeks). Similar increase in injuries were observed in Normandy during the second cold wave (Figure 1).ConclusionsDuring the flood episode, the rising water level was slow with foreseeable evolution, compared to other sudden flood events occurring in south of France in 2010 due to violent thunderstorms. This progressive evolution allows French authority to deploy wide specific organization in order to mitigate impact on concerned populations. That may explain the absence impact observed in ED at regional and national levels during the flood disaster. The evolution of injuries during 2018 episode is attributable to the cold wave that occurred simultaneously.As the French syndromic surveillance system is implemented on the whole territory and collects emergency data routinely since several years, it constitutes a reactive tool to assess the potential public health impact of both sudden and predictable disasters. It can either contribute to adapt management action or reassure decision makers if no major impact is observed.References[1] Ahern M, Kovats S. The health impacts of floods. In: Few R, Matthies F, eds. Flood hazards and health: responding to present and future risks. London, Earthscan, 2006:28–53.[2] Hughes H, Morbey R, Hughes T. et al. Using an Emergency Department Syndromic Surveillance System to investigate the impact of extreme cold weather events Public Health. 2014 Jul;128(7):628-35.[3] Caserio-Schönemann C, Bousquet V, Fouillet A, Henry V. The French syndromic surveillance system SurSaUD (R). Bull Epidémiol Hebd 2014;3-4:38-44.

scholarly journals Increase in emergency department visits related to cannabis reported using syndromic surveillance system

2019 ◽  
Vol 29 (4) ◽  
pp. 621-625 ◽  
Author(s):  
G N Noel ◽  
A M Maghoo ◽  
F F Franke ◽  
G V Viudes ◽  
P M Minodier
Keyword(s):  
Emergency Department ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Age Groups ◽  
The United States ◽  
Cross Sectional Study ◽  
Emergency Department Visits ◽  
Cross Sectional ◽  
Syndromic Surveillance System ◽  
Icd 10

Abstract Background Cannabis is illegal in France but, as in many countries, legalization is under debate. In the United States, an increase of emergency department (ED) visits related to cannabis exposure (CE) in infants and adults was reported. In France, a retrospective observational study also suggested an increase of CE in children under 6 years old. This study only included toddlers and the data sources used did not allow repeated analysis for monitoring. Methods Our study aimed to evaluate the trend in visits for CE in ED in patients younger than 27 years old in Southern France. A cross-sectional study using the Electronic Emergency Department Abstracts (EEDA) included in the national Syndromic Surveillance System. CE visits were defined using International Classification of Disease (ICD-10). Results From 2009 to 2014, 16 EDs consistently reported EEDA with <5% missing diagnosis code. Seven hundred and ninety seven patients were admitted for CE including 49 (4.1%) children under 8 years old. From 2009–11 to 2012–14, the rate of CE visits increased significantly across all age groups. The highest increase was in the 8–14 years old (+144%; 1.85–4.51, P < 0.001) and was also significant in children under 8 (0.53–1.06; P = 0.02). Among children under 8, hospitalization rate (75.5% vs. 16.8%; P < 0.001) and intensive care unit admissions (4.1% vs. 0.1%; P < 0.001) were higher compared with patients older than 8 years. Conclusion These trends occurred despite cannabis remaining illegal. EEDA could be useful for monitoring CE in EDs.

Framework for the Development of Response Protocols for Public Health Syndromic Surveillance Systems: Case Studies of 8 US States

2009 ◽  
Vol 3 (S1) ◽  
pp. S29-S36 ◽  
Author(s):  
Lori Uscher-Pines ◽  
Corey L. Farrell ◽  
Steven M. Babin ◽  
Jacqueline Cattani ◽  
Charlotte A. Gaydos ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
The United States ◽  
Essential Elements ◽  
System Response ◽  
Surveillance Systems ◽  
Health Departments ◽  
Public Health Response ◽  
Syndromic Surveillance System

ABSTRACTObjectives: To describe current syndromic surveillance system response protocols in health departments from 8 diverse states in the United States and to develop a framework for health departments to use as a guide in initial design and/or enhancement of response protocols.Methods: Case study design that incorporated in-depth interviews with health department staff, textual analysis of response plans, and a Delphi survey of syndromic surveillance response experts.Results: All 8 states and 30 of the 33 eligible health departments agreed to participate (91% response rate). Fewer than half (48%) of surveyed health departments had a written response protocol, and health departments reported conducting in-depth investigations on fewer than 15% of syndromic surveillance alerts. A convened panel of experts identified 32 essential elements for inclusion in public health protocols for response to syndromic surveillance system alerts.Conclusions: Because of the lack of guidance, limited resources for development of response protocols, and few examples of syndromic surveillance detecting previously unknown events of public health significance, health departments have not prioritized the development and refinement of response protocols. Systems alone, however, are not effective without an organized public health response. The framework proposed here can guide health departments in creating protocols that will be standardized, tested, and relevant given their goals with such systems. (Disaster Med Public Health Preparedness. 2009;3(Suppl 1):S29–S36)

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