scholarly journals “Koman i lé” : An Online Self-Reported Symptoms Surveillance System in Reunion Island

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Nadège Marguerite ◽  
Pascal Vilain ◽  
Etienne Sévin ◽  
Farid Sahridji ◽  
Laurent Filleul
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Outbreaks ◽  
Reunion Island ◽  
Web Based ◽  
Health Authorities ◽  
Major Outbreak ◽  
Policy Information ◽  
Réunion Island ◽  
Sentinel Population

In Reunion Island, the population is very sensitive to public health concerns. In this context, the health authorities implemented since April 2014 a web-based surveillance system, called “Koman i lé” and based on a volunteers' cohort in general population. This surveillance system allowed to follow the seasonal influenza epidemic in 2014 and the major outbreak of conjunctivitis from January to April 2015. In conclusion, the sentinel population allows the population of Reunion Island to take an active part in the health regional policy. Information reported by individuals can increase traditional public health methods for more timely detection of disease outbreaks.

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 Enhanced syndromic surveillance during the 9 th Indian Ocean Island Games, 2015

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Pascal Vilain ◽  
Frédéric Pages ◽  
Guy Henrion ◽  
Xavier Combes ◽  
Marc Weber ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Reunion Island ◽  
Mass Gathering ◽  
Secondary Diagnosis ◽  
Syndromic Surveillance System ◽  
Ocean Island ◽  
Réunion Island ◽  
Ed Visits

ObjectiveTo describe how syndromic surveillance was enhanced to detecthealth events during the 9thIndian Ocean Island Games (IOIG) inReunion Island.IntroductionThe 9thIOIG took place in Reunion Island from July 31 to August9, 2015. This sport event gathered approximatively 1 640 athletes,2 000 volunteers and several thousand spectators from seven islands:Comoros, Madagascar, Maldives, Mauritius, Mayotte, Seychelles andReunion.In response to the import risk of infectious diseases from thesecountries where some of them are endemics, the syndromicsurveillance system, which captures 100% of all EmergencyDepartment visits, was enhanced in order to detect any health event.MethodsIn Reunion Island, syndromic surveillance system is based onOSCOUR® network (Organisation de la surveillance coordonnéedes urgences) that collects data from all emergency departments ofthe island. Data are daily transmitted to the French national publichealth agency then are available to the regional office. At the regionallevel, data are integrated into an application that allows the built ofpredefined syndromic groups according to the health risks related tomass gatherings (Table 1, parts 1 to 3) and complemented by specificsyndromic groups (table 1, part 4). Daily analyses with temporal[1] and spatial-temporal [2] algorithms were performed during thesurveillance period of July 27 to August 13, 2015. In addition to thismonitoring, ED physicians were requested to proactively tag Y33(ICD-10) as secondary diagnosis, each ED visits related to IOIG. Linelists were reviewed daily. Each day, an epidemiological report wassend to public health authorities.ResultsFrom July 31 to August 9, 2015, the activity of EDs was inaccordance with that expected. No health events were detected bythe syndromic surveillance system except for the syndrome “alcoholintoxication” for which consecutive signals were observed fromAugust 6 to 9, 2015. This increase occurs commonly at the beginningof each month (due to the social benefits payday) [3] nevertheless thisevent has probably been increased by IOIG (finals for team sportsand games closing ceremony). In total, 8 ED visits were tagged Y33as secondary diagnosis. In over half the cases, visits were related totrauma.ConclusionsThe syndromic surveillance system proved to be useful for thesurveillance of mass gathering events due to its capacity to detecthealth events but also to provide reassurance public health authorities[4]. As described in literature [5], few ED visits were tagged in relationto IOIG. Indeed, the tag of ED visits was implemented two weeksbefore the games, and given the shifts of ED physicians, some of themmay have not been informed. In the future, preparation meetings withphysicians will have to be planned several months before in order toimprove the response rate for mass gathering events.

scholarly journals Using a Syndromic Approach to Study Health Impact and Risk Factors of Alcohol Intoxication in Reunion Island

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Pascal Vilain ◽  
Sophie Larrieu ◽  
Xavier Combes ◽  
Arnaud Bourdé ◽  
Pierre-Jean Marianne dit Cassou ◽  
...  
Keyword(s):  
Public Health ◽  
Alcohol Intoxication ◽  
Public Health Problem ◽  
Health Impact ◽  
Major Public Health Problem ◽  
Reunion Island ◽  
Syndromic Surveillance System ◽  
Health Authorities ◽  
Réunion Island ◽  
Syndromic Approach

In Reunion Island, alcohol is a major public health problem. Syndromic surveillance system based on ED data was used for describe alcohol intoxication visits between 2010-2012 and factors associated with their variations. During the study period, alcohol intoxication was the second leading cause of all visits in ED. Time-series models showed a robust association between ED visits and days of minimum social benefits payment, weekends, public holidays. These results will be transmitted to health authorities in order to orient the public health policies.

scholarly journals A major outbreak of gastroenteritis in Réunion Island in 2012: first identification of G12 rotavirus on the Island

2013 ◽  
Vol 18 (19) ◽  
Author(s):  
N Caillère ◽  
P Vilain ◽  
E Brottet ◽  
J Kaplon ◽  
K Ambert-Balay ◽  
...  
Keyword(s):  
Reunion Island ◽  
Binary File ◽  
Major Outbreak ◽  
Réunion Island

Binary file ES_Abstracts_Final_ECDC.txt matches

scholarly journals Online Information on Electronic Cigarettes: Comparative Study of Relevant Websites From Baidu and Google Search Engines

10.2196/14725 ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. e14725
Author(s):  
Ting Chen ◽  
Sarah Gentry ◽  
Dechao Qiu ◽  
Yan Deng ◽  
Caitlin Notley ◽  
...  
Keyword(s):  
Public Health ◽  
Search Engines ◽  
Electronic Cigarettes ◽  
Online Information ◽  
Web Based ◽  
The Public ◽  
Health Authorities ◽  
Cigarette Advertising ◽  
Public Health Authorities ◽  
Google Search

Background Online information on electronic cigarettes (e-cigarettes) may influence people’s perception and use of e-cigarettes. Websites with information on e-cigarettes in the Chinese language have not been systematically assessed. Objective The aim of this study was to assess and compare the types and credibility of Web-based information on e-cigarettes identified from Google (in English) and Baidu (in Chinese) search engines. Methods We used the keywords vaping or e-cigarettes to conduct a search on Google and the equivalent Chinese characters for Baidu. The first 50 unique and relevant websites from each of the two search engines were included in this analysis. The main characteristics of the websites, credibility of the websites, and claims made on the included websites were systematically assessed and compared. Results Compared with websites on Google, more websites on Baidu were owned by manufacturers or retailers (15/50, 30% vs 33/50, 66%; P<.001). None of the Baidu websites, compared to 24% (12/50) of Google websites, were provided by public or health professional institutions. The Baidu websites were more likely to contain e-cigarette advertising (P<.001) and less likely to provide information on health education (P<.001). The overall credibility of the included Baidu websites was lower than that of the Google websites (P<.001). An age restriction warning was shown on all advertising websites from Google (15/15) but only on 10 of the 33 (30%) advertising websites from Baidu (P<.001). Conflicting or unclear health and social claims were common on the included websites. Conclusions Although conflicting or unclear claims on e-cigarettes were common on websites from both Baidu and Google search engines, there was a lack of online information from public health authorities in China. Unbiased information and evidence-based recommendations on e-cigarettes should be provided by public health authorities to help the public make informed decisions regarding the use of e-cigarettes.

scholarly journals Analyzing Twitter Data to Evaluate People’s Attitudes towards Public Health Policies and Events in the Era of COVID-19

2021 ◽  
Vol 18 (12) ◽  
pp. 6272
Author(s):  
Meng Hsiu Tsai ◽  
Yingfeng Wang
Keyword(s):  
Public Health ◽  
Sentiment Analysis ◽  
Surveillance System ◽  
Data Preprocessing ◽  
Health Policies ◽  
Public Health Policies ◽  
Twitter Data ◽  
Health Authorities ◽  
Public Health Authorities ◽  
People’S Attitudes

Policymakers and relevant public health authorities can analyze people’s attitudes towards public health policies and events using sentiment analysis. Sentiment analysis focuses on classifying and analyzing text sentiments. A Twitter sentiment analysis has the potential to monitor people’s attitudes towards public health policies and events. Here, we explore the feasibility of using Twitter data to build a surveillance system for monitoring people’s attitudes towards public health policies and events since the beginning of the COVID-19 pandemic. In this study, we conducted a sentiment analysis of Twitter data. We analyzed the relationship between the sentiment changes in COVID-19-related tweets and public health policies and events. Furthermore, to improve the performance of the early trained model, we developed a data preprocessing approach by using the pre-trained model and early Twitter data, which were available at the beginning of the pandemic. Our study identified a strong correlation between the sentiment changes in COVID-19-related Twitter data and public health policies and events. Additionally, the experimental results suggested that the data preprocessing approach improved the performance of the early trained model. This study verified the feasibility of developing a fast and low-human-effort surveillance system for monitoring people’s attitudes towards public health policies and events during a pandemic by analyzing Twitter data. Based on the pre-trained model and early Twitter data, we can quickly build a model for the surveillance system.

Risk Communication and Crisis Communication in Infectious Disease Outbreaks in Germany: What Is Being Done, and What Needs to be Done

2014 ◽  
Vol 8 (3) ◽  
pp. 206-211 ◽  
Author(s):  
Petra Dickmann ◽  
Nadine Biedenkopf ◽  
Sam Keeping ◽  
Markus Eickmann ◽  
Stephan Becker
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Risk Communication ◽  
Crisis Communication ◽  
Contextual Information ◽  
International Health ◽  
Disease Outbreaks ◽  
World Health ◽  
Health Authorities ◽  
Public Health Authorities

AbstractObjectiveRisk communication plays a central role in the management of infectious disease. The World Health Organization's 2005 International Health Regulations have highlighted the need for countries to strengthen their capacities in this area to ensure effective responses to public health emergencies. We surveyed laboratories, hospitals, and public health institutions in Germany to detail the current situation regarding risk communication and crisis management and to identify which areas require further development.MethodsA mixed methods approach was adopted. An initial questionnaire was distributed to relevant persons in laboratories and hospitals, and semistructured interviews were conducted with selected participants. Representatives from state public health authorities, federal agencies, and media also were interviewed to add additional contextual information to the questionnaire responses.ResultsBased on the responses received, the universal sense among key stakeholders was that risk communication and crisis communication measures must be improved. Collaborative working was a consistent theme, with participants suggesting that a partnering strategy could help to improve performance. This approach could be achieved through better coordination between groups, for example, through a knowledge-sharing policy.ConclusionsMore research is needed on how such collaboration might be implemented, along with a general conceptual framework for risk communication to underpin the overall strategy. (Disaster Med Public Health Preparedness. 2014;0:1-6)

scholarly journals Implementation of a nationwide Waterborne disease outbreak surveillance system in France

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
D Mouly ◽  
J Pouey ◽  
C Galey ◽  
J Chesneau ◽  
G Jones ◽  
...  
Keyword(s):  
Public Health ◽  
Drinking Water ◽  
Health Insurance ◽  
Surveillance System ◽  
Water System ◽  
Ministry Of Health ◽  
Voluntary Reporting ◽  
Health Authorities ◽  
Environmental Criteria ◽  
Drinking Water System

Abstract Issue/Problem Waterborne disease outbreaks (WBDOs) remain a public health issue in developed countries, but to date the surveillance of WBDOs in France, mainly based on the voluntary reporting of clusters of acute gastrointestinal infections (AGIs) by general practitioners to health authorities, is characterized by low sensitivity. In this context an integrated and automatized approach to detect WBDO relying on the identification of clusters of medicalized AGI cases sharing a same drinking water networks (DWN) was developed, evaluated in a simulation study and tested in a pilot study by the French National Public Health Agency. Description of the problem Two national big databases support the detection process of potential WBDO: health insurance database for AGI, ministry of health database for drinking water system information. Each detected outbreak has to be investigated regarding environmental criteria during the days before the onset of the outbreak: results on bacterial water monitoring, weather (e.g. heavy rain), technical incidents in the drinking water system (e.g. chlorination breakdown, alarm malfunction). To evaluate the strength of association with drinking water, four levels are proposed based on epidemiological and environmental criteria (strong, probable, possible and undetermined). Results The WBDO surveillance system has been implemented in all french departments since start of 2019 and support by the ministry of health. A web-application, named “EpiGEH”, was also developed to support the surveillance system. A retrospective study between 2010 and 2017 has detected almost 300 to 550 potential WBDO per year while voluntary reporting identified 2 to 3 WBDO each year during the same period. Lessons Such a specific surveillance system should help health authorities to formulate recommendations regarding the management of drinking water systems and propose appropriate preventive measures, in accordance with the water safety plans. Key messages The WBDO surveillance system based from health insurance databases constitutes a daily surveillance system of drinking water quality. The WBDO surveillance system should drastically improve the detection sensitivity by a factor 100 to 200 compared to voluntary reporting.

scholarly journals ‘Watch the Flu’: A Tweet Monitoring Tool for Epidemic Intelligence of Influenza in Australia

2020 ◽  
Vol 34 (09) ◽  
pp. 13616-13617
Author(s):  
Brian Jin ◽  
Aditya Joshi ◽  
Ross Sparks ◽  
Stephen Wan ◽  
Cécile Paris ◽  
...  
Keyword(s):  
Public Health ◽  
Language Processing ◽  
Visual Analysis ◽  
Disease Outbreaks ◽  
Monitoring Tool ◽  
Time Data ◽  
Web Based ◽  
Data Pipeline ◽  
Epidemic Intelligence ◽  
Health Experts

‘Watch The Flu’ is a tool that monitors tweets posted in Australia for symptoms of influenza. The tool is a unique combination of two areas of artificial intelligence: natural language processing and time series monitoring, in order to assist public health surveillance. Using a real-time data pipeline, it deploys a web-based dashboard for visual analysis, and sends out emails to a set of users when an outbreak is detected. We expect that the tool will assist public health experts with their decision-making for disease outbreaks, by providing them insights from social media.

scholarly journals Online Information on Electronic Cigarettes: Comparative Study of Relevant Websites From Baidu and Google Search Engines (Preprint)

2019 ◽  
Author(s):  
Ting Chen ◽  
Sarah Gentry ◽  
Dechao Qiu ◽  
Yan Deng ◽  
Caitlin Notley ◽  
...  
Keyword(s):  
Public Health ◽  
Search Engines ◽  
Electronic Cigarettes ◽  
Online Information ◽  
Web Based ◽  
The Public ◽  
Health Authorities ◽  
Cigarette Advertising ◽  
Public Health Authorities ◽  
Google Search

BACKGROUND Online information on electronic cigarettes (e-cigarettes) may influence people’s perception and use of e-cigarettes. Websites with information on e-cigarettes in the Chinese language have not been systematically assessed. OBJECTIVE The aim of this study was to assess and compare the types and credibility of Web-based information on e-cigarettes identified from Google (in English) and Baidu (in Chinese) search engines. METHODS We used the keywords <i>vaping</i> or <i>e-cigarettes</i> to conduct a search on Google and the equivalent Chinese characters for Baidu. The first 50 unique and relevant websites from each of the two search engines were included in this analysis. The main characteristics of the websites, credibility of the websites, and claims made on the included websites were systematically assessed and compared. RESULTS Compared with websites on Google, more websites on Baidu were owned by manufacturers or retailers (15/50, 30% vs 33/50, 66%; <i>P</i>&lt;.001). None of the Baidu websites, compared to 24% (12/50) of Google websites, were provided by public or health professional institutions. The Baidu websites were more likely to contain e-cigarette advertising (<i>P</i>&lt;.001) and less likely to provide information on health education (<i>P</i>&lt;.001). The overall credibility of the included Baidu websites was lower than that of the Google websites (<i>P</i>&lt;.001). An age restriction warning was shown on all advertising websites from Google (15/15) but only on 10 of the 33 (30%) advertising websites from Baidu (<i>P</i>&lt;.001). Conflicting or unclear health and social claims were common on the included websites. CONCLUSIONS Although conflicting or unclear claims on e-cigarettes were common on websites from both Baidu and Google search engines, there was a lack of online information from public health authorities in China. Unbiased information and evidence-based recommendations on e-cigarettes should be provided by public health authorities to help the public make informed decisions regarding the use of e-cigarettes.

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