scholarly journals Tablet-based participatory syndromic surveillance at Simhashta festival in India

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Vishal Diwan ◽  
Anette Hulth ◽  
Ponnaiah Manickam ◽  
Viduthalai V Balagurusamy ◽  
Deepak Agnihotri ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Large Population ◽  
Central India ◽  
Mass Gathering ◽  
Summary Report ◽  
Syndromic Surveillance System ◽  
Mass Gatherings ◽  
The World

Objective: To develop, test and study tablet-based participatory syndromic surveillance system for common infectious disease conditions at community level in Simhashta religious mass gathering in Ujjain, India, 2016.Introduction: Infectious disease surveillance for generating early warnings to enable a prompt response during mass gatherings has long been a challenge in India 1,2 as well as in other parts of the world 3,4,5. Ujjain, Madhya Pradesh in Central India hosted one of the largest religious festival in the world called ‘Simhasth kumbh mela’ on the banks of River Kshipra, where more than 50 million attendees came for holy dip during April 22 to May 21, 2016. The attendees included pilgrims (residents and visitors), observers, officials and volunteers. We developed an android application with automated summary reports and an interactive dashboard for syndromic surveillance during the gathering.Methods: We established the participatory surveillance at all 22 sectors of the festival area, and at 20 out-patient hospitals and 12 pharmacies. We trained 55 nursing and social work graduate trainees to collect data from all these settings. The data collectors visited designated spots daily during a fixed time and collected age, gender, residence and self-reported symptoms from consenting attendees during the festival period. The application automatically added date, time and location of interview to each record and data was transmitted to a web server. We monitored the data in the interactive dashboard and prepared summary report on a periodic basis. Daily summary report of self-reported symptoms by time, place and person was shared daily evening with the festival surveillance authority.Results: Of the total 93,020 invited pilgrims, 91% participated in the surveillance. Almost 90% of those were from outside the festival city, 60% were men and 57% were aged 15 to 44 years. Almost 50% of them self-reported presence of at least one symptom. Most frequently reported symptoms were dehydration due to heat (13%), cold (13%), fever (7%) and loose stool (5%). During the festival period of over one month, surveillance data indicated increasing trends of self-reported cough and fever and declining trends of self-reported dehydration (Figure-1). The designated public health authorities for the festival did make use of the information for appropriate action. This tablet-based application was able to collect, process and visualise around 2500 records per day from the community without any data loss.Conclusions: To our knowledge, this is the first report from India documenting real-time surveillance of the community using hand-held devices during a mass gathering. Despite some implementation issues and limitations in the approach and data collected, the use of digital technology provided well-timed information avoiding tedious manual work and reduced a good amount of human resources and logistics involved in reporting symptoms with a traditional paper-based method in such a large population. In retrospect, the main utility of the surveillance output was that of giving reassurance to the officials, as no major outbreaks occurred during the event. We believe that this experience and further analyses will provide input for the establishment and use of such a surveillance system during mass gatherings. The team of investigators propose improving the methods and tools for future use.

scholarly journals Fever in Children - an Assessment of Validity by a Shewhart Model in a Syndromic Surveillance System in China

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Changming Zhou ◽  
Huijian Cheng ◽  
Genming Zhao ◽  
Qi Zhao ◽  
Biao Xu ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Case Report ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Disease Outbreaks ◽  
Syndromic Surveillance System ◽  
Infectious Disease Outbreaks ◽  
Shewhart Chart ◽  
Common Infectious Disease ◽  
Report System

The objective is to evaluate the validity of the signals generated by Shewhart chart to detect the increase in febrile children with patients with common infectious diseases. There were 28,049 and 42,029 reports for febrile patients in the two study counties during the 2-year period. The sensitivity were 29.03% and 34.78%. The PPVs were 64.29% and 53.33%. The sensitivity of signals in the syndromic surveillance system was low using the Shewhart model while the PPV was relatively high which suggested that this syndromic surveillance system had potential ability to supplement conventional case report system in detecting common infectious disease outbreaks.

scholarly journals ISS-An Electronic Syndromic Surveillance System for Infectious Disease in Rural China

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e62749 ◽  
Author(s):  
Weirong Yan ◽  
Lars Palm ◽  
Xin Lu ◽  
Shaofa Nie ◽  
Biao Xu ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Rural China ◽  
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 Development and Validation of an Automated Emergency Department-Based Syndromic Surveillance System for Use at a Mass Gathering Event (2020 Arctic Winter Games, Yukon Canada) During a Global Pandemic: Implications for Lower Resourced and Remote Settings

2020 ◽  
Author(s):  
Etran Bouchouar ◽  
Benjamin M. Hetman ◽  
Brendan Hanley
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
The Arctic ◽  
Validation Dataset ◽  
Mass Gathering ◽  
Syndromic Surveillance System ◽  
Local Public Health ◽  
Global Pandemic

Abstract Background: Automated syndromic surveillance systems are useful tools for rapidly identifying health risks during times when routine surveillance and follow-up cannot meet the demands of the population. In Yukon, Canada, the Arctic Winter Games were scheduled in March 2020, and were expected to increase the local population beyond the capacity of local public health surveillance. An emergency department-based automated syndromic surveillance system was therefore developed and validated using local hospitalization records for use during the event. 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 to detect syndromic cases from three different fields (triage notes; chief complaint; discharge diagnosis) using Yukon emergency department case data containing information from 19,082 visits over the period of October 1, 2018 to April 30, 2019. 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 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. However, the system was rapidly adapted into an additional surveillance tool for use in the COVID-19 pandemic. Conclusions: Validation is an important step for measuring the accuracy of syndromic surveillance, and ensuring it performs adequately in a local context. Ultimately, the 2020 Arctic Winter Games were cancelled due to the risks associated with mass gatherings during the global pandemic of COVID-19 and could not therefore be tested under a mass gathering scenario. However, the results from our validation study suggest that our surveillance system may be useful for future mass gathering events and proved a timely development for integration into Yukon’s COVID-19 surveillance infrastructure.

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.

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