scholarly journals High added value of a population-based participatory surveillance system for community acute gastrointestinal, respiratory and influenza-like illnesses in Sweden, 2013–2014 using the web

2017 ◽  
Vol 145 (6) ◽  
pp. 1193-1202 ◽  
Author(s):  
A. PINI ◽  
H. MERK ◽  
A. CARNAHAN ◽  
I. GALANIS ◽  
E. VAN STRATEN ◽  
...  

SUMMARYIn 2013–2014, the Public Health Agency of Sweden developed a web-based participatory surveillance system, Hӓlsorapport, based on a random sample of individuals reporting symptoms weekly online, to estimate the community incidence of self-reported acute gastrointestinal (AGI), acute respiratory (ARI) and influenza-like (ILI) illnesses and their severity. We evaluated Hӓlsorapport's acceptability, completeness, representativeness and its data correlation with other surveillance data. We calculated response proportions and Spearman correlation coefficients (r) between (i) incidence of illnesses in Hӓlsorapport and (ii) proportions of specific search terms to medical-advice website and reasons for calling a medical advice hotline. Of 34 748 invitees, 3245 (9·3%) joined the cohort. Participants answered 81% (139 013) of the weekly questionnaires and 90% (16 351) of follow-up questionnaires. AGI incidence correlated with searches on winter-vomiting disease [r = 0·81, 95% confidence interval (CI) 0·69–0·89], and ARI incidence correlated with searches on cough (r = 0·77, 95% CI 0·62–0·86). ILI incidence correlated with the web query-based estimated incidence of ILI patients consulting physicians (r = 0·63, 95% CI 0·42–0·77). The high response to different questionnaires and the correlation with other syndromic surveillance systems suggest that Hӓlsorapport offers a reasonable representation of AGI, ARI and ILI patterns in the community and can complement traditional and syndromic surveillance systems to estimate their burden in the community.

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Pascal Vilain ◽  
Salamta Bah-Assoumani ◽  
Ali-Mohamed Youssouf ◽  
Laurent Filleul

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.


2021 ◽  
Author(s):  
Abigail R Greenleaf ◽  
Gerald Mwima ◽  
Molibeli Lethoko ◽  
Martha Conkling ◽  
George Keefer ◽  
...  

BACKGROUND The increase in cell phone ownership in low- and middle-income countries (LMIC) has created an opportunity for low-cost, rapid data collection by calling participants on their cell phones. Cell phones can be mobilized for a myriad of data collection purposes, including surveillance. In LMIC, cell phone–based surveillance has been used to track Ebola, measles, acute flaccid paralysis, and diarrheal disease, as well as noncommunicable diseases. Phone-based surveillance in LMIC is a particularly pertinent, burgeoning approach in the context of the COVID-19 pandemic. Participatory surveillance via cell phone could allow governments to assess burden of disease and complements existing surveillance systems. OBJECTIVE We describe the protocol for the LeCellPHIA (Lesotho Cell Phone PHIA) project, a cell phone surveillance system that collects weekly population-based data on influenza-like illness (ILI) in Lesotho by calling a representative sample of a recent face-to-face survey. METHODS We established a phone-based surveillance system to collect ILI symptoms from approximately 1700 participants who had participated in a recent face-to-face survey in Lesotho, the Population-based HIV Impact Assessment (PHIA) Survey. Of the 15,267 PHIA participants who were over 18 years old, 11,975 (78.44%) consented to future research and provided a valid phone number. We followed the PHIA sample design and included 342 primary sampling units from 10 districts. We randomly selected 5 households from each primary sampling unit that had an eligible participant and sampled 1 person per household. We oversampled the elderly, as they are more likely to be affected by COVID-19. A 3-day Zoom training was conducted in June 2020 to train LeCellPHIA interviewers. RESULTS The surveillance system launched July 1, 2020, beginning with a 2-week enrollment period followed by weekly calls that will continue until September 30, 2022. Of the 11,975 phone numbers that were in the sample frame, 3020 were sampled, and 1778 were enrolled. CONCLUSIONS The surveillance system will track COVID-19 in a resource-limited setting. The novel approach of a weekly cell phone–based surveillance system can be used to track other health outcomes, and this protocol provides information about how to implement such a system. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/31236


2017 ◽  
Vol 32 (6) ◽  
pp. 667-672 ◽  
Author(s):  
Dan Todkill ◽  
Paul Loveridge ◽  
Alex J. Elliot ◽  
Roger A. Morbey ◽  
Obaghe Edeghere ◽  
...  

AbstractIntroductionThe Public Health England (PHE; United Kingdom) Real-Time Syndromic Surveillance Team (ReSST) currently operates four national syndromic surveillance systems, including an emergency department system. A system based on ambulance data might provide an additional measure of the “severe” end of the clinical disease spectrum. This report describes the findings and lessons learned from the development and preliminary assessment of a pilot syndromic surveillance system using ambulance data from the West Midlands (WM) region in England.Hypothesis/ProblemIs an Ambulance Data Syndromic Surveillance System (ADSSS) feasible and of utility in enhancing the existing suite of PHE syndromic surveillance systems?MethodsAn ADSSS was designed, implemented, and a pilot conducted from September 1, 2015 through March 1, 2016. Surveillance cases were defined as calls to the West Midlands Ambulance Service (WMAS) regarding patients who were assigned any of 11 specified chief presenting complaints (CPCs) during the pilot period. The WMAS collected anonymized data on cases and transferred the dataset daily to ReSST, which contained anonymized information on patients’ demographics, partial postcode of patients’ location, and CPC. The 11 CPCs covered a broad range of syndromes. The dataset was analyzed descriptively each week to determine trends and key epidemiological characteristics of patients, and an automated statistical algorithm was employed daily to detect higher than expected number of calls. A preliminary assessment was undertaken to assess the feasibility, utility (including quality of key indicators), and timeliness of the system for syndromic surveillance purposes. Lessons learned and challenges were identified and recorded during the design and implementation of the system.ResultsThe pilot ADSSS collected 207,331 records of individual ambulance calls (daily mean=1,133; range=923-1,350). The ADSSS was found to be timely in detecting seasonal changes in patterns of respiratory infections and increases in case numbers during seasonal events.ConclusionsFurther validation is necessary; however, the findings from the assessment of the pilot ADSSS suggest that selected, but not all, ambulance indicators appear to have some utility for syndromic surveillance purposes in England. There are certain challenges that need to be addressed when designing and implementing similar systems.TodkillD, LoveridgeP, ElliotAJ, MorbeyRA, EdeghereO, Rayment-BishopT, Rayment-BishopC, ThornesJE, SmithG. Utility of ambulance data for real-time syndromic surveillance: a pilot in the West Midlands region, United Kingdom. Prehosp Disaster Med. 2017;32(6):667–672.


Author(s):  
Lisa Lix ◽  
James Ayles ◽  
Sharon Bartholomew ◽  
Charmaine Cooke ◽  
Joellyn Ellison ◽  
...  

Chronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageous because it does not require individual-level data to be shared across jurisdictional boundaries. Our objective is to describe the process, structure, benefits, and challenges of a distributed model for chronic disease surveillance across all Canadian provinces and territories (P/Ts) using linked administrative data. The Public Health Agency of Canada (PHAC) established the Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to facilitate standardized, national estimates of chronic disease prevalence, incidence, and outcomes. The CCDSS primarily relies on linked health insurance registration files, physician billing claims, and hospital discharge abstracts. Standardized case definitions and common analytic protocols are applied to the data for each P/T; aggregate data are shared with PHAC and summarized for reports and open access data initiatives. Advantages of this distributed model include: it uses the rich data resources available in all P/Ts; it supports chronic disease surveillance capacity building in all P/Ts; and changes in surveillance methodology can be easily developed by PHAC and implemented by the P/Ts. However, there are challenges: heterogeneity in administrative databases across jurisdictions and changes in data quality over time threaten the production of standardized disease estimates; a limited set of databases are common to all P/Ts, which hinders potential CCDSS expansion; and there is a need to balance comprehensive reporting with P/T disclosure requirements to protect privacy. The CCDSS distributed model for chronic disease surveillance has been successfully implemented and sustained by PHAC and its P/T partners. Many lessons have been learned about national surveillance involving jurisdictions that are heterogeneous with respect to healthcare databases, expertise and analytical capacity, population characteristics, and priorities.


Author(s):  
Natalie Strobel ◽  
Jenny Bourke ◽  
Helen Leonard ◽  
Alice Richardson ◽  
Karen Edmond ◽  
...  

IntroductionThe IDEA system is a population-based data linkage system for intellectual disability (ID), which combines data from two government departments. Due to recent policy changes the future of the IDEA system is unknown. Understanding the IDEA system's strengths and limitations will provide data custodians with the opportunity to re-design the system. Objectives and ApproachAn evaluation of the IDEA surveillance system was undertaken to assess the quality, efficiency and usefulness of the system. The primary objectives were to evaluate systematically and objectively the attributes of the system and provide recommendations to data custodians and stakeholders to strengthen the surveillance system. The evaluation was based on the methods from the 2001 U.S. Centers for Disease Control and Prevention guidelines on evaluation of public health surveillance systems. We assessed the following system attributes: usefulness, simplicity, flexibility, data quality, acceptability, representativeness, timeliness, and stability. This was completed by process observation, semi-structured interviews and data analysis. ResultsOur results found the IDEA system was flexible, acceptable, representative, timely and stable. Given data linkage process and maintaining confidentiality the data linkage process was considered relatively simple. We compared individuals in the IDEA surveillance system to a sub-group of individuals, cerebral palsy with ID, to the mandatory reporting surveillance system WARDA-CP. There were 582 individuals identified in the WARDA-CP surveillance system as having cerebral palsy and ID. Of those identified 501 (86.1%) were also in the IDEA database and 81 (13.9%) were not. There were little differences in WARDA-CP cases that were not identified in the IDEA system between Indigenous status, sex and place of residence. Conclusion/ImplicationsThe IDEA system has successfully been used to understand prevalence rates and inform resource allocation. Advocacy organisations could play an important role in the sustainability of the system. Additional variables or enhanced surveillance for functional capacity could strengthen the system and provide important information to inform policy and practice.


2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Anne Fouillet ◽  
Cecile Forgeot ◽  
Marie-Michele Thiam ◽  
Celine Caserio-Schonemann

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.


2009 ◽  
Vol 3 (S1) ◽  
pp. S29-S36 ◽  
Author(s):  
Lori Uscher-Pines ◽  
Corey L. Farrell ◽  
Steven M. Babin ◽  
Jacqueline Cattani ◽  
Charlotte A. Gaydos ◽  
...  

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)


2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Heather Rubino ◽  
David Atrubin ◽  
Janet J. Hamilton

ED chief complaint and discharge diagnosis data accessed through a syndromic surveillance system can be used for effective, timely monitoring of RSV hospitalizations in children < 5 years old and may be a more efficient and complete means of monitoring seasonality of RSV activity by region and statewide compared to hospital-based laboratory data reporting. Additionally, this surveillance technique can efficiently monitor RSV activity as well as estimate hospital admissions due to RSV and may be a useful approach for other states with syndromic surveillance systems.


2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Sameh W Boktor ◽  
Kristen Waller ◽  
Lenee Blanton ◽  
Krista Kniss

Objective: Discuss use of syndromic surveillance as a source for the state’s ILI/Influenza surveillanceDiscuss reliability of syndromic data and methods to address problems caused by data outliers and inconsistencies.Introduction: ILINet is a CDC program that has been used for years for influenza-like illness (ILI) surveillance, using a network of outpatient providers who volunteer to track and report weekly the number of visits due to ILI and the total number of visits to their practice. Pennsylvania has a network of 95 providers and urgent care clinics that submit data to ILINet. However, ongoing challenges in recruiting and retaining providers, and inconsistent weekly reporting are barriers to receiving accurate, representative, and timely ILI surveillance data year-round. Syndromic surveillance data have been used to enhance outpatient ILI surveillance in a number of jurisdictions, including Pennsylvania. At present, 156 hospitals, or 90% of all Pennsylvania hospitals with emergency departments (EDs), send chief complaint and other information on their ED visits to the Department of Health’s (PADOH) syndromic surveillance system. PADOH evaluated the consistency and reliability of ILI syndromic data as compared to ILINet data, to confirm that syndromic data were suitable for use in ILINet.Methods: Pennsylvania ILINet data from the past 6 influenza seasons (2011-2012 to 2016-2017, or 314 weeks of data) were downloaded from the CDC’s ILINet website. The statewide weekly percent of visits due to ILI in ILINet was used as the standard for comparisons. For syndromic surveillance, PADOH uses the Epicenter platform hosted by Health Monitoring Systems (HMS); visit-level data are also stored in SAS datasets at PADOH, and HMS forwards a subset of data to the National Syndromic Surveillance System Program. Using syndromic data from the same time period, the proportion of weeks with no syndromic data available was calculated for each facility. A state-developed ILI algorithm (very similar to the 2016 algorithm developed by the ISDS Syndrome Definitions Workgroup) was applied to ED visit chief complaint data to identify visits likely to be due to ILI. The algorithm flags the ER visit as ILI if chief complaint has any combinations of words for flu or fever plus either cough and sore throat or fever and both cough or sore throat . The percent of ED visits due to ILI per the syndromic algorithm (ILIsyn) was calculated for each week by hospital and state-wide. Facility ILIsyn trends were compared to the State level percent ILI data from ILINet by visually examining plots and by calculating Pearson correlation coefficients. Facilities that had >=15 weeks where ILIsyn differed from percent ILI in ILINet by more than 5% were considered to be poorly correlated.Results: A total of 156 hospitals were evaluated in the study. Twenty of the hospitals were excluded because they did not have syndromic data for at least 50% of the weeks in the study period, and an additional 20 were excluded because they had not agreed to have data forwarded to CDC. Of the remaining 116 facilities, individual facility correlation coefficients between ILIsyn and ILINet trends ranged from 0.03 to 0.82 (examples are in Figure 1). Twenty-four hospitals (20.7%) were determined to be poorly correlated. When data from the remaining 92 hospitals were combined, the state ILINet and state-wide ILIsyn trends were strongly correlated statistically and graphically (r=0.82, p <0.0001, Figure 2). Syndromic data from these 92 facilities were deemed acceptable for inclusion in ILINet. Conclusions: Syndromic surveillance data are a valuable source for ILI surveillance. However, evaluation at the hospital-specific level revealed that useful information is not obtained from all facilities. This project demonstrated that validation of data at the facility level is crucial to obtaining reliable and meaningful information. More work is needed to understand which factors distinguish well-correlated from poorly-correlated facilities, and how to improve the quality of information obtained from poorly-correlated facilities.


PEDIATRICS ◽  
1996 ◽  
Vol 98 (2) ◽  
pp. 315-316
Author(s):  
Muin J. Khoury ◽  
Coleen Boyle ◽  
Pierre DeCoufle ◽  
Louise Floyd ◽  
Karen Hymbaughm

We read with great interest the commentary of Aase et al entitled "Do we need the term fetal alcohol effects (FAE)?"1 As a public health agency, the Centers for Disease Control and Prevention (CDC) has been working with states and academic organizations to develop and evaluate prevention programs for fetal alcohol syndrome (FAS). A fundamental component of such programs is the design and implementation of population-based surveillance systems for FAS to track the magnitude of the problem to assess temporal trends related to intervention programs.2,3


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