scholarly journals Utility of a Syndromic Surveillance System to Identify Disease Outbreaks with Reportable Disease Data

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Carrie Eggers ◽  
Janet Hamilton ◽  
Richard Hopkins

The sensitivity and predictive value of a surveillance system (ESSENCE-FL) originally designed for syndromic data to identify possible outbreak activity using data from a reportable disease system was examined.  ESSENCE-FL-generated alerts were compared with confirmed outbreak activity for different infectious diseases over a 52-week period.  Results showed that although overall sensitivity of the system to detect outbreak activity was fairly low, the positive predictive value was relatively high.  This evaluation concludes that the application of reportable disease data within the ESSENCE-FL syndromic surveillance system is useful for prompting users of possible outbreak activity that warrants further inquiry.

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Changming Zhou ◽  
Huijian Cheng ◽  
Genming Zhao ◽  
Qi Zhao ◽  
Biao Xu ◽  
...  

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.


2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 40S-47S ◽  
Author(s):  
Laurel Harduar Morano ◽  
Anna E. Waller

Objectives: To improve heat-related illness surveillance, we evaluated and refined North Carolina’s heat syndrome case definition. Methods: We analyzed North Carolina emergency department (ED) visits during 2012-2014. We evaluated the current heat syndrome case definition (ie, keywords in chief complaint/triage notes or International Classification of Diseases, Ninth Revision, Clinical Modification [ ICD-9-CM] codes) and additional heat-related inclusion and exclusion keywords. We calculated the positive predictive value and sensitivity of keyword-identified ED visits and manually reviewed ED visits to identify true positives and false positives. Results: The current heat syndrome case definition identified 8928 ED visits; additional inclusion keywords identified another 598 ED visits. Of 4006 keyword-identified ED visits, 3216 (80.3%) were captured by 4 phrases: “heat ex” (n = 1674, 41.8%), “overheat” (n = 646, 16.1%), “too hot” (n = 594, 14.8%), and “heatstroke” (n = 302, 7.5%). Among the 267 ED visits identified by keyword only, a burn diagnosis or the following keywords resulted in a false-positive rate >95%: “burn,” “grease,” “liquid,” “oil,” “radiator,” “antifreeze,” “hot tub,” “hot spring,” and “sauna.” After applying the revised inclusion and exclusion criteria, we identified 9132 heat-related ED visits: 2157 by keyword only, 5493 by ICD-9-CM code only, and 1482 by both (sensitivity = 27.0%, positive predictive value = 40.7%). Cases identified by keywords were strongly correlated with cases identified by ICD-9-CM codes (rho = .94, P < .001). Conclusions: Revising the heat syndrome case definition through the use of additional inclusion and exclusion criteria substantially improved the accuracy of the surveillance system. Other jurisdictions may benefit from refining their heat syndrome case definition.


2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Sheharyar Minhas

ObjectiveTo prevent and identify gastrointestinal outbreaks due to swimming pools using a two-part surveillance system i) Model Aquatic Health Code (MAHC) Guideline Survey and ii) syndromic surveillanceIntroductionSwimming in contaminated pools can cause gastroenteritis from water contaminated by viruses, bacteria, or parasites. Germs that cause gastroenteritis are shed in feces of infected persons, and easily spread to uninfected persons swimming in pools. Symptoms of gastrointestinal illness can include nausea, vomiting, watery or bloody diarrhea, and weight loss. Common causes of swimming-related gastroenteritis included viruses (norovirus), parasites (giardia, cryptosporidium), and bacteria (Escherichia coli, Shigella). Cryptosporidium is most common agent associated with swimming pool outbreaks. In 2011-2012, public health officials from 32 States reported 90 swimming-pool associated outbreaks to CDC’s Waterborne Disease and Outbreak Surveillance System (WBDOSS). These 90 outbreaks resulted in 1,788 cases, 95 hospitalizations, 1 death. 52% of these outbreaks were caused by Cryptosporidium.MethodsLiterature search was conducted using published peer-reviewed articles via PubMed and Internet websites including, CDC and U.S. consumer product safety commission, Agency for toxic substance and disease registry. Statistical data on GI illness outbreaks associated with swimming pools prevalence and outcomes were also reviewed. Current surveillance methods used for detecting prevalence of waterborne disease outbreaks are based on examples from Ohio and Nebraska to determine approaches and effectiveness of the systems.ResultsSurvey and Education Packet - Distribute a survey with questions about current MAHC guideline adherence and MAHC educational packets that include the incident response guidelines and the water contamination response logStrengths: Low cost, simple, and acceptableLimitations: Not timely event reportingEvent Reporting - Develop a website for reporting contamination events based on the water contamination response logStrengths: Timely reportingLimitations: Complex to setup and maintain, moderate cost, and may not be acceptablePool Inspections - Require pools to undergo periodic inspections to monitor adherence to MAHC guidelinesStrengths: Complete and representativeLimitations: Complex, expensive, not timely event reportingThe current system is based on state reporting to the CDC through the paper-based reporting waterborne disease outbreaks surveillance system (WBDOSS), and the National Outbreak Reporting System (NORS), an electronic reporting system in place since 2009CDC uses waterborne disease outbreak surveillance data too identify the types of etiologic agents, and settings associated with outbreakso evaluate the adequacy of regulations to promote healthy and safe swimmingo establish priorities to improve prevention, guidelines, and regulations at the local, state, and federal levelsThe WBDOSS is not sufficient to capture early detection and reporting of AGI outbreaks. We recommend the these surveillance approaches:Syndromic surveillance of WBD outbreaks to capture early outbreaks of diarrheal, and as many suspected cases as possible in a timely mannerSentinel surveillance at specific healthcare facilities in the proximity of swimming pools where outbreaks can occurActive Lab-based surveillance would offer more robust and complete analysis of the prevalence and incidence of acute GI illness outbreaks in the StateConclusionsOur study concluded that state health department should begin a two-part surveillance system: i) distributing MAHC guideline surveys & education packet; ii) syndromic surveillance system for outbreaks. MAHC Guideline Survey and Education Packet would be cost effective to educate pool operators on current MAHC guidelines and gather baseline data on adherence to MAHC guidelines for responding to contamination events. Afterwards, once baseline data is gathered and awareness of the MAHC guidelines is established, the state health department can determine if event reporting or pool inspections are necessary to increase either the timeliness or representativeness of the surveillance system. Syndromic surveillance would be the most timely and sensitive surveillance system. This is important to achieve health department's goal of early outbreak detection. Both predictive value and data quality are limitations of syndromic surveillance system. Acute gastrointestinal illness is also caused by sources other than pool contamination which can cause false positives.References1-CDC. Protracted Outbreaks of Cryptosporidiosis Associated With Swimming Pool Use --- Ohio and Nebraska, 2000 MMWR 2001; 50(20); 406-410.http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5020a3.htm2-CDC. Outbreaks of Illness Associated with 2-Recreational Water — United States, 2011–2012 MMWR. 64(24); 668-672. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6424a4.htm?s_cid=mm6424a4_w3-CDC. The Model Aquatic Health Code. August 2015. http://www.cdc.gov/mahc/index.htm4-CDC. (n.d.) Decoding the MAHC: The Model Aquatic Health Code. Retrieved from https://www.cdc.gov/healthywater/pdf/swimming/pools/mahc/decoding-the-mahc.pdf5-CDC. (2016). Fecal Incident Response Recommendations for Aquatic Staff. Retrieved from https://www.cdc.gov/healthywater/swimming/pdf/fecal-incident-response-guidelines.pdf6-CDC. (n.d.) Water Contamination Response Log. Retrieved from https://www.cdc.gov/healthywater/pdf/swimming/pools/water-contamination-response-log.pdf7-CDC. (2016). Model Aquatic Health Code Aquatic Facility Inspection Report. Retrieved from https://www.cdc.gov/mahc/pdf/mahc-aquatic-facility-inspection-report.pdf


2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Mariette Hooiveld ◽  
Madelief Mollers ◽  
Stephanie Van Rooden ◽  
Robert A. Verheij ◽  
Susan Hahné

ObjectiveFacing challenges to establish a new national syndromicsurveillance system in the Netherlands for infectious diseases amongasylum seekers.IntroductionMost European countries are facing a continuous increased influxof asylum seekers [1]. Poor living conditions in crowded shelters andrefugee camps increase the risk for - outbreaks of - infectious diseasesin this vulnerable population. In line with ECDC recommendations[2], we aim to improve information on infectious diseases amongasylum seekers by establishing a new syndromic surveillance systemin the Netherlands. This system will complement the notifiabledisease system for infectious diseases.The aim of the syndromic surveillance system is to improve thedetecting of outbreaks of infectious diseases in asylum seekers’centres in an early stage of development to be able to take adequateand timely measures to prevent further spread, and to collectinformation on the burden of infection within this population.MethodsPrimary health care for asylum seekers in the Netherlands isorganized nationally by the Asylum Seekers Health Centre, withgeneral practitioners providing care in each reception centre. Generalpractitioners (GPs) act as gatekeepers for specialized, secondaryhealth care and the GP is the first professional to consult for healthproblems. Therefore, electronic health records (EHR) kept by GPsprovide a complete picture of this population. These EHRs containdata on diagnoses/symptoms and treatment of asylum seekers, usingthe International Classification of Primary Care (ICPC). This data isrecorded routinely, as part of the health care process. During summer2016, about 30,000 asylum seekers were housed in about 60 receptioncentres across the Netherlands.ResultsThe governance structure was layed down in a collaborationagreement between the Asylum Seekers Health Centre, the nationalinstitute of public health RIVM and NIVEL. To ensure privacy ofthe asylum seekers, a privacy protocol has been drawn, taking intoaccount strict privacy regulations in the Netherlands. The informationsystem provider of the health care centre developed an extraction toolthat automatically generates weekly data extracts from the electronichealth records system to a Trusted Third Party (TTP). Beforetransferring the data to NIVEL, the TTP removes directly identifyingpatient information, indirectly identifying information like date ofbirth is replaced by quarter and year, and the personal identificationnumber is replaced by a pseudonym. At NIVEL, all data is storedin a relational database, from which weekly research extracts aregenerated for infectious disease surveillance at RIVM after applyinga second pseudonymisation step (two-way pseudonimisation) [3].First data extracts are being expected mid-October 2016, after whichdata quality will be evaluated. Weekly, or daily, consultations rateswill be calculated based on the number of cases meeting predefineddefinitions, stratified by immigration centre, age group, sex andnationality. Numerators will be based on the number of populationhoused in the immigration centres.ConclusionsWith the cooperation of a national health care centre, providingprimary care to asylum seekers housed at several locations, and theinformation system provider of the health care centre, EHRs can beused for syndromic surveillance, taking into account strict privacyregulations. The new surveillance system will be evaluated after oneyear, focusing on data quality, usefulness, and the added value aboveto the notification of diseases.


Author(s):  
Urania G. Dafni ◽  
S. Tsiodras ◽  
D. Panagiotakos ◽  
K. Gkolfinopoulou ◽  
G. Kouvatscas ◽  
...  

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