scholarly journals “That was then, this is now” improving public health syndromic surveillance baselines

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Roger Morbey ◽  
Alex J. Elliot ◽  
Paul Loveridge ◽  
Helen Hughes ◽  
Sally Harcourt ◽  
...  
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Syndromic Surveillance ◽  
Regression Models ◽  
Major Change ◽  
Surveillance Systems ◽  
Care Activity ◽  
Working Practices ◽  
Available Information ◽  
Traditional Surveillance

ObjectiveTo improve the ability of syndromic surveillance systems to detectunusual events.IntroductionSyndromic surveillance systems are used by Public Health England(PHE) to detect changes in health care activity that are indicative ofpotential threats to public health. By providing early warning andsituational awareness, these systems play a key role in supportinginfectious disease surveillance programmes, decision making andsupporting public health interventions.In order to improve the identification ofunusualactivity, wecreated new baselines to modelseasonally expectedactivity inthe absence of outbreaks or other incidents. Although historicaldata could be used to model seasonality, changes due to publichealth interventions or working practices affected comparability.Specific examples of these changes included a major change in theway telehealth services were provided in England and the rotavirusvaccination programme introduced in July 2013 that changed theseasonality of gastrointestinal consultations. Therefore, we needed toincorporate these temporal changes in our baselines.MethodsWe used negative binominal regression to model daily syndromicsurveillance, allowing for day of week and public holiday effects.To account for step changes in data caused by changes in healthcaresystem working practices or public health interventions we introducedspecific independent variables into the models. Finally, we smoothedthe regression models to provide short term forecasts of expectedtrends.The new baselines were applied to PHE’s four syndromicsurveillance systems for daily surveillance and public-facing weeklybulletins.ResultsWe replaced traditional surveillance baselines (based on simpleaverages of historical data) with the regression models for dailysurveillance of 53 syndromes across four syndromic surveillancesystems. The improved models captured current seasonal trends andmore closely reflected actual data outside of outbreaks.ConclusionsSyndromic surveillance baselines provide context forepidemiologists to make decisions about seasonal disease activity andemerging public health threats. The improved baselines developedhere showed whether current activity was consistent with expectedactivity, given all available information, and improved interpretationwhen trends diverged from expectations.

scholarly journals Emergency department syndromic surveillance systems: a systematic review

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Helen E. Hughes ◽  
Obaghe Edeghere ◽  
Sarah J. O’Brien ◽  
Roberto Vivancos ◽  
Alex J. Elliot
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Disease Surveillance ◽  
Syndromic Surveillance ◽  
Best Practice ◽  
Public Health Practice ◽  
Healthcare Services ◽  
Urgent Care ◽  
Severe Illness ◽  
Surveillance Systems

Abstract Background Syndromic surveillance provides public health intelligence to aid in early warning and monitoring of public health impacts (e.g. seasonal influenza), or reassurance when an impact has not occurred. Using information collected during routine patient care, syndromic surveillance can be based on signs/symptoms/preliminary diagnoses. This approach makes syndromic surveillance much timelier than surveillance requiring laboratory confirmed diagnoses. The provision of healthcare services and patient access to them varies globally. However, emergency departments (EDs) exist worldwide, providing unscheduled urgent care to people in acute need. This provision of care makes ED syndromic surveillance (EDSyS) a potentially valuable tool for public health surveillance internationally. The objective of this study was to identify and describe the key characteristics of EDSyS systems that have been established and used globally. Methods We systematically reviewed studies published in peer review journals and presented at International Society of Infectious Disease Surveillance conferences (up to and including 2017) to identify EDSyS systems which have been created and used for public health purposes. Search criteria developed to identify “emergency department” and “syndromic surveillance” were applied to NICE healthcare, Global Health and Scopus databases. Results In total, 559 studies were identified as eligible for inclusion in the review, comprising 136 journal articles and 423 conference abstracts/papers. From these studies we identified 115 EDSyS systems in 15 different countries/territories across North America, Europe, Asia and Australasia. Systems ranged from local surveillance based on a single ED, to comprehensive national systems. National EDSyS systems were identified in 8 countries/territories: 2 reported inclusion of ≥85% of ED visits nationally (France and Taiwan). Conclusions EDSyS provides a valuable tool for the identification and monitoring of trends in severe illness. Technological advances, particularly in the emergency care patient record, have enabled the evolution of EDSyS over time. EDSyS reporting has become closer to ‘real-time’, with automated, secure electronic extraction and analysis possible on a daily, or more frequent basis. The dissemination of methods employed and evidence of successful application to public health practice should be encouraged to support learning from best practice, enabling future improvement, harmonisation and collaboration between systems in future. Prospero number CRD42017069150.

Integrating technology and data in public health disease surveillance in Africa: case study of the AVADAR program (Preprint)

2021 ◽  
Author(s):  
Chinedu Ejike Anarado ◽  
Loveth Metiboba ◽  
Faye Simmonds ◽  
Tope Falodun
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Data Gathering ◽  
Sub Saharan Africa ◽  
Surveillance Systems ◽  
Wild Poliovirus ◽  
Timely Response ◽  
Sub Saharan ◽  
Traditional Surveillance

BACKGROUND Sub-saharan Africa, Afghanistan and Pakistan are the last frontiers with the prevalence of wild poliovirus (WPV). Following joint efforts and partnerships some of which were instituted in the last 20 years, Africa was declared free of WPV in August 2020. While efforts now focus on eliminating circulating vaccine derived poliovirus (cVDPV), it is important to review some of the interventions that resulted in a polio-free certification for the continent. OBJECTIVE The Auto-visual AFP detection and response (AVADAR) program was one of such interventions. AVADAR helped with a more focused, technology and data driven campaign, to ensure that surveillance was broad, inclusive, and responsive. With the infusion of mobile health technology, the project became a success as it reported, investigated and confirmed more cases of AFP compared to the existing traditional surveillance systems. This study attempts a review of the AVADAR intervention with a view to understand the role played by technology and data. METHODS This study comparatively reviewed the data generated over a three year period, across nine countries where the AVADAR project was implemented. It sought to understand how AVADAR was an improvement over traditional surveillance systems. RESULTS The AVADAR program confirmed more reported AFP cases, when compared with the traditional (paper-based) system. It was found that more true AFP cases were found through the AVADAR system. AVADAR accounted for 76% of cases reported across eight countries. CONCLUSIONS Evidently, data and technology - in this case - the AVADAR tool, addressed most of the challenges of Public Health Surveillance in the target countries. The challenge of erratic surveillance data gathering, and feedback was reduced as the AVADAR program demonstrated coordinated data gathering, active case search, timely response to alerts, and ultimately, improved confirmation of true cases. It contributes lessons that could be useful in enhancing surveillance systems across the developing world particularly in Africa.

scholarly journals Updating syndromic surveillance baselines following public health interventions

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Andre Charlett ◽  
Sally Harcourt ◽  
Gillian Smith
Keyword(s):  
Public Health ◽  
Syndromic Surveillance ◽  
Regression Models ◽  
Step Change ◽  
Health Interventions ◽  
Model Fit ◽  
Surveillance Systems ◽  
Rotavirus Vaccine ◽  
Public Health Interventions ◽  
Post Intervention

ObjectiveTo adjust modelled baselines used for syndromic surveillance to account for public health interventions. Specifically to account for a change in the seasonality of diarrhoea and vomiting indicators following the introduction of a rotavirus vaccine in England.IntroductionPublic Health England's syndromic surveillance service monitor presentations for gastrointestinal illness to detect increases in health care seeking behaviour driven by infectious gastrointestinal disease. We use regression models to create baselines for expected activity and then identify any periods of signficant increases. The introduction of a rotavirus vaccine in England during July 2013 (Bawa, Z. et al. 2015) led to a reduction in incidence of the disease, requiring a readjustment of baselines.MethodsWe identified syndromes where rates had dropped significantly following the vaccine’s introduction. For these indicators, we introduced new variables into the regression models used to create baselines. Specifically we tested for a ‘step-change’ drop in rates and a change in the seasonality of baselines. Finally we checked the new models accuracy against actual syndromic data before and after the vaccine introduction.ResultsWe were able to improve model fit post-intervention, with the best-fitting models based on a change in seasonality. All post-intervention regression models had reduced average residual square error. Reductions in residual errors ranged from <1% to 60% when a ‘step-change’ variable was included and 4% to 75% when accounting for seasonality. Furthermore, every syndrome showed a better model fit when a change in seasonality was included.ConclusionsPrior to the vaccine’s introduction, rotavirus caused a spring-time peak in vomiting and diarrhoea recorded by syndromic surveillance systems. Failure to account for the reduction in this peak post-vaccine would have made surveillance systems less effective. In particular, any increased activity during spring may have been undetected. Moreover, models that did not account for changes in seasonality would increase the chances of false alarms during other seasons. By adjusting our baselines for the changes in seasonality due to the vaccine we were able to maintain effective surveillance systems.ReferencesBawa, Z., et al. Assessing the Likely Impact of a Rotavirus Vaccination Program in England: The Contribution of Syndromic Surveillance. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2015;61(1):77-85.

scholarly journals Developing Syndromic Surveillance to Monitor and Respond to Adverse Health Events Related to Psychoactive Substance Use: Methods and Applications

2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 65S-72S ◽  
Author(s):  
Michelle L. Nolan ◽  
Hillary V. Kunins ◽  
Ramona Lall ◽  
Denise Paone
Keyword(s):  
Public Health ◽  
New York ◽  
New York City ◽  
York City ◽  
Syndromic Surveillance ◽  
Psychoactive Drug ◽  
Surveillance Systems ◽  
Chief Complaints ◽  
Level Information ◽  
Ed Visits

Introduction: Recent increases in drug overdose deaths, both in New York City and nationally, highlight the need for timely data on psychoactive drug-related morbidity. We developed drug syndrome definitions for syndromic surveillance to monitor drug-related emergency department (ED) visits in real time. Materials and Methods: We used 2012 archived syndromic surveillance data from New York City hospitals to develop definitions for psychoactive drug-related syndromes. The dataset contained ED visit-level information that included patients’ chief complaints, dates of visits, ZIP codes of residence, discharge diagnoses, and dispositions. After manually reviewing chief complaints, we developed a classification scheme comprising 3 categories (overdose, drug mention, and drug abuse/misuse), which we used to define 25 psychoactive drug syndromes. From July 2013 through December 2015, the New York City Department of Health and Mental Hygiene performed daily syndromic surveillance of psychoactive drug-related ED visits using the 25 syndrome definitions. Results: Syndromic surveillance triggered 4 public health investigations, supported 8 other public health investigations that had been triggered by other mechanisms, and resulted in the identification of 5 psychoactive drug-related outbreaks. Syndromic surveillance also identified a substantial increase in synthetic cannabinoid-related visits (from an average of 3 per week in January 2014 to >300 per week in July 2015) and an increase in heroin overdose visits (from 80 to 171 in the first 3 quarters of 2012 and 2014, respectively) in a single neighborhood. Practice Implications: Syndromic surveillance using these novel definitions enabled monitoring of trends in psychoactive drug-related morbidity, initiation and support of public health investigations, and targeting of interventions. Health departments can refine these definitions for their jurisdictions using the described methods and integrate them into existing syndromic surveillance systems.

scholarly journals How Should We Be Conducting Routine Analysis of Traditional Emergency Department Syndromic Surveillance Data?

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
David Atrubin ◽  
Michael Wiese
Keyword(s):  
Emergency Department ◽  
Best Practices ◽  
International Society ◽  
Disease Surveillance ◽  
Syndromic Surveillance ◽  
Surveillance Data ◽  
Outbreak Detection ◽  
Surveillance Systems ◽  
Track Record ◽  
Periodic Disease

This roundtable will focus on how traditional emergency department syndromic surveillance systems should be used to conduct daily or periodic disease surveillance.  As outbreak detection using these systems has demonstrated an equivocal track record, epidemiologists have sought out other interesting uses for these systems.  Over the numerous years of the International Society for Disease Surveillance (ISDS) Conference, many of these studies have been presented; however, there has been a dearth of discussion related to how these systems should be used. This roundtable offers a forum to discuss best practices for the routine use of emergency department syndromic surveillance data.

scholarly journals Avian Flu, Ebola, MERS, and Other Emerging Challenges for Influenza Surveillance Practitioners

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Alan Siniscalchi ◽  
Brooke Evans
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Ebola Virus ◽  
Virus Disease ◽  
Cost Effective ◽  
Emerging Diseases ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Public Health Agencies ◽  
Public Health Practitioners

Public health agencies strive to develop and maintain cost-effective disease surveillance systems to better understand the burden of disease within their jurisdiction. The emergence of novel avian influenza and other respiratory viruses such as MERS-CoV along with other emerging diseases including Ebola virus disease offer new challenges to public health practitioners. The authors conducted a series of surveys of influenza surveillance coordinators to identify and define these challenges. The results emphasize the importance of maintaining sufficient infrastructure and the trained personnel needed to operate these surveillance systems for optimal disease detection and public health preparedness and response readiness.

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