Public Health Syndromic Surveillance Research Articles

Is there a relationship between opioid use and transient global amnesia?

Opioid-associated amnestic syndrome (OAS) and transient global amnesia (TGA) are conditions with clinical overlap. We therefore sought to determine whether opioid use might be associated with TGA. Data from the Massachusetts Department of Public Health Syndromic Surveillance program were queried to ascertain the frequency of opioid use among emergency department (ED) encounters for TGA compared to that for all other ED visits between January 2019 and June 2023. A total of 13,188,630 ED visits were identified during the study period. Of 1417 visits for TGA, one visit met the exposure definition for opioid use. There were 13,187,213 visits for other indications, 57,638 of which were considered opioid-exposed. The odds ratio for the relationship between opioid use and TGA was 0.16 (95% confidence interval 0.02, 1.14). Despite the clinical overlap between OAS and TGA, surveillance data from ED visits in Massachusetts do not suggest that opioid use is a risk factor for TGA, indicating that OAS and TGA are distinct entities.

Development and assessment of a hospital admissions-based syndromic surveillance system for COVID-19 in Ontario, Canada: ACES Pandemic Tracker

BackgroundThe COVID-19 pandemic has continued to pose a major global public health risk. The importance of public health surveillance systems to monitor the spread and impact of COVID-19 has been well demonstrated. The purpose of this study was to describe the development and effectiveness of a real-time public health syndromic surveillance system (ACES Pandemic Tracker) as an early warning system and to provide situational awareness in response to the COVID-19 pandemic in Ontario, Canada.MethodsWe used hospital admissions data from the Acute Care Enhanced Surveillance (ACES) system to collect data on pre-defined groupings of symptoms (syndromes of interest; SOI) that may be related to COVID-19 from 131 hospitals across Ontario. To evaluate which SOI for suspected COVID-19 admissions were best correlated with laboratory confirmed admissions, laboratory confirmed COVID-19 hospital admissions data were collected from the Ontario Ministry of Health. Correlations and time-series lag analysis between suspected and confirmed COVID-19 hospital admissions were calculated. Data used for analyses covered the period between March 1, 2020 and September 21, 2020.ResultsBetween March 1, 2020 and September 21, 2020, ACES Pandemic Tracker identified 22,075 suspected COVID-19 hospital admissions (150 per 100,000 population) in Ontario. After correlation analysis, we found laboratory-confirmed hospital admissions for COVID-19 were strongly and significantly correlated with suspected COVID-19 hospital admissions when SOI were included (Spearman’s rho = 0.617) and suspected COVID-19 admissions when SOI were excluded (Spearman’s rho = 0.867). Weak to moderate significant correlations were found among individual SOI. Laboratory confirmed COVID-19 hospital admissions lagged in reporting by 3 days compared with suspected COVID-19 admissions when SOI were excluded.ConclusionsOur results demonstrate the utility of a hospital admissions syndromic surveillance system to monitor and identify potential surges in severe COVID-19 infection within the community in a timely manner and provide situational awareness to inform preventive and preparatory health interventions.

Detection of Hyalomma rufipes in a recently arrived asylum seeker to the EU

The importation of novel tick species to Europe and the emergence of tick-borne diseases have been of rising concern over the last decades. In May 2019, a total of 349 asylum seekers arrived in Malta by boat. Public health syndromic surveillance was conducted on all migrant boat arrivals. The incidental finding of a tick with anomalous morphology in a newly arrived migrant in Malta prompted an epidemiological investigation. Morphological identification of the tick followed by species identification using keys specific to North Africa was conducted and molecular testing for Crimean Congo haemorrhagic fever virus (CCHFV) was performed. Detailed interview and clinical examination of the case were conducted on arrival and follow-up interviews were undertaken 1- and 4-weeks post-arrival.A Hyalomma rufipes tick was identified on the chest of a 28-year-old male from Sudan. The patient reported malaise and headache on arrival. No further symptoms were reported during follow-up. There was no evidence of previous CCHFV infection or the presence of other ticks or pathogens on the patient. The investigation revealed that the H. rufipes tick had likely been acquired in Libya.This is the first report of the presence of a H. rufipes tick, the main vector for CCHFV, on a recently arrived migrant in Europe. This event highlights the importance of increasing awareness on the risk of tick-borne infections among recently arrived migrants in the Mediterranean countries and the need to consider tick screening as part of the health screening offered in the EU.

The characteristics of dockless electric rental scooter-related injuries in a large U.S. city

Objective To describe the characteristics of dockless electric rental scooter ("e-scooter")-related injuries presenting to two emergency departments in one large U.S. city. Methods This observational cohort study utilized the city’s public health syndromic surveillance system to prospectively identify patients with e-scooter-related injuries presenting between September and November 2018. The medical records for all adult patients treated at the two participating emergency departments were manually reviewed to extract demographic and clinical data. Cases involving mobility scooters or non-electric scooters were excluded. Results For the 124 included adult patients with e-scooter-related injuries, the median age was 30 years (IQR: 22-43), they were predominantly male (59.7%), and approximately half (51.6%) arrived by ambulance. Falling from the scooter (84.7%) was the most common mechanism; twelve patients (9.7%) had collided with a motor vehicle. Head and face injuries (45.5%) were common; only 2 patients (1.6%) were documented as wearing a helmet at the time of injury. Most patients (n = 112, 90.3%) required imaging, more than half (n = 78, 62.9%) required an emergency department procedure, and 26 (21.0%) required surgical intervention. Most patients were discharged home, but 35 (28.2%) were admitted to hospital. Two patients (1.6%) were admitted to the intensive care unit. Conclusions E-scooters are an emerging transportation technology associated with a wide range of potentially serious injuries that consume substantial emergency department and hospital resources. Head injuries are a particular concern, as few e-scooter riders are wearing helmets at the time of injury.

Monitoring and Improving Syndromic Surveillance Data Quality

Monitoring and Improving Syndromic Surveillance Data Quality

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

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.

Framework for the Development of Response Protocols for Public Health Syndromic Surveillance Systems: Case Studies of 8 US States

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. 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. 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. 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.

Syndromic surveillance using minimum transfer of identifiable data: the example of the National Bioterrorism Syndromic Surveillance Demonstration Program.

Several health plans and other organizations are collaborating with the Centers for Disease Control and Prevention to develop a syndromic surveillance system with national coverage that includes more than 20 million people. A principal design feature of this system is reliance on daily reporting of counts of individuals with syndromes of interest in specified geographic regions rather than reporting of individual encounter-level information. On request from public health agencies, health plans and telephone triage services provide additional information regarding individuals who are part of apparent clusters of illness. This reporting framework has several advantages, including less sharing of protected health information, less risk that confidential information will be distributed inappropriately, the prospect of better public acceptance, greater acceptance by health plans, and less effort and cost for both health plans and public health agencies. If successful, this system will allow any organization with appropriate data to contribute vital information to public health syndromic surveillance systems while preserving individuals' privacy to the greatest extent possible.