Syndromic Surveillance

Since 1 January 2016, the Auvergne and Rhone-Alpes regions have merged as part of the territorial reform. The new region is composed of 12 departments and accounts for more than 8 million inhabitants. Its territory is heterogeneous in population density with very urban areas (Clermont-Ferrand, Grenoble, Lyon and Saint-Etienne) and important mountainous areas (Arc Alpin, Massif Central). In France since 2004, the syndromic surveillance system SurSaUD® [1] coordinated by the French Public Health Agency (Sant© publique France) collects morbidity data on a daily basis from two data sources: the emergency departments (ED) network Oscour® and the emergency general practitioners SOS Medecins associations. In Auvergne-Rhone-Alpes, the number of structures participating in the scheme has gradually increased from 2006 to today; as of 1 September 2018, all emergency services (N = 84) and all SOS ©decins associations (N = 7) transmit their data on a daily basis. Both data sources collect medical diagnoses, using ICD10 codes in the ED network and specific medical thesaurus in SOS Medecins Associations. These data are routinely analyzed to detect and follow-up various expected or unusual public health events all over the territory [2]. A reflection on the analysis of monitoring data at the sub-regional level was conducted in the region in order to refine the analyses carried out and better meet the expectations of local partners.

Objective: Define analytic areas at a sub-regional level to better meet the needs of local decision-makers.

On August 15, 2018, the Connecticut Department of Public Health (DPH) became aware of a cluster of suspected overdoses in an urban park related to the synthetic cannabinoid K2. Abuse of K2 has been associated with serious adverse effects and overdose clusters have been reported in multiple states. This investigation aimed to characterize the use of syndromic surveillance data to monitor a cluster of suspected overdoses in real time.

Objective: To describe the use of syndromic surveillance data for real-time situational awareness of emergency department utilization during a localized mass overdose event related to the substance K2.

In December 2009, Taiwan’s CDC stopped its sentinel physician surveillance system. Currently, infectious disease surveillance systems in Taiwan rely on not only the national notifiable disease surveillance system but also real-time outbreak and disease surveillance (RODS) from emergency rooms, and the outpatient and hospitalization surveillance system from National Health Insurance data. However, the timeliness of data exchange and the number of monitored syndromic groups are limited. The spatial resolution of monitoring units is also too coarse, at the city level. Those systems can capture the epidemic situation at the nationwide level, but have difficulty reflecting the real epidemic situation in communities in a timely manner. Based on past epidemic experience, daily and small area surveillance can detect early aberrations. In addition, emerging infectious diseases do not have typical symptoms at the early stage of an epidemic. Traditional disease-based reporting systems cannot capture this kind of signal. Therefore, we have set up a clinic-based surveillance system to monitor 23 kinds of syndromic groups. Through longitudinal surveillance and sensitive statistical models, the system can automatically remind medical practitioners of the epidemic situation of different syndromic groups, and will help them remain vigilant to susceptible patients. Local health departments can take action based on aberrations to prevent an epidemic from getting worse and to reduce the severity of the infected cases.

Objective: Sentinel physician surveillance in the communities has played an important role in detecting early aberrations in epidemics. The traditional approach is to ask primary care physicians to actively report some diseases such as influenza-like illness (ILI), and hand, foot, and mouth disease (HFMD) to health authorities on a weekly basis. However, this is labor-intensive and time-consuming work. In this study, we try to set up an automatic sentinel surveillance system to detect 23 syndromic groups in the communites.

During an influenza pandemic, when hospitals and doctors'™ offices are or are perceived to be overwhelmed, many ill people may not seek medical care. People may also avoid medical facilities due to fear of contracting influenza or transmitting it to others. Therefore, syndromic methods for monitoring illness outside of health care settings are important adjuncts to traditional disease reporting. Monitoring absenteeism trends in schools and workplaces provide the archetypal examples for such approaches. NIOSH's early experience with workplace absenteeism surveillance during the 2009 - 2010 H1N1 pandemic established that workplace absenteeism correlates well with the occurrence of influenza-like illness (ILI) and significant increases in absenteeism can signal concomitant peaks in disease activity. It also demonstrated that, while population-based absenteeism surveillance using nationally representative survey data is not as timely, it is more valid and reliable than surveillance based on data from sentinel worksites.1 In 2017, NIOSH implemented population-based, monthly surveillance of health-related workplace absenteeism among full-time workers.

Objective: To describe the methodology of the National Institute for Occupational Safety and Health (NIOSH) system for national surveillance of health-related workplace absenteeism among full-time workers in the United States and to present initial findings from October through July of the 2017 - 2018 influenza season.

Suicide is a growing public health problem in the United States. From 2001 to 2016, ED visit rates for nonfatal self-harm, a common risk factor for suicide, increased 42%. To improve public health surveillance of suicide-related problems, including SI and SA, the Data and Surveillance Task Force within the National Action Alliance for Suicide Prevention recommended the use of real-time data from hospital ED visits. The collection and use of real-time ED visit data on SI and SA could support a more targeted and timely public health response to prevent suicide. Therefore, this investigation aimed to monitor ED visits for SI or SA and to identify temporal, demographic, and geographic patterns using data from CDC's National Syndromic Surveillance Program (NSSP).

Objective: To describe epidemiological characteristics of emergency department (ED) visits related to suicidal ideation (SI) or suicidal attempt (SA) using syndromic surveillance data.

LAC experienced several days of record-breaking temperatures during the summer of 2018. Downtown Los Angeles temperatures soared to 108°F in July with an average daily maximum of 92°F. Extreme heat events such as these can pose major risks to human health. Syndromic surveillance can be a useful tool in providing near real-time surveillance of HRI. In 2014, a working group was formed within the CSTE Climate Change Subcommittee to define and analyze HRI. The workgroup's goal was to provide guidance to public health professionals in adapting and implementing an HRI syndrome surveillance query. The Acute Communicable Disease Control Program's (ACDC) Syndromic Surveillance Unit utilized CSTE's HRI query to provide surveillance during the extreme heat season in 2018 in LAC. Additional modifications to the CSTE query were evaluated for potential improvements towards characterizing HRI trends.

Objective: To analyze Los Angeles County'™s (LAC) extreme heat season in 2018 and evaluate the Council of State and Territorial Epidemiologists' (CSTE) syndrome query for heat-related-illness (HRI) in Los Angeles County (LAC)

The public health problem identified by Alabama Department of Public Health Syndromic Surveillance (AlaSyS) was that the data reflected in the user application of ESSENCE (Electronic Surveillance System for the Early Notification of Community-based Epidemics) was underestimating occurrences of syndromic alerts preventing Alabama Department of Public Health (ADPH) from timely recognition of potential public health threats. Syndromic surveillance (SyS) data in ESSENCE were not reliable for up to a week after the visit date due to slow processing, server downtime, and untimely data submission from the facilities. For AlaSyS, 95 percent of data should be submitted within 24 hours from time of visit, for near real time results. The slow data processing caused latency in the data deeming it less useful for surveillance purposes, consequently the data was not meaningful for daily alerts. For example, if a user ran a report to assess the number of Emergency Department (ED) visits that mentioned heroin in the chief complaint (CC), depending on the status of the data coming from the facility (processing, sending, or offline), the number of visits visible to the user could vary from one to several days. With the opioid epidemic Alabama is currently facing, this delay poses a major public health problem.

Objective: To monitor and improve the data quality captured in syndromic surveillance for Alabama Department of Public Health Syndromic Surveillance (AlaSyS).

Syndromic data is shifting the way surveillance has been done traditionally. Most recently, surveillance has gone beyond city limits and county boundary lines. In southeast Texas, a regional consortium of public health agencies and stakeholders in the 13-County area governs the local ESSENCE system. The Houston Health Department, (HHD) is responsible for deploying ESSENCE to the entire region. To effectively monitor the health of the region's population, a need arose to establish clear guidelines for disease investigation and data sharing triggered by syndromic surveillance across the area. Since Houston's instance of ESSENCE serves all 13 counties, the consortium instituted a cross- jurisdictional etiquette group. The purpose of the group is to determine the standard protocol for responding to ESSENCE alerts and best practices for data sharing and use among consortium members.

Objective: To demonstrate the importance of a cross-jurisdictional etiquette workgroup in the Texas Southeast region that leverages on the Syndromic Surveillance Consortium. To promote data sharing and communicate the findings of disease to assist rapid investigation and data sharing.

In response to the February 2016 Zika virus (ZIKV) outbreak, an inter-agency agreement between the U.S. Centers for Disease Control and Prevention (CDC) and U.S. Agency for International Development (USAID) commissioned further research on the epidemiology, transmission, diagnosis, and birth defects associated with ZIKV. The surveillance and research activities conducted included ecology studies focusing on the transmission dynamics; pregnancy and infant cohort studies to look for birth defects, developmental outcomes and risk factors associated with ZIKV infection; and laboratory studies evaluating the usefulness of multiple Zika diagnostic platforms. These studies were established by either setting up new systems, or leveraging on existing surveillance systems to include ZIKV research specific data elements. Conducted using country-specific protocols, these research systems included key data elements for cross-site analysis. Challenges faced included collection of non-standardized data, differing functional requirements, varying security and confidentiality protocols and limitations of informatics infrastructure. These challenges highlight an opportunity to evaluate and present the informatics-based components necessary to rapidly deploy surveillance and research study activities during a global health emergency situation. We highlight the key challenges and presents strategies for setting up rapid surveillance and research study activities. Additional areas of focus also include system architecture, global partnerships, and workforce development.

Objective: To assess challenges of establishing surveillance and research study systems and present strategies for rapid deployment in global health for the outbreak response.

On September 10, 2017, Irma made landfall in the Florida Keys as a Category 4 hurricane and subsequently tracked up the west side of the state. Due to the size of the storm, it impacted nearly all of Florida. The Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE-FL), the state’s syndromic surveillance system, captures 98% of the emergency department (ED) visits statewide and has historically served a vital function in providing near real-time ED data that are used to track post-disaster morbidity and mortality. After previous hurricanes and tropical storms, increases in carbon monoxide poisonings, animal bites, and injuries have been documented. During post-Irma surveillance, an additional increase in seizure-related ED visits was observed.

Objective: Using Florida's syndromic surveillance data, to describe the increase in seizure activity in the days after Hurricane Irma made landfall in 2017