Dashboard

North Carolina hosted the 2018 FEI WEG in Polk County at the Tryon Equestrian Center in September 2018. Polk County, located in the Mountain region of Western North Carolina, is home to 20,357 people, and the population is widely distributed. Event organizers expected approximately 300,000 to 500,000 people to visit the area, with 800 horses from 71 countries taking part in the games. Providing adequate public health epidemiologic investigations and response for the large scale event in the predominantly rural area presented a challenge. The NC Surveillance & Response Team was created to facilitate enhanced surveillance for significant public health events during the WEG, assist local public health agencies with epidemiologic investigations and response, develop public health risk assessments, and implement control measures. Surveillance data were collected from the North Carolina Electronic Disease Surveillance System (NC EDSS), North Carolina’s and CDC’s National syndromic surveillance systems (NC DETECT and NSSP ESSENCE), Public Health Epidemiologists from Atrium Health and Mission Hospital, and reports from the on-site medical facility (MED-1) at the Tryon Equestrian Center. The data were reviewed and summarized in internal and external situation reports.

Objective: To describe surveillance activities and use of existing state (NC DETECT) and national (NSSP) syndromic surveillance systems during the International Federation for Equestrian Sports (FEI) World Equestrian Games (WEG), in Mill Spring, NC from September 11 to September 23, 2018

Data-driven decision-making is a cornerstone of public health emergency response; therefore, a highly-configurable and rapidly deployable data capture system with built-in quality assurance (QA; e.g., completeness, standardization) is critical. Additionally, to keep key stakeholders informed of developments during an emergency, data need to be shared in a timely and effective manner. Dynamic data visualization is a particularly useful means of sharing data with healthcare providers and the public.2 During Spring 2018, detection of canine influenza H3N2 among dogs in NYC caused concern in the veterinary community. Canine influenza is a highly contagious respiratory infection caused by an influenza A virus.3 However, no central database existed in NYC to monitor the outbreak and no single agency was responsible for data capture. Our team at the NYC Department of Health and Mental Hygiene (DOHMH) partnered with the NYC Veterinary Medical Association (VMA) to monitor the canine influenza H3N2 outbreak by building a web-based reporting platform and interactive dashboard.

Objective: The objectives of this project were to rapidly build and deploy a web-based reporting platform in response to a canine influenza H3N2 outbreak in New York City (NYC) and provide aggregate data back to the veterinary community as an interactive dashboard.

The mission of the Infectious-Disease-Epidemiology Department at the Robert Koch Institute is the prevention, detection and control of infections in the German population. For this purpose it has a set of surveillance and outbreak-detection systems in place. Some of these cover a wide range of diseases, e.g. the traditional surveillance of about 80 notifiable diseases, while others are specialised for the timely assessment of only one or a few diseases, e.g. participatory syndromic surveillance of acute respiratory infections. Many different such data sources have to be combined to allow a holistic view of the epidemiological situation. The continuous integration of many heterogeneous data streams into a readily available and accessible product remains a big challenge in infectious-disease epidemiology.

Objective: Providing an integrative tool for public health experts to rapidly assess the epidemiological situation based on data streams from different surveillance systems and relevant external factors, e.g. weather or socio-economic conditions. The efficient implementation in a modular architecture of disease- or task-specific visualisations and interactions, their combination in dashboards and integration in a consistent, general web application. The user-oriented development through an iterative process in close collaboration with epidemiologists.

In 2015, ISDH responded to an HIV outbreak among persons using injection drugs in Scott County [1]. Information to manage the public health response to this event and aftermath included data from multiple sources (e.g., HIV testing, surveillance, contact tracing, medical care, and HIV prevention activities). During the outbreak, access to timely and accurate data for program monitoring and reporting was difficult for health department staff. Each dataset was managed separately and tailored to the relevant HIV program area’s needs. Our challenge was to create a platform that allowed separate systems to communicate with each other and design a DP that offered a consolidated view of data. ISDH initiated efforts to integrate these HIV data sources to better track HIV prevention, diagnosis, and care metrics statewide, support decision-making and policies, and facilitate a more rapid response to future HIV-related investigations. The Centers for Disease Control and Prevention (CDC) through its Info-Aid program provided technical assistance to support ISDH’s data integration process and develop a DP that could aggregate these data and improve reporting of crucial statewide metrics. After an initial assessment phase, an in-depth analysis of requirements resulted in several design principles and lessons learned that later translated into standardization of data formats and design of the data integration process.

Objective: The objective was to design and develop a dashboard prototype (DP) that integrates HIV data from disparate sources to improve monitoring and reporting of HIV care continuum metrics in Indiana. The tool aimed to support Indiana State Department of Health (ISDH) to monitor key HIV performance indicators, more fully understand populations served, more quickly identify and respond to crucial needs, and assist in planning and decision-making.

NC DETECT provides near-real-time statewide surveillance capacity to local, regional and state level users across NC with twice daily data feeds from 117 (99%) emergency departments (EDs), hourly updates from the statewide poison center, and daily feeds from statewide EMS runs and select urgent care centers. The NC DETECT Web Application provides access to aggregate and line listing analyses customized to users' respective jurisdictions. The most active users are state-level epidemiologists (DPH) and hospital-based public health epidemiologists (PHEs). The use of NC DETECT is included in PHE job descriptions and NC DETECT functionality has been developed specifically to meet the surveillance needs of this group, including data entry of aggregated lab results for flu and respiratory panels. Interviews of local health department (LHD) users completed as part of an evaluation project have suggested that functionality specifically tailored to LHDs may increase their use of the NC DETECT Web application [1]. As of June 2011, there were 139 LHD users with active accounts to use the Web application (out of 384 total users with active accounts).

Objective

To describe the development, implementation and preliminary evaluation of new dashboard interfaces in NC DETECT, designed primarily for infrequent users of NC DETECT at local health departments.

Capital Health is a regional health care organization, which provides services for over one million inhabitants in the Edmonton area of Alberta, Canada. Traditionally, disease surveillance under its jurisdiction has been paper-based and records maintained by different departments in several locations. Before the Alberta Real Time Syndromic Surveillance Net (ARTSSN), there was no centralized database or unified approach to surveillance and automated reporting despite rich electronic health data in the region. The existing labor-intensive manual surveillance process is inefficient and inherently susceptible to human error. Its effectiveness is sub-optimal in detecting outbreaks of emerging infectious diseases, and clusters of injuries or toxic exposures. The ultimate objective of ARTSSN is to enhance public health surveillance through earlier and more sensitive detection of clusters and trends, with subsequent tracking and response through an integrated, automated surveillance and reporting system.

Objective

ARTSSN is a pilot public health surveillance project developed for the Capital Health region of Alberta, Canada and funded by Alberta Health and Wellness. This paper describes the advantages of using ARTSSN and comparing information derived from multiple electronic data sources simultaneously for real time syndromic surveillance.