Data Sharing

It can be difficult to distinguish between truth, half-truth, fiction, and misinformation as we watch the news, read headlines, and scroll through various social media feeds. Fortunately, epidemiologists have the tools needed to serve as a practical resource for colleagues, partners, and communities. The Scrutinizer Challenge is an opportunity for epidemiologists to tackle at least one news story or study a month that is relevant to public health. The goal is that we would do the research necessary to examine data sources and implications of news stories and studies. This process can help us deliver consistent and reliable messages to share with colleagues, partners, and communities. It also provides an opportunity for epidemiologists that practice in different settings to consolidate resources and develop working relationships that may be needed to more thoroughly examine issues.

Objective: Epidemiologists will be better prepared to serve as a practical resource within their communities and spheres of influence by taking the time to examine data sources behind and implications of news stories and studies that are being widely circulated.

Government reporting of notifiable disease data is common and widespread, though most countries do not report in a machine-readable format. This is despite the WHO International Health Regulations stating that [e]ach State Party shall notify WHO, by the most efficient means of communication available. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health. While most nations likely store incident data in a machine-readable format, governments can be hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational. A survey conducted by LANL of notifiable disease data reporting in over fifty countries identified only a few websites that report data in a machine-readable format. The majority (>70%) produce reports as PDF files on a regular basis. The bulk of the PDF reports present data in a structured tabular format, while some report in natural language or graphical charts. The structure and format of PDF reports change often; this adds to the complexity of identifying and parsing the desired data. Not all websites publish in English, and it is common to find typos and clerical errors. LANL has developed a tool, Epi Archive, to collect global notifiable disease data automatically and continuously and make it uniform and readily accessible.

Objective: Automatically collect and synthesize global notifiable disease data and make it available to humans and computers. Provide the data on the web and within the Biosurveillance Ecosystem (BSVE) as a novel data stream. These data have many applications including improving the prediction and early warning of disease events.

Tennessee has experienced an increase of fatal and non-fatal drug overdoses which has been almost entirely driven by the opioid epidemic. Increased awareness by medical professionals, new legislation surrounding prescribing practices, and mandatory use of the state's prescription drug monitoring program has resulted in a decrease of opioid prescriptions and dosages. Paradoxically, emergency department discharges and inpatient hospitalizations due to opioid overdoses have continued to increase. The Tennessee Department of Health, Office of Informatics and Analytics (TDH OIA) has developed visualizations and reports for opioid overdose surveillance data to enhance communication and timely response by health partners. Through opioid overdose surveillance reporting data briefs we aim to focus not on big data analytics, but rather meaningfully targeted data briefs that illustrate mindful data points and visualizations. These data briefs provide information that is actionable to support decision making across the spectrum of partners involved in responding to Tennessee's opioid epidemic.

Objective: Through opioid overdose surveillance data briefs, we aim to focus on creating meaningful targeted reports that incorporate mindful data points and visualizations for diverse audiences. Data briefs provide information that is actionable to support decision making across the spectrum of partners involved in responding to Tennessee's opioid epidemic. Additionally, visualizations and reporting of opioid overdose surveillance data create pathways and processes for sharing data and opportunities to collaborate with others expertise that enrich communication among multi agency collaborators and interdepartmental partners.

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.

In 2014, CDC started receiving an increase in reports of children in the United States with unexplained limb weakness or paralysis (120 total cases). These children were later confirmed by neurology experts to have a rare condition called acute flaccid myelitis (AFM). The Council of State and Territorial Epidemiologists created a standardized case definition for AFM in 2015, allowing CDC to establish standardized surveillance to monitor AFM, determine possible causes and risk factors, and attempt to estimate the baseline incidence. Through this surveillance, CDC identified another increase in AFM cases in 2016 (149 total cases), and obtained valuable information on the clinical presentation to help characterize this illness and the epidemiology of AFM. However, despite the ongoing investigation, many questions still remain about AFM, including why the increases occurred and what has caused most of the AFM cases. The lack of AFM knowledge has made preventing AFM, finding effective treatments for patients, and developing communication messages challenging.

Objective: To assess the type, tone, consistency, and accuracy of communications surrounding a rare polio-like condition called acute flaccid myelitis between 2014-2017 from from CDC, other health agencies, researchers, news media outlets, and the public.

There is a significant body of literature on the use of social media for monitoring ailments such as influenza-like illness1 and cholera,2 as well as public opinions on topics such as vaccination.3 In general, these studies have shown that social media correlates well with official data sources,1,2,3 with the trends identifiable before official data are available.2 However, less is known about the impact of integrating social media into public health practice, and resulting interventions. Therefore, the ISDS Social Media for Disease Surveillance Workgroup initiated a systematic literature review on the use of social media for actionable biosurveillance.

Objective

The objective of this study is to systematically review the literature on the use of social media for biosurveillance in order to evaluate whether this data source can improve public health practice or community health outcomes.

The Oregon Health Authority (OHA), in collaboration with the Johns Hopkins University Applied Physics Laboratory, implemented a syndromic surveillance system, Oregon ESSENCE. A critical component to developing and growing this statewide system is obtaining buy-in and voluntary participation from hospital Emergency Departments (EDs). This process involves approval at multiple levels within a hospital facility from administration to information technology staff responsible for sending electronic ED data to the Oregon ESSENCE system. Therefore, developing marketing materials that appeal to a wide range of recruitment audiences is a key step in obtaining stakeholder buy-in. OHA adopted the ISDS and CDC syndromic surveillance standards for the public health objective of the Center for Medicaid and Medicare Services (CMS) Meaningful Use Programs. However, Oregon hospitals will not receive financial incentive to participate in Oregon ESSENCE from CMS until 2014 during stage two of Meaningful Use. Consequently, this project's early years will focus on obtaining voluntary participation from hospitals.

Objective

Encourage hospitals to participate in OHA emergency department syndromic surveillance system, Oregon ESSENCE.

Cross-jurisdictional sharing of public health syndrome data is useful for many reasons, among them to provide a larger regional or national view of activity and to determine if unusual activity observed in one jurisdiction is atypical. Considerable barriers to sharing of public health data exist, including maintaining control of potentially sensitive data and having informatics systems available to take and view data. The Distribute project [1,2] has successfully enabled cross-jurisdictional sharing of ILI syndrome data through a community of practice approach to facilitate control and trust, and a distributed informatics solution. The Gossamer system [3] incorporates methods used in several UW projects including Distribute. Gossamer has been designed in a modular fashion to be hosted using virtual or physical machines, including inside cloud environments. Two modules of the Gossamer system are designed for aggregate data sharing, and provide a subset of the Distribute functionality. The Distribute and Gossamer systems have been used for ad-hoc sharing in three different contexts; sharing of common ILI data for research into syndrome standardization, sharing syndromic data for specific events (2010 Olympics) and for pilot regional sharing of respiratory lab results. Two additional projects are underway to share specific syndromes of recent interest: alcohol related and heat related ED visits.

Objective

To demonstrate how rapid adhoc sharing of surveillance data can be achieved through informatics methods developed for the Distribute project.