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In 2002, the United States (US) Centers for Disease Control and Prevention (CDC) launched the National Environmental Public Health Tracking Program (Tracking Program) to address the challenges in environmental health surveillance described by the Pew Environmental Commission (1). The report cited gaps in our understanding of how the environment affects our health and attributed these gaps to a dearth of surveillance data for environmental hazards, human exposures, and health effects. The Tracking Program's mission is to provide information from a nationwide network of integrated health and environmental data that drives actions to improve the health of communities. Accomplishing this mission requires a range of expertise from environmental health scientists to programmers to communicators employing the best practices and latest technical advances of their disciplines. Critical to this mission, the Tracking Program must identify and prioritize what data are needed, address any gaps found, and integrate the data into the network for ongoing surveillance.

Objective: To increase the availability and accessibility of standardized environmental health data for public health surveillance and decision-making.

Submitted by elamb on

After the 2009 H1N1 pandemic, the Assistant Secretary of Defense for Nuclear, Chemical and Biological Defense indicated œbiodefense would include emerging infectious disease. In response, DTRA launched an initiative for an innovative, rapidly emerging capability to enable real-time biosurveillance for early warning and course of action analysis. Through competitive prototyping, DTRA selected Digital Infuzion to develop the platform and next generation analytics. This work was extended to enhance collaboration capabilities and to harness data science and advanced analytics for multi-disciplinary surveillance including climate, crop, and animal as well as human data. New analysis tools ensure the BSVE supports a One Health paradigm to best inform public health action. Digital Infuzion and DTRA first introduced the BSVE to the ISDS community at the 2013 annual conference SWAP Meet. Digital Infuzion is pleased to present the mature platform to this community again as it is now a fully developed capability undergoing FedRAMP certification with the Department of Homeland Security's National Biosurveillance Integration Center and Is the basis for Digital Infuzion's HARBINGER ecosystem for biosurveillance.

Objective: While there is a growing torrent of data that disease surveillance could leverage, few effective tools exist to help public health professionals make sense of this data or that provide secure work-sharing and communication. Meanwhile, our ever more-connected world provides an increasingly receptive environment for diseases to emerge and spread rapidly making early warning and collaborative decision-making essential to saving lives and reducing the impact of outbreaks. Digital Infuzion's previous work on the Defense Threat Reduction Agency (DTRA)'s Biosurveillance Ecosystem (BSVE) built a cloud-based platform to ingest big data with analytics to provide users a robust surveillance environment. We next enhanced the BSVE data sources and analytics to support an integrated One Health paradigm. The resulting BSVE and Digital Infuzion's HARBINGER platform include: 1) identifying and ingesting data sources that span global human, animal and crop health; 2) inclusion of non-health data such as travel, weather, and infrastructure; 3) the data science tools, analytics and visualizations to make these data useful and 4) a fully-featured Collaboration Center for secure work-sharing and communication across agencies.

Submitted by elamb on

At the Governor’s Opioid Addiction Crisis Datathon in September 2017, a team of Booz Allen data scientists participated in a two-day hackathon to develop a prototype surveillance system for business users to locate areas of high risk across multiple indicators in the State of Virginia. We addressed 1) how different geographic regions experience the opioid overdose epidemic differently by clustering similar counties by socieconomic indicators, and 2) facilitating better data sharing between health care providers and law enforcement. We believe this inexpensive, open source, surveillance approach could be applied for states across the nation, particularly those with high rates of death due to drug overdoses and those with significant increases in death.

Objective:

A team of data scientists from Booz Allen competed in an opioid hackathon and developed a prototype opioid surveillance system using data science methods. This presentation intends to 1) describe the positives and negatives of our data science approach, 2) demo the prototype applications built, and 3) discuss next steps for local implementation of a similar capability.

Submitted by elamb on

In a context of finite resources, multiple needs and growing demands of organizational accountability, there has been an increase in the number of multi-dimensional prioritization exercises (of diseases, interventions, etc) in the health arena. Not all of them following robust methodologies. The seminar will explore robust techniques for the prioritization of alternatives in health settings.

Many methods to detect outbreaks currently exist, although most are ineffective in the face of real data, resulting in high false positivity. More complicated methods have better precision, but can be difficult to interpret and justify. Praedico™ is a next generation biosurveillance application built on top of a Hadoop High Performance Cluster that incorporates multiple syndromic surveillance methods of alerting, and a machine-learning (ML) model using a decision tree classifier  evaluating over 100 different signals simultaneously, within a user friendly interface.

Objective

To compare syndromic surveillance alerting in VA using Praedico™ and ESSENCE.

Submitted by teresa.hamby@d… on

The basic reproduction number represents the number of secondary infections expected to be caused by an infectious individual introduced into an entirely susceptible population. It is a fundamental measure used to characterize infectious disease outbreaks and is essential in developing mathematical models to determine appropriate interventions. Much work has been done to investigate methods for estimating the basic reproduction number during the early stages of infectious disease outbreaks. However, these methods often require data that may not be readily available at the beginning of an outbreak. An approach developed by Becker has been widely used to estimate the basic reproduction number using only the final case count and size of the at-risk population. A modification to this approach is proposed that allows estimates to be obtained earlier in an outbreak using only the current case count, number currently ill, and the size of the at-risk population.

Objective

To present a modification to an established approach to estimating the basic reproduction number to allow estimates to be obtained at any point during an outbreak using only the current case count, number currently ill, and the size of the at-risk population.

Submitted by teresa.hamby@d… on

Community health assessments are a foundation of public health practice and a prerequisite to achieving public health accreditation. Best practice dictates that CHAs must incorporate qualitative and quantitative data and utilize a number of indicators to create a detailed picture of a community’s health. Metrics may describe demographics, social and economic factors, health behaviors, health outcomes, and healthcare access and utilization. Commonly used indicators facilitate cross-jurisdiction comparisons and simplify decisionmaking. However, while many readily available indicators exist on a county level, few have been made available on the sub-county level. Syndromic surveillance messages, typically emergency room visit records, contain sub-county level data on patient residence, such as zip code or municipality. As hospitals progress towards meeting Stage 2 Meaningful Use requirements, transmission of syndromic surveillance data to public health entities will become standard. Analysis of emergency room visit data, either in aggregate or by specific syndromes, may be a valuable sub-county level indicator of community health status and access to care that can be standardized across jurisdictions.

Objective

To identify geographic clustering of elevated emergency room (ER) usage rates for incorporation into community health assessments (CHA) in suburban Cook County and to validate this metric as a potential sub-county level community health indicator.

Submitted by teresa.hamby@d… on

Pacific Northwest National Laboratory (PNNL), on behalf the Defense Threat Reduction Agency (DTRA; project number CB10190), hosts an annual intern- based web app development contest. Previous competitions have focused on mobile biosurveillance applications. The 2016 competition pivoted away from biosurveillance to focus on addressing challenges within the field of chemical surveillance and increasing public health chemical situational awareness. The result of the app will be integrated within the DTRA BSVE.

Objective

Pacific Northwest National Laboratory hosted an intern-based web application development contest in the summer of 2016 centered around developing novel chemical surveillance applications to aid in health situational awareness. Making up the three teams were three graduate students (n=9) from various US schools majoring in nonpublic health domains, such as computer sicence and user design. The interns successfully developed three applications that demonstrated a value-add to chemical surveillance—ChemAnalyzer (text analytics), RetroSpect (retrospective analysis of chemical events), and ToxicBusters (geo-based trend analytics). These applications will be the basis for the first chemical surveillance application to be incorporated into the DTRA Biosurveillance Ecosystem (BSVE).

Submitted by teresa.hamby@d… on
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