Skip to main content

Burkom Howard

Description

The ESSENCE demonstration module was built to help DoD health monitors make routine decisions based on disparate evidence sources such as daily counts of ILI-related chief complaints, ratios of positive lab tests for influenza, patient age distribution, and counts of antiviral prescriptions [1]. The module was a population-based (rather than individual-based) Bayesian network (PBN) in that inputs were algorithmic results from these multiple aggregate data streams, and output was the degree of belief that the combined evidence required investigation. The module reduced total alerts substantially and retained sensitivity to the majority of documented outbreaks while clarifying underlying sources of evidence. The current effort was to advance the prototype to production by refining components of the fusion methodology to improve sensitivity while retaining the reduced alert rate.

Objective

The project involves analytic combination of multiple evidence sources to monitor health at hundreds of care facilities. A demonstration module featuring a population-based Bayes Network [1] was refined and expanded for application in the Department of Defense Electronic Surveillance System for Community-Based Epidemics (ESSENCE).

Submitted by uysz on
Description

The ISDS Research Committee (RC) is an interdisciplinary group of researchers interested in various topics related to disease surveillance. The RC hosts a literature review process with a permanent repository of relevant journal articles and bimonthly calls that provide a forum for discussion and author engagement. The calls have led to workgroups and society-wide events, boosted interest in the ISDS Conference, and fostered networking among participants. Since 2007, the RC has identified and classified published articles using an automated search method with the aim of progressing ISDS’s mission of advancing the science and practice of disease surveillance by fostering collaboration and increasing awareness of innovations in the field of surveillance. The RC literature review efforts have provided an opportunity for interprofessional collaboration and have resulted in a repository of over 1,000 articles, but feedback from ISDS members indicated relevant articles were not captured by the existing methodology. The method of automated literature retrieval was thus refined to improve efficiency and inclusiveness of stakeholder interests.

 Objective

To improve the method of automated retrieval of surveillance-related literature from a wide range of indexed repositories.

Submitted by uysz on
Description

Temporal alerting algorithms commonly used in syndromic surveillance systems are often adjusted for data features such as cyclic behavior but are subject to overfitting or misspecification errors when applied indiscriminately. In a project for the Armed Forces Health Surveillance Center to enable multivariate decision support, we obtained 4.5 years of outpatient, prescription and laboratory test records from all US military treatment facilities. A proof-of-concept project phase produced 16 events with multiple evidence corroboration for comparison of alerting algorithms for detection performance. We used the representative streams from each data source to compare sensitivity of 6 algorithms to injected spikes, and we used all data streams from 16 known events to compare them for detection timeliness.

Objective

For a multi-source decision support application, we sought to match univariate alerting algorithms to surveillance data types to optimize detection performance.

Submitted by uysz on
Description

The Joint VA/DoD BioSurveillance System for Emerging Biological Threats project seeks to improve situational awareness of the health of VA/DoD populations by combining their respective data. Each system uses a version of the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE); a combined version is being tested. The current effort investigated combining the datasets for disease cluster detection. We compared results of retrospective cluster detection studies using both separate and joined data. — Does combining datasets worsen the rate of background cluster determination?

— Does combining mask clusters detected on the separate datasets?

— Does combining find clusters that the separate datasets alone would miss?

Objective:

We examined the utility of combining surveillance data from the Departments of Defense (DoD) and Veterans Affairs (VA) for spatial cluster detection.

 

Submitted by Magou on
Description

Twelve years into the 21st century, after publication of hundreds of articles and establishment of numerous biosurveillance systems worldwide, there is no agreement among the disease surveillance community on most effective technical methods for public health data monitoring. Potential utility of such methods includes timely anomaly detection, threat corroboration and characterization, follow-up analysis such as case linkage and contact tracing, and alternative uses such as providing supplementary information to clinicians and policy makers. Several factors have impeded establishment of analytical conventions. As immediate owners of the surveillance problem, public health practitioners are overwhelmed and understaffed. Goals and resources differ widely among monitoring institutions, and they do not speak with a single voice. Limited funding opportunities have not been sufficient for cross-disciplinary collaboration driven by these practitioners. Most academics with the expertise and luxury of method development cannot access surveillance data. Lack of data access is a formidable obstacle to developers and has caused talented statisticians, data miners, and other analysts to abandon the field. The result is that older research is neglected and repeated, literature is flooded with papers of varying utility, and the decision-maker seeking realistic solutions without detailed technical knowledge faces a difficult task. Regarding conventions, the disease surveillance community can learn from older, more established disciplines, but it also poses some unique challenges. The general problem is that disease surveillance lies on the fringe of disparate fields (biostatistics, statistical process control, data mining, and others), and poses problems that do not adequately fit conventional approaches in these disciplines. In its eighth year, the International Society of Disease Surveillance is well positioned to address the standardization problem because its membership represents the involved stakeholders including progressive programs worldwide as well as resource-limited settings, and also because best practices in disease surveillance is fundamental to its mission. The proposed panel is intended to discuss how an effective, sustainable technical conventions group might be maintained and how it could support stakeholder institutions.

Objective

The panel will present the problem of standardizing analytic methods for public health disease surveillance, enumerate goals and constraints of various stakeholders, and present a straw-man framework for a conventions group.

 

Submitted by Magou on
Description

The Johns Hopkins University Applied Physics Laboratory is collaborating with epidemiologists of the US Dept. of Agriculture's Animal and Plant Health Inspection Service (APHIS) Center for Epidemiology and Animal Health (CEAH) to increase animal health surveillance capacity. CEAH monitors selected syndromic animal health indicators for stakeholder reporting. This project’s goal was to extend this capacity to bovine veterinary laboratory test accession data.

Objective:

Standardize selection of indicator data streams and corresponding alerting algorithms for syndromic, reportable disease, and confirmed diagnostic categories derived from veterinary laboratory test order data for bovines.

Submitted by elamb on
Description

An objective of the Joint VA/DoD BioSurveillance System for Emerging Biological Threats project is to improve situational awareness of the health of combined VA and DoD populations. DoD and VA both use versions of the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE). With a retrospective outpatient data collection available, we analyzed relative coverage and timeliness of the two systems to understand potential benefits of a joint system.

Objective

We determined the utility and effective methodology for combin- ing patient record information from the Departments of Veterans Af- fairs (VA) and Defense (DoD) health surveillance systems. 

Submitted by jababrad@indiana.edu on
Description

Each year, influenza affects approximately 5-20% of the United States population causing over 200,000 hospitalizations and 3,000 – 49,000 death. As a key point of entry to the health care system, EDs are responsible for the initial management and treatment of a substantial proportion of these influenza patients, thus directly impacting overall public health. As the front line of influenza diagnosis and treatment, ED providers may benefit from real-time easily shared influenza surveillance information.

Objective

To evaluate the utility and acceptability of a real-time cloud based influenza surveillance tool amongst emergency department (ED) providers.

Submitted by teresa.hamby@d… on
Description

Previous studies have demonstrated the benefit of laboratory surveillance and its capability to accurately detect influenza outbreaks earlier than syndromic surveillance. Current laboratory surveillance has an approximate 2-week lag due to laboratory test turn–around time and data collection. In order to provide real-time access to aggregated test results, we utilized direct cloud connectivity with a rapid PCR-based influenza test, Xpert Flu, to centrally consolidate test results along with GIS data. On-site, type-specific results were available to physicians and uploaded for public health awareness within 100 minutes of patient nasopharyngeal swab.

Objective

To demonstrate the feasibility and validity of a novel electronic surveillance system utilizing a cloud-based interface that consolidates laboratory test results and geographical information in real-time.

Submitted by teresa.hamby@d… on
Description

To identify the disciplines and journal titles of surveillance-related publications from a wide range of indexed repositories and to draw attention to the publication repository created by the ISDS Research Committee.

Introduction

The ISDS Research Committee (RC) is an interdisciplinary group of researchers interested in a wide range of topics related to disease surveillance. The RC hosts a literature review process that results in a permanent repository1 of relevant journal articles; some of which are presented in bi-monthly calls/webinars that provide a forum for discussion and author engagement.2 The webinars have led to workgroups and society-wide events, boosted interest in ISDS, the annual conference, and fostered networking among members and guests. Since 2007, the RC has identified and classified published articles using an automated search method with the aim of progressing ISDS’s mission of advancing the science and practice of disease surveillance by fostering collaboration and increasing awareness of current advances in the field of surveillance. In 2012 the RC refined the method of automated literature retrieval resulting in increases in relevant articles identified. The RC literature review efforts have provided an opportunity for interdisciplinary collaboration and have resulted in a repository of 1920 articles from March 2012-August 2014 (2012=37.4% of articles in the repository, 2013=35.1%, 2014=27.5%).

 

Submitted by aising on