scholarly journals Novel Analysis and Visualization of Chemical Events for Public Health Surveillance

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Michael J. Henry ◽  
Lauren Charles-Smith ◽  
Kyungsik Han ◽  
Courtney D. Corley
Keyword(s):  
Public Health ◽  
Situational Awareness ◽  
National Laboratory ◽  
Data Sources ◽  
Northwest National Laboratory ◽  
Application Development ◽  
App Development ◽  
Web App ◽  
Chemical Events ◽  
Chemical Event

ObjectivePacific Northwest National Laboratory hosted an intern-basedweb application development contest in the summer of 2016 centeredaround developing novel chemical surveillance applications to aid inhealth situational awareness. Making up the three teams were threegraduate students (n=9) from various US schools majoring in non-public health domains, such as computer sicence and user design. Theinterns suc- cessfully developed three applications that demonstrateda value-add to chemical surveillance—ChemAnalyzer (textanalytics), RetroSpect (retrospective analysis of chemical events),and ToxicBusters (geo-based trend analytics). These applicationswill be the basis for the first chemical surveillance application to beincorporated into the DTRA Biosurveillance Ecosystem (BSVE).IntroductionPacific Northwest National Laboratory (PNNL), on behalf theDefense Threat Reduction Agency (DTRA; project number CB10190),hosts an annual intern- based web app development contest. Previouscompetitions have focused on mobile biosurveillance applications.The 2016 competition pivoted away from biosurveillance to focus onaddressing challenges within the field of chemical surveillance andincreasing public health chemical situational awareness. The result ofthe app will be integrated within the DTRA BSVE.MethodsPNNL hosted nine graduate interns for a 10-week period inthe summer of 2016 as participants in a summer web applicationdevelopment contest. Students were drawn from such fields assoftware engineering and user experience and design and placedinto three teams of three students. The challenge presented to theinterns was to design and develop a fully-functional web applicationthat would address a critical need within the chemical surveillancecommunity. The interns developed their own ideas (vetted by PNNLand DTRA), discovered and inte- grated their own data sources,and produced their own visualizations and an- alytics, independentof any assistence outside of that provided in an advisory capacity.The competition end with a judging event with a panel of subjectmatter experts and cash awards were distributed to the teams.ResultsEach team produced a unique application. Although there wasmild overlap between some of the ideas, the applications weredeveloped independently and each reflected the unique contributionsof the teams. ChemAnalyzer is a text-analytics platform designedto facilitate more data- driven decision, given a corpus of text dataabout a chemical event. Their plat- form provided the ability toautomatically identify and highlight key words in documents relatedto chemical events. The keywords are drawn from an on- tologyinstalled with the system, as well as any user-identified keywords.The ChemAnalyzer team finished in third place. The RetroSpect teamdeveloped a visual analytic tool for performing retrospec- tive analysisand monitoring of chemical events. Their app provided the ability tosearch and analyze past events, as well as visualization of state andcounty information for the recorded chemical events. The RetroSpectteam finished in second place. The Toxicbusters team—the winnersof the competition—created a geo-based situational awareness toolfor tracking chemical events. Their app featured an updateable mapoverlay, search functionality for finding specific or related events,incident and city/state/national-level statistics and trends, as wellas news and social media integration based on keywords related tochemical surveillance.ConclusionsEach of the apps developed by the teams provides value to ananalyst tasked with monitoring chemical events. The apps integratedunique data sources to provides a full picture of a chemical event, andits effects upon the surrounding population. This integrated analyticsprovides a valuable benefit over existing workflows, where analystsmust monitor news, social, and other information sources manuallyfor real-time information. The apps developed by these interns aredesigned to enable identification and analysis of the incident asquickly as possible, allowing for more timely assessments of theincident and its impacts. The web app development contest provideda unique opportunity for students to learn about the emergingneeds in chemical surveillance as it relates to health sit- uationalawareness. Students were drawn from a variety of fields and weretasked with developing novel web apps addressing some of the mostpressing challenges in the field of chemical surveillance. The ideasgenerated by the students will help form the basis for future chemicalsurveillance application development to be integrated with the DTRABSVE.

scholarly journals Analytics for Investigation of Disease Outbreaks (AIDO)

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Ashlynn Daughton ◽  
Maneesha Chitanvis ◽  
Nileena Velappan ◽  
Forest M Altherr ◽  
Geoffery Fairchild ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Situational Awareness ◽  
Contextual Information ◽  
National Laboratory ◽  
Disease Outbreaks ◽  
Disease Manifestation ◽  
Data Set ◽  
Web Based ◽  
Public Health Decision

Objective: Analytics for the Investigation of Disease Outbreaks (AIDO) is a web-based tool designed to enhance a user’s understanding of unfolding infectious disease events. A representative library of over 650 outbreaks across a wide selection of diseases allows similar outbreaks to be matched to the conditions entered by the user. These historic outbreaks contain detailed information on how the disease progressed as well as what measures were implemented to control its spread, allowing for a better understanding within the context of other outbreaks.Introduction: Situational awareness, or the understanding of elemental components of an event with respect to both time and space, is critical for public health decision-makers during an infectious disease outbreak. AIDO is a web-based tool designed to contextualize incoming infectious disease information during an unfolding event for decision-making purposes.Methods: Public health analysts of the Biology Division at Los Alamos National Laboratory curated a diverse library of historic disease outbreaks from publicly available official reports and peer reviewed literature to serve as a representation of the range of potential outbreak scenarios for a given disease. Available outbreak metadata are used to identify properties that relate to the magnitude and/or duration of the outbreak. Properties vary by disease, as they are related to disease-specific characteristics like transmission, disease manifestation, risk factors related to disease severity, and environmental factors specific to the given location. These properties are then incorporated into a similarity algorithm (s in Figure 1) to identify outbreaks that are similar to user inputs.Results: AIDO currently includes libraries for 39 diseases that are diverse across pathogen type (viral, bacterial and parasitic) as well as transmission type (vectorborne (e.g., Dengue, Malaria), foodborne (e.g., Salmonella, Campylobacteriosis), waterborne (e.g., Cholera), and person-to-person transmitted (e.g., Measles)). In addition to providing a similarity score to the user’s outbreak, we provide aggregated comparisons to multiple historical outbreaks, descriptive statistics to show the distribution of property values for each disease, and extensive contextual information about each outbreak.Conclusions: The analytics provided by AIDO allow users to interact with a unique data set of historic outbreaks and the associated metadata to contextualize incoming information and generate hypotheses about appropriate decisions. The tool is continually updated with new functionalities and additional data.

scholarly journals Origins and Development of the National Laboratory System for Public Health Testing

2010 ◽  
Vol 125 (2_suppl) ◽  
pp. 18-30 ◽  
Author(s):  
J. Rex Astles ◽  
Vanessa A. White ◽  
Laurina O. Williams
Keyword(s):  
Public Health ◽  
National Laboratory ◽  
Laboratory System

scholarly journals Moving Faster than the COVID-19 Pandemic: The Rapid, Digital Transformation of a Public Health System

2021 ◽  
Vol 12 (02) ◽  
pp. 229-236
Author(s):  
Clair Sullivan ◽  
Ides Wong ◽  
Emily Adams ◽  
Magid Fahim ◽  
Jon Fraser ◽  
...  
Keyword(s):  
Public Health ◽  
Health System ◽  
Public Health System ◽  
Digital Transformation ◽  
Contact Tracing ◽  
Programming Approach ◽  
Data Governance ◽  
Application Development ◽  
Containment Strategy

Abstract Background Queensland, Australia has been successful in containing the COVID-19 pandemic. Underpinning that response has been a highly effective virus containment strategy which relies on identification, isolation, and contact tracing of cases. The dramatic emergence of the COVID-19 pandemic rendered traditional paper-based systems for managing contact tracing no longer fit for purpose. A rapid digital transformation of the public health contact tracing system occurred to support this effort. Objectives The objectives of the digital transformation were to shift legacy systems (paper or standalone electronic systems) to a digitally enabled public health system, where data are centered around the consumer rather than isolated databases. The objective of this paper is to outline this case study and detail the lessons learnt to inform and give confidence to others contemplating digitization of public health systems in response to the COVID-19 pandemic. Methods This case study is set in Queensland, Australia. Universal health care is available. A multidisciplinary team was established consisting of clinical informaticians, developers, data strategists, and health information managers. An agile “pair-programming” approach was undertaken to application development and extensive change efforts were made to maximize adoption of the new digital workflows. Data governance and flows were changed to support rapid management of the pandemic. Results The digital coronavirus application (DCOVA) is a web-based application that securely captures information about people required to quarantine and creates a multiagency secure database to support a successful containment strategy. Conclusion Most of the literature surrounding digital transformation allows time for significant consultation, which was simply not possible under crisis conditions. Our observation is that staff was willing to adopt new digital systems because the reason for change (the COVID-19 pandemic) was clearly pressing. This case study highlights just how critical a unified purpose, is to successful, rapid digital transformation.

Framing Bacterial Genomics for Public Health(care)

2021 ◽  
Author(s):  
Alison Laufer Halpin ◽  
L. Clifford McDonald ◽  
Christopher A. Elkins
Keyword(s):  
Public Health ◽  
National Laboratory ◽  
Resistance Mechanisms ◽  
Public Health Care ◽  
Virulence Determinants ◽  
Top Down ◽  
Bottom Up ◽  
The Public ◽  
Bacterial Genomics ◽  
Healthcare Associated

Advancements in comparative genomics have generated significant interest in defining applications for healthcare-associated pathogens. Clinical microbiology, however, relies on increasingly automated platforms to quickly identify pathogens, resistance mechanisms, and therapy options within CLIA- and FDA-approved frameworks. Additionally, and most notably, healthcare-associated pathogens, especially those that are resistant to antibiotics, represent a diverse spectrum of genera harboring complex genetic targets including antibiotic, biocide, and virulence determinants that can be highly transmissible and, at least for antibiotic resistance, serve as potential targets for containment efforts. U.S. public health investments have focused on rapidly detecting outbreaks and emerging resistance in healthcare-associated pathogens using reference, culture-based, and molecular methods that are distributed, for example, across national laboratory network infrastructures. Herein we describe the public health applications of genomic science that are built from the top-down for broad surveillance, as well as the bottom-up, starting with identification of infections and infectious clusters. For healthcare-associated, including antimicrobial-resistant, pathogens, we propose a combination of top-down and bottom-up genomic approaches leveraged across the public health spectrum, from local infection control, to regional and national containment efforts, to national surveillance for understanding emerging strain ecology and fitness of healthcare pathogens.

Situational awareness in public health preparedness settings

2005 ◽  
Author(s):  
Parsa Mirhaji ◽  
Yanko F. Michea ◽  
Jiajie Zhang ◽  
Samuel W. Casscells
Keyword(s):  
Public Health ◽  
Situational Awareness ◽  
Public Health Preparedness

scholarly journals Use of Emergency Department Data to Monitor and Respond to an Increase in Opioid Overdoses in New Hampshire, 2011-2015

2017 ◽  
Vol 132 (1_suppl) ◽  
pp. 73S-79S ◽  
Author(s):  
Elizabeth R. Daly ◽  
Kenneth Dufault ◽  
David J. Swenson ◽  
Paul Lakevicius ◽  
Erin Metcalf ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
New Hampshire ◽  
Syndromic Surveillance ◽  
Situational Awareness ◽  
The United States ◽  
Chief Complaint ◽  
Public Health Response ◽  
Syndromic Surveillance System ◽  
Icd Codes

Objectives: Opioid-related overdoses and deaths in New Hampshire have increased substantially in recent years, similar to increases observed across the United States. We queried emergency department (ED) data in New Hampshire to monitor opioid-related ED encounters as part of the public health response to this health problem. Methods: We obtained data on opioid-related ED encounters for the period January 1, 2011, through December 31, 2015, from New Hampshire’s syndromic surveillance ED data system by querying for (1) chief complaint text related to the words “fentanyl,” “heroin,” “opiate,” and “opioid” and (2) opioid-related International Classification of Diseases ( ICD) codes. We then analyzed the data to calculate frequencies of opioid-related ED encounters by age, sex, residence, chief complaint text values, and ICD codes. Results: Opioid-related ED encounters increased by 70% during the study period, from 3300 in 2011 to 5603 in 2015; the largest increases occurred in adults aged 18-29 and in males. Of 20 994 total opioid-related ED visits, we identified 18 554 (88%) using ICD code alone, 690 (3%) using chief complaint text alone, and 1750 (8%) using both chief complaint text and ICD code. For those encounters identified by ICD code only, the corresponding chief complaint text included varied and nonspecific words, with the most common being “pain” (n = 3335, 18%), “overdose” (n = 1555, 8%), “suicidal” (n = 816, 4%), “drug” (n = 803, 4%), and “detox” (n = 750, 4%). Heroin-specific encounters increased by 827%, from 4% of opioid-related encounters in 2011 to 24% of encounters in 2015. Conclusions: Opioid-related ED encounters in New Hampshire increased substantially from 2011 to 2015. Data from New Hampshire’s ED syndromic surveillance system provided timely situational awareness to public health partners to support the overall response to the opioid epidemic.

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