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Landscape of international event-based biosurveillance

Hartley, DM; Nelson, NP; Walters, R; Arthur, R; Yangarber, R; Madoff, L; Linge, JP; Mawudeku, A; Collier, N; Brownstein, JS; Thinus, G; Lightfoot, N
Fonte: CoAction Publishing Publicador: CoAction Publishing
Tipo: Artigo de Revista Científica
Publicado em 19/02/2010 EN
Relevância na Pesquisa
27.75%
Event-based biosurveillance is a scientific discipline in which diverse sources of data, many of which are available from the Internet, are characterized prospectively to provide information on infectious disease events. Biosurveillance complements traditional public health surveillance to provide both early warning of infectious disease events and situational awareness. The Global Health Security Action Group of the Global Health Security Initiative is developing a biosurveillance capability that integrates and leverages component systems from member nations. This work discusses these biosurveillance systems and identifies needed future studies.

Advancing a Framework to Enable Characterization and Evaluation of Data Streams Useful for Biosurveillance

Margevicius, Kristen J.; Generous, Nicholas; Taylor-McCabe, Kirsten J.; Brown, Mac; Daniel, W. Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 02/01/2014 EN
Relevância na Pesquisa
28.1%
In recent years, biosurveillance has become the buzzword under which a diverse set of ideas and activities regarding detecting and mitigating biological threats are incorporated depending on context and perspective. Increasingly, biosurveillance practice has become global and interdisciplinary, requiring information and resources across public health, One Health, and biothreat domains. Even within the scope of infectious disease surveillance, multiple systems, data sources, and tools are used with varying and often unknown effectiveness. Evaluating the impact and utility of state-of-the-art biosurveillance is, in part, confounded by the complexity of the systems and the information derived from them. We present a novel approach conceptualizing biosurveillance from the perspective of the fundamental data streams that have been or could be used for biosurveillance and to systematically structure a framework that can be universally applicable for use in evaluating and understanding a wide range of biosurveillance activities. Moreover, the Biosurveillance Data Stream Framework and associated definitions are proposed as a starting point to facilitate the development of a standardized lexicon for biosurveillance and characterization of currently used and newly emerging data streams. Criteria for building the data stream framework were developed from an examination of the literature...

Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis

Generous, Nicholas; Margevicius, Kristen J.; Taylor-McCabe, Kirsten J.; Brown, Mac; Daniel, W. Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 29/01/2014 EN
Relevância na Pesquisa
27.75%
The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility...

Biosurveillance enterprise for operational awareness, a genomic-based approach for tracking pathogen virulence

Valdivia-Granda, Willy A
Fonte: Landes Bioscience Publicador: Landes Bioscience
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
27.43%
To protect our civilians and warfighters against both known and unknown pathogens, biodefense stakeholders must be able to foresee possible technological trends that could affect their threat risk assessment. However, significant flaws in how we prioritize our countermeasure-needs continue to limit their development. As recombinant biotechnology becomes increasingly simplified and inexpensive, small groups, and even individuals, can now achieve the design, synthesis, and production of pathogenic organisms for offensive purposes. Under these daunting circumstances, a reliable biosurveillance approach that supports a diversity of users could better provide early warnings about the emergence of new pathogens (both natural and manmade), reverse engineer pathogens carrying traits to avoid available countermeasures, and suggest the most appropriate detection, prophylactic, and therapeutic solutions. While impressive in data mining capabilities, real-time content analysis of social media data misses much of the complexity in the factual reality. Quality issues within freeform user-provided hashtags and biased referencing can significantly undermine our confidence in the information obtained to make critical decisions about the natural vs. intentional emergence of a pathogen. At the same time...

A Review of Evaluations of Electronic Event-Based Biosurveillance Systems

Gajewski, Kimberly N.; Peterson, Amy E.; Chitale, Rohit A.; Pavlin, Julie A.; Russell, Kevin L.; Chretien, Jean-Paul
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 20/10/2014 EN
Relevância na Pesquisa
27.43%
Electronic event-based biosurveillance systems (EEBS’s) that use near real-time information from the internet are an increasingly important source of epidemiologic intelligence. However, there has not been a systematic assessment of EEBS evaluations, which could identify key uncertainties about current systems and guide EEBS development to most effectively exploit web-based information for biosurveillance. To conduct this assessment, we searched PubMed and Google Scholar to identify peer-reviewed evaluations of EEBS’s. We included EEBS’s that use publicly available internet information sources, cover events that are relevant to human health, and have global scope. To assess the publications using a common framework, we constructed a list of 17 EEBS attributes from published guidelines for evaluating health surveillance systems. We identified 11 EEBS’s and 20 evaluations of these EEBS’s. The number of published evaluations per EEBS ranged from 1 (Gen-Db, GODsN, MiTAP) to 8 (GPHIN, HealthMap). The median number of evaluation variables assessed per EEBS was 8 (range, 3–15). Ten published evaluations contained quantitative assessments of at least one key variable. No evaluations examined usefulness by identifying specific public health decisions...

Sigma: Strain-level inference of genomes from metagenomic analysis for biosurveillance

Ahn, Tae-Hyuk; Chai, Juanjuan; Pan, Chongle
Fonte: Oxford University Press Publicador: Oxford University Press
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
27.43%
Motivation: Metagenomic sequencing of clinical samples provides a promising technique for direct pathogen detection and characterization in biosurveillance. Taxonomic analysis at the strain level can be used to resolve serotypes of a pathogen in biosurveillance. Sigma was developed for strain-level identification and quantification of pathogens using their reference genomes based on metagenomic analysis.

Constructing Rigorous and Broad Biosurveillance Networks for Detecting Emerging Zoonotic Outbreaks

Brown, Mac; Moore, Leslie; McMahon, Benjamin; Powell, Dennis; LaBute, Montiago; Hyman, James M.; Rivas, Ariel; Jankowski, Mark; Berendzen, Joel; Loeppky, Jason; Manore, Carrie; Fair, Jeanne
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 06/05/2015 EN
Relevância na Pesquisa
27.43%
Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities of potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human...

A Biosurveillance-driven Home Score to Guide Strep Pharyngitis Treatment

Fine, Andrew; Nizet, Victor; Mandl, Kenneth
Fonte: University of Illinois at Chicago Library Publicador: University of Illinois at Chicago Library
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
37.84%
Objective: 1. To derive and validate an accurate clinical prediction model (“home score”) to estimate a patient’s risk of group A streptococcal (GAS) pharyngitis before a health care visit based only on history and real-time local biosurveillance, and to compare its accuracy to traditional clinical prediction models composed of history and physical exam features. 2. To examine the impact of a home score on patient and public health outcomes. Introduction: GAS pharyngitis affects hundreds of millions of individuals globally each year, and over 12 million seek care in the United States annually for sore throat. Clinicians cannot differentiate GAS from other causes of acute pharyngitis based on the oropharynx exam, so consensus guidelines recommend use of clinical scores to classify GAS risk and guide management of adults with acute pharyngitis. When the clinical score is low, consensus guidelines agree patients should neither be tested nor treated for GAS. A prediction model that could identify very-low risk patients prior to an ambulatory visit could reduce low-yield, unnecessary visits for a most common outpatient condition. We recently showed that real-time biosurveillance can further identify patients at low-risk of GAS. With increasing emphasis on patient-centric health care and the well-documented barriers impeding clinicians’ incorporation of prediction models into medical practice...

Landscape of international event-based biosurveillance

HARTLEY David; NELSON Noele; WALTERS R.; ARTHUR Ray; YANGARBER Roman; MADOFF Larry; LINGE Jens; MAWUDEKU Abla; COLLIER Nigel; BROWNSTEIN John; THINUS Germain; LIGHTFOOT Nigel
Fonte: Emerging Health Threats Forum Publicador: Emerging Health Threats Forum
Tipo: Articles in Journals Formato: Printed
ENG
Relevância na Pesquisa
27.75%
Event-based biosurveillance is a scientific discipline in which diverse sources of data, many of which are available from the Internet, are characterized prospectively to provide information on infectious disease events. Biosurveillance complements traditional public health surveillance to provide both early warning of infectious disease events and situational awareness. The Global Health Security Action Group of the Global Health Security Initiative is developing a biosurveillance capability that integrates and leverages component systems from member nations. This work discusses these biosurveillance systems and identifies needed future studies.; JRC.DG.G.2-Global security and crisis management

Factors Influencing Performance of Internet-Based Biosurveillance Systems Used in Epidemic Intelligence for Early Detection of Infectious Diseases Outbreaks

BARBOZA Philippe; VAILLANT Laetitia; HARTLEY David; NELSON Noele; MAWUDEKU Abla; MADOFF Larry; LINGE Jens; COLLIER Nigel; BROWNSTEIN John; ASTAGNEAU Pascal
Fonte: PUBLIC LIBRARY SCIENCE Publicador: PUBLIC LIBRARY SCIENCE
Tipo: Articles in Journals Formato: Online
ENG
Relevância na Pesquisa
27.62%
Background: Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Method and Findings: Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems’ performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p,0001). I-Se varied significantly from 43% to 71% (p = 0001) whereas other indicators were similar (C-DR: p = 020; C-Se...

Interfacing a biosurveillance portal and an international network of institutional analysts to detect biological threats

RICCARDO Flavia; SHIGEMATSU Mika; CHOW Catherine; LINGE Jens; DOHERTY Brian; DENTE Maria Grazia; DECLICH Silvia; BARKER Mike; BARBOZA Philippe; VAILLANT Laetitia; DONACHIE Alastair; MAWUDEKU Abla; ARTHUR Ray; MCKNIGHT Jason
Fonte: MARY ANN LIEBERT Publicador: MARY ANN LIEBERT
Tipo: Articles in Journals Formato: Online
ENG
Relevância na Pesquisa
27.43%
The Early Alerting and Reporting (EAR) project launched in 2008, is aimed at improving global early alerting and risk assessment and evaluating the feasibility and opportunity of integrating the analysis of biological, chemical, radio-nuclear (CBRN) and pandemic influenza threats. At a time when no international collaborations existed in the field of event based surveillance, EAR’s innovative approach consisted in the involvement of both epidemic intelligence experts and internet-based biosurveillance system providers in the framework of an international collaboration called the Global Health Security initiative that involved the Ministries of Health of G7 countries and Mexico, the World Health Organization and the European Commission. The EAR project pooled data from seven major internet-based biosurveillance systems onto a common portal that was progressively optimized for biological threat detection under the guidance of epidemic intelligence experts from public health institutions in Canada, the European Centre for Disease Prevention and Control, France, Germany, Italy, Japan, the United Kingdom and the United States of America. The group became the first end users of the EAR portal, constituting a network of analysts working with a common standard operating procedure and risk assessment tools on a rotation basis to constantly screen and assess public information on the web for events that could suggest an intentional release of biological agents. Following the first two-year pilot phase...

An overview of Internet biosurveillance

HARTLEY David; NELSON Noele; ARTHUR Ray; BARBOZA Philippe; COLLIER Nigel; LIGHTFOOT Nigel; LINGE Jens; VAN DER GOOT Erik; MAWUDEKU Abla; MADOFF Larry; VAILLANT Laetitia; WALTERS R.; YANGARBER Roman; MANTERO Jas; COURTNEY D Corley; BROWNSTEIN John
Fonte: Wiley Publicador: Wiley
Tipo: Articles in periodicals and books Formato: Online
ENG
Relevância na Pesquisa
27.75%
Internet biosurveillance utilizes unstructured data from diverse web-based sources to provide early warning and situational awareness of public health threats. The scope of source coverage ranges from local media in the vernacular to international media in widely read languages. Internet biosurveillance is a timely modality that is available to government and public health officials, healthcare workers, and the public and private sector, serving as a real-time complementary approach to traditional indicator-based public health disease surveillance methods. Internet biosurveillance also supports the broader activity of epidemic intelligence. This overview covers the current state of the field of Internet biosurveillance, and provides a perspective on the future of the field.; JRC.G.2-Global security and crisis management

Assessing the effectiveness of biosurveillance via discrete event simulation

Dao, Jason H.
Fonte: Monterey, California. Naval Postgraduate School Publicador: Monterey, California. Naval Postgraduate School
Tipo: Tese de Doutorado
Relevância na Pesquisa
27.62%
Bioterrorism is not a new threat, but the potential for disastrous outcomes is greater than it has ever been. In order to confront this threat, biosurveillance systems are utilized to provide early warning of health threats, early detection of health events, and situational awareness of disease activity. To date, there is little known about the performance of such biosurveillance systems in comparison to diagnosis capabilities of medical personnel. In this thesis, a discrete event simulation model of an anthrax outbreak is developed in order to analyze the performance of such biosurveillance systems in comparison to medical personnel. This research found the Early Aberration Reporting System C1 statistical algorithm is useful in early event detection of a bioterror attack. Given an exposed population of 1,000 people, the nominal probability that the algorithm signals first is 31.5% and it is 0.3% for an exposed population of 10,000 people. Given an exposed population of 1,000 people, the nominal time it takes for the algorithm to signal is 3.3 days and 0.38 days for an exposed population of 10,000 people.

Evaluating Biosurveillance System Performance: Using the Early Aberration Reporting System (EARS) to Detect H1N1 in Monterey County, California (Poster)

Fricker, Ronald D.; Hagen, Katie; Barnes, Suan; Fricker, Ronald; Michie, Kristy; Rees, Bryan; Hanni, Krista
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Poster
Relevância na Pesquisa
27.62%
The Monterey County Health Department (MCHD) in California uses the Early Aberration Reporting System (EARS) to monitor emergency room and clinic data for biosurveillance, particularly as an alert system for increases in various types of disease. The flexibility of the syndrome building process has proven to be the most useful feature of EARS compared to other biosurveillance tools, but it is also the one feature most prone to programming errors. To ameliorate this issue, a collaborative academic/public health partnership was developed to provide an opportunity to study methods which improve the overall biosurveillance goals of EARS.

Optimizing Biosurveillance Systems that Use Threshold-based Event Detection Methods

Fricker, Ronald D., Jr.; Banschbach, David
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Journal Paper
Relevância na Pesquisa
27.43%
Information Fusion, 13, 117-128.; The article of record as published may be found at http://dx.doi.org/10.1016/j.inffus.2009.12.002; We describe a methodology for optimizing a threshold detection-based biosurveillance system. The goal is to maximize the system-wide probability of detecting an ‘‘event of interest” against a noisy background, subject to a constraint on the expected number of false signals. We use nonlinear programming to appropriately set detection thresholds taking into account the probability of an event of interest occurring somewhere in the coverage area. Using this approach, public health officials can ‘‘tune” their biosurveillance systems to optimally detect various threats, thereby allowing practitioners to focus their public health surveillance activities. Given some distributional assumptions, we derive a one-dimensional optimization methodology that allows for the efficient optimization of very large systems. We demonstrate that optimizing a syndromic surveillance system can improve its performance by 20–40%.

Biosurveillance: Detecting, Tracking, and Mitigating the Effects of Natural Disease and Bioterrorism

Fricker, Ronald D. Jr.
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Parte de Livro
Relevância na Pesquisa
27.62%
Encyclopedia of Operations Research and the Management Sciences, Cochran, J.J. (ed.), John Wiley & Sons Ltd.; The article of record as published may be located at http://dx.doi.org/10.1002/9780470400531; Biosurveillance is the regular collection, analysis, and interpretation of health and health related data for indicators of diseases and other outbreaks by public health organizations. Motivated by the threat of bioterrorism, biosurviellance systems are being developed and implemented around the world. The goal of these systems has been expanded to include both early event detection and situational awareness, so that the focus is not simply on detection, but also on response and consequence management. Whether they rae useful for detecting bioterrorism or not, there seems to be consensus that these biosurveillance systems are likely to be useful for detecting bioterrorism or not, there seems to be consensus that these biosurveillance systems are likely to be useful for detecting and responding to naural disease outbreaks such as seasonal and pandemic flu, and thus they have potential to significantly advance and modernize the practice of public health surveillance.

Comparing Directionally Sensitive MCUSUM and MEWMA Procedures with Application to Biosurveillance

Fricker, Ronald D. Jr.; Hu, Cecilia X.
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Journal Paper
Relevância na Pesquisa
27.43%
Quality Engineering, 20, 478-494.; This paper compares the performance of two new directly-sensitive multivariate methods, based on the multivariate CUSUM (MCUSUM) and the multivariate exponentially weighted moving average (MEWMA), for biosurveillance. While neither of these methods is currently in use in a biosurviellance system, they are among the most promising multivariate methods for this application. Our analysis is based on a detailed series of simulations using synthetic biosurveillance data that mimics various types of disease background incidence and outbreaks. We apply the MCUSUM and the MEWMA to residuals from an adaptive regression that accounts for the systematic effects normally present in biosurviellance data. We find that, much like the results from univariate CUSUM and EWMA comparisons in classical statistical process control applications, the directionally-sensitive MCUSUM and MEWMA perform very similarly.

Some Methodological Issues in Biosurveillance

Fricker, Ronald D. Jr.
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Journal Paper
Relevância na Pesquisa
27.43%
with commentaries [1] [2] [3] [4] [5] and rejoinder), Statistics in Medicine, 30, 403-441.; The article of record as published may be found at http://dx.doi.org/10.1002/sim.3880; The PowerPoint slides from the complete talk can be accessed at http://faculty.nps.edu/rdfricke/Biosurveillance.htm; This paper briefly summarizes a short course I gave at the 12th Biennial Centers for Disease Control and Prevention (CDC) and Agency for Toxic Substances and Disease Registry (ATSDR) Symposium held in Decatur, Georgia on April 6, 2009. The goal of this short course was to discuss various methodological issues of biosurveillance detection algorithms, with a focus on the issues related to developing, evaluating, and implementing such algorithms.

A Spatio-temporal Methodology for Real-time Biosurveillance

Fricker, Ronald D., Jr.; Chang, Joseph T.
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Journal Paper
Relevância na Pesquisa
27.62%
Quality Engineering, 20, 465-477.; In this paper we introduce a new spatio-temporal methodology for biosurveillance entitled the Repeated Two-sample Rank (RTR) procedure. It is designed to sequentially incorporate information from individual observations and thus can operate on data in real-time as it arrives into an automated biosurveillance system. In addition, upon a signal of a possible outbreak, the methodology suggests a way to graphically indicate the likely outbreak location, and the output can subsequently be used to track the spread of an outbreak. Thus, the methodology can be used for both early event detection and situational awareness in automated biosurveillance systems.

Factors Influencing Performance of Internet-Based Biosurveillance Systems Used in Epidemic Intelligence for Early Detection of Infectious Diseases Outbreaks

Barboza, Philippe; Vaillant, Laetitia; Le Strat, Yann; Hartley, David M.; Nelson, Noele P.; Mawudeku, Abla; Madoff, Lawrence C.; Linge, Jens P.; Collier, Nigel; Brownstein, John S.; Astagneau, Pascal
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
27.62%
Background: Internet-based biosurveillance systems have been developed to detect health threats using information available on the Internet, but system performance has not been assessed relative to end-user needs and perspectives. Method and Findings Infectious disease events from the French Institute for Public Health Surveillance (InVS) weekly international epidemiological bulletin published in 2010 were used to construct the gold-standard official dataset. Data from six biosurveillance systems were used to detect raw signals (infectious disease events from informal Internet sources): Argus, BioCaster, GPHIN, HealthMap, MedISys and ProMED-mail. Crude detection rates (C-DR), crude sensitivity rates (C-Se) and intrinsic sensitivity rates (I-Se) were calculated from multivariable regressions to evaluate the systems’ performance (events detected compared to the gold-standard) 472 raw signals (Internet disease reports) related to the 86 events included in the gold-standard data set were retrieved from the six systems. 84 events were detected before their publication in the gold-standard. The type of sources utilised by the systems varied significantly (p<0001). I-Se varied significantly from 43% to 71% (p = 0001) whereas other indicators were similar (C-DR: p = 020; C-Se...