scholarly journals Evaluating multi-purpose syndromic surveillance systems – a complex problem

2021 ◽  
Vol 13 (3) ◽  
Author(s):  
Roger Morbey ◽  
Gillian Smith ◽  
Isabel Oliver ◽  
Obaghe Edeghere ◽  
Iain Lake ◽  
...  
Keyword(s):  
Decision Making ◽  
Syndromic Surveillance ◽  
Detection Algorithm ◽  
Complex Problem ◽  
Automated Detection ◽  
Surveillance Systems ◽  
Practical Application ◽  
Wide Range ◽  
Human Decision ◽  
Detection Capabilities

Surveillance systems need to be evaluated to understand what the system can or cannot detect. The measures commonly used to quantify detection capabilities are sensitivity, positive predictive value and timeliness. However, the practical application of these measures to multi-purpose syndromic surveillance services is complex. Specifically, it is very difficult to link definitive lists of what the service is intended to detect and what was detected. First, we discuss issues arising from a multi-purpose system, which is designed to detect a wide range of health threats, and where individual indicators, e.g. ‘fever’, are also multi-purpose. Secondly, we discuss different methods of defining what can be detected, including historical events and simulations. Finally, we consider the additional complexity of evaluating a service which incorporates human decision-making alongside an automated detection algorithm. Understanding the complexities involved in evaluating multi-purpose systems helps design appropriate methods to describe their detection capabilities.

scholarly journals Smart EcoCUVA – Tools for Food Marketing Strategy

2006 ◽  
pp. 1-8
Author(s):  
Maarit Pallari
Keyword(s):  
Decision Making ◽  
Action Research ◽  
Well Being ◽  
Complex Problem ◽  
Utility Value ◽  
Value Analysis ◽  
Trade Offs ◽  
Wide Range ◽  
The Usa ◽  
Application Fields

The implementation of the green productivity and marketing concept in agribusiness is a must in the future.Food production is influenced by the environment and society, and vice versa. Today a growing number ofconsumers are aware of the link between environmental and social well-being and fresh, pure, healthy, tastyand safe foodstuffs. Enterprises will have to consider three important aspects of value when doing business:economic, social and environmental value. The foundation of the quality research this study is concernedwith is action research. Action research is a way to analyze sustainable development, the aptness ofagriculture and the marketing opportunities these offer for developing ecoproducts in the SMEs.The study seeks to answer the following questions:- What kind of Classical Utility Value Analyses could be tool of the eco-product?- To what extent can a customer/interest group affect the development and decision-making of ecoproducts?- Is the method a suitable tool for analyzing ecological criterions in the marketing model?Classical Utility Value Analysis is a formal, analytic approach for evaluating and comparing differentalternatives. It is one decision making method of multi-criteria analysis. The roots of utility value analysis,which is one of the mathematical models for analytical decision making, are in the USA and Germany. Themethod is almost 40 years old, of the same age as the manuscript of the values tradeoff. The same historicallanguage is being used to build up new tools, principles and theory. The so-called Smart EcoCUVA hasused both methodologies (Utility value analysis and decision making analysis) when setting the goals andmathematical steps. Research results always give the best available alternative.Making rational decisions for any complex problem requires various analyses of trade-offs (compromises)between conflicting goals (objectives, outcomes) that are used for measuring the results of applying variousdecisions in a wide range of application fields. A typical decision problem has an infinite number ofsolutions, and decision makers are interested in analyzing trade-offs between those that correspond to theirpreferences, which is often called a preferential structure of the decision-maker.Smart EcoCuva analysis helps to assess different alternatives according to a variety of environmentalcriteria associated with enterprises and their products. The analysis methods take account of the monetaryand non-monetary aspects when determining the selection of the best alternative. Smart EcoCuva is themethodological cornerstone for the creation of an innovative concept that will contribute to encouraging theefficient use of natural resources and thereby enhancing sustainability.The Smart EcoCuva tools to be developed aim to be environmentally sound, economically viable, sociallyjust and culturally appropriate. They are a new, science-based reaction of sustainable agriculture to globalatmosphere, as well as constitute an appropriate link between people and nature. New environmentallyfriendly food combines healthy food with people’s lifestyles.

Searching for Herbert Simon

2013 ◽  
Vol 4 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Michael F. Gorman ◽  
Donald E. Wynn ◽  
William David Salisbury
Keyword(s):  
Decision Making ◽  
Analytical Techniques ◽  
Decision Makers ◽  
Business Analytics ◽  
Herbert Simon ◽  
Business Decision ◽  
Wide Range ◽  
Human Decision ◽  
Potential Impact ◽  
Effective Use

Since Herbert Simon’s seminal work (Simon, 1957) on bounded rationality researchers and practitioners have sought the “holy grail” of computer-supported decision-making. A recent wave of interest in “business analytics” (BA) has elevated interest in data-driven analytical decision making to the forefront. While reporting and prediction via business intelligence (BI) systems has been an important component to business decision making for some time, BA broadens its scope and potential impact in business decision making further by moving the focus to prescription. The authors see BA as the end-to-end process integrating the production through consumption of the data, and making more extensive use of the data through heavily automated, integrated and advanced predictive and prescriptive tools in ways that better support, or replace, the human decision maker. With the advent of “big data”, BA already extends beyond internal databases to external and unstructured data that is publicly produced and consumed data with new analytical techniques to better enable business decision makers in a connected world. BI research in the future will be broader in scope, and the challenge is to make effective use of a wide range of data with varying degrees of structure, and from sources both internal and external to the organization. In this paper, we suggest ways that this broader focus of BA will also affect future BI research streams.

scholarly journals An Automated Detection System for Microaneurysms That Is Effective across Different Racial Groups

2016 ◽  
Vol 2016 ◽  
pp. 1-5
Author(s):  
George Michael Saleh ◽  
James Wawrzynski ◽  
Silvestro Caputo ◽  
Tunde Peto ◽  
Lutfiah Ismail Al Turk ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Detection System ◽  
Detection Algorithm ◽  
Rapid Identification ◽  
Automated Detection ◽  
Automated System ◽  
Racial Groups ◽  
Fundus Images ◽  
Screening Service ◽  
Wide Range

Patients without diabetic retinopathy (DR) represent a large proportion of the caseload seen by the DR screening service so reliable recognition of the absence of DR in digital fundus images (DFIs) is a prime focus of automated DR screening research. We investigate the use of a novel automated DR detection algorithm to assess retinal DFIs for absence of DR. A retrospective, masked, and controlled image-based study was undertaken. 17,850 DFIs of patients from six different countries were assessed for DR by the automated system and by human graders. The system’s performance was compared across DFIs from the different countries/racial groups. The sensitivities for detection of DR by the automated system were Kenya 92.8%, Botswana 90.1%, Norway 93.5%, Mongolia 91.3%, China 91.9%, and UK 90.1%. The specificities were Kenya 82.7%, Botswana 83.2%, Norway 81.3%, Mongolia 82.5%, China 83.0%, and UK 79%. There was little variability in the calculated sensitivities and specificities across the six different countries involved in the study. These data suggest the possible scalability of an automated DR detection platform that enables rapid identification of patients without DR across a wide range of races.

scholarly journals Communicating the detection capabilities of syndromic surveillance systems

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Roger Morbey
Keyword(s):  
Public Health ◽  
Risk Assessment ◽  
Syndromic Surveillance ◽  
Evidence Synthesis ◽  
Decision Makers ◽  
Assessment Process ◽  
Surveillance Systems ◽  
Specificity And Sensitivity ◽  
Different Types ◽  
Detection Capabilities

ObjectiveTo communicate the detection capabilities of syndromic surveillance systems to public health decision makers.IntroductionIncreasingly public health decision-makers are using syndromic surveillance for real-time reassurance and situational awareness in addition to early warning1. Decision-makers using intelligence, including syndromic data, need to understand what the systems are capable of detecting, what they cannot detect and specifically how much reassurance should be inferred when syndromic systems report ‘nothing detected’. In this study we quantify the detection capabilities of syndromic surveillance systems used by Public Health England (PHE).The key measures for detection capabilities are specificity and sensitivity (although timeliness is also very important for surveillance systems)2. However, measuring the specificity and sensitivity of syndromic surveillance systems is not straight forward. Firstly, syndromic systems are usually multi-purpose and may be better at identifying certain types of public health threat than others. Secondly, whilst it is easy to quantify statistical aberration detection algorithms, surveillance systems involve other stages, including data collection and human decision-making, which also affect detection capabilities. Here, we have taken a ‘systems thinking’ approach to understand potential barriers to detection, and summarize what we know about detection capabilities of syndromic surveillance systems in England.MethodsWithin the systems thinking approach all stages in surveillance (data collection, automated statistical analysis, expert risk assessment and reporting of any aberrations) were considered. Sensitivity and specificity were then calculated for the system as a whole, and the separate impact of each process stage.To communicate these findings to decision-makers, we created an evidence synthesis. Evidence was synthesised from research involving PHE syndromic surveillance systems and retrospective incidents detected and/or investigated by PHE. We then summarized the evidence for different types of incident.ResultsWe identified the following stages which influence detection:The proportion of people who become symptomatic;The proportion of symptomatic people who present to different types of health care;The coding of symptomatic patients;Coverage of different health care systems by syndromic surveillance;Statistical algorithms used to identify unusual clusters within syndromic data;Risk assessment process used to determine action resulting following automated statistical alarms3.Stages 1 to 3 depend on the type of incident that is affecting peoples’ health or healthcare seeking behaviour: stages 3 to 6 depend on the capabilities of the syndromic surveillance system. In general, each stage increases the time until detection, and reduces sensitivity but should improve specificity.Our evidence synthesis identified a wide range of threats to public health including: seasonal outbreaks of respiratory infections; allergic rhinitis; insect bites; gastrointestinal outbreaks; air pollution; and heat waves. We ranked the available evidence, giving more weight to actual events detected and validated against independent evidence, and less to purely descriptive epidemiology or modelled simulations. We created different measures for sensitivity, specificity and timeliness depending on the type of evidence available. Sensitivity ranged from 100% for seasonal influenza to 0% for seasonal adenovirus. Specificity also varied, with high specificity where we had a specific syndromic indicators, e.g. sunstroke, and lower for those associated only with more generic multi-purpose indicators e.g. acute respiratory infections. Timeliness varied from being able to provide early warning of up to seven days prior to traditional surveillance methods for some respiratory illnesses, to being able to detect and report on the health impact of air pollution within four days of a period of poor air quality.ConclusionsThis study has shown that a syndromic surveillance systems’ utility depends on more than just an algorithm’s specificity and sensitivity measure. We’ve identified the impact of the different surveillance stages and separately considered different types of incident. Thus, we can identify the impact of issues such as local population coverage and an individual investigator’s risk assessment practices. Furthermore, the evidence synthesis will provide a summary for decision makers, and help identify gaps in our knowledge where more research is required.References1. Colon-Gonzalez FJ, Lake IR, Morbey RA, Elliot AJ, Pebody R, Smith GE. A methodological framework for the evaluation of syndromic surveillance systems: a case study of England. BMC Public Health. 2018;18(1):544. http://dx.doi.org/10.1186/s12889-018-5422-92. Kleinman KP, Abrams AM. Assessing surveillance using sensitivity, specificity and timeliness. Stat Methods Med Res. 2006;15(5):445-64.3. Smith GE, Elliot AJ, Ibbotson S, Morbey R, Edeghere O, Hawker J, et al. Novel public health risk assessment process developed to support syndromic surveillance for the 2012 Olympic and Paralympic Games. J Public Health. 2016. http://dx.doi.org/10.1093/pubmed/fdw054

The Oxford Handbook of Offender Decision Making

2017 ◽  
Keyword(s):  
Decision Making ◽  
Criminal Behavior ◽  
Rational Choice Theory ◽  
Choice Theory ◽  
Process Models ◽  
Dual Process ◽  
Core Element ◽  
Sexual Crime ◽  
Wide Range ◽  
Human Decision

How offenders make decisions that lead to criminal conduct is a core element of virtually every discussion about crime and law enforcement. What type of information can deter a potential offender? For whom is the prospect of a sanction effective? How can emotions facilitate or impede crime? How does the availability of guns affect behavior in violent conflicts? Do offenders learn to commit crime from the experiences of others? Is crime perpetrated by juveniles always the result of impulsive decisions? How do offenders choose crime targets and locations? The Oxford Handbook of Offender Decision Making covers and integrates contemporary theoretical, methodological, and empirical knowledge about the role of human decision making as it relates to criminal behavior. It provides state-of-the art reviews of the main paradigms in offender decision making, such as rational choice theory and deterrence, but also includes recent approaches such as dual-process models of decision making. It contains up-to-date reviews of empirical research on a wide range of decision types, from criminal initiation and desistance to choice of location, time, target, victim, and modus operandi. It also contains reviews of decision making regarding specific types of crime, including homicide, sexual crime, burglary, and white-collar and organized crime. In addition, it includes comprehensive in-depth treatments of the principal research methods used to study offender decision making, such as experimental designs, observation studies, surveys, offender interviews, and simulations.

scholarly journals Comparison of statistical algorithms for daily syndromic surveillance aberration detection

2019 ◽  
Vol 35 (17) ◽  
pp. 3110-3118
Author(s):  
Angela Noufaily ◽  
Roger A Morbey ◽  
Felipe J Colón-González ◽  
Alex J Elliot ◽  
Gillian E Smith ◽  
...  
Keyword(s):  
Public Health ◽  
Syndromic Surveillance ◽  
Performance Metrics ◽  
High Specificity ◽  
Outbreak Detection ◽  
Supplementary Information ◽  
Surveillance Systems ◽  
Detection Algorithms ◽  
Aberration Detection ◽  
Wide Range

Abstract Motivation Public health authorities can provide more effective and timely interventions to protect populations during health events if they have effective multi-purpose surveillance systems. These systems rely on aberration detection algorithms to identify potential threats within large datasets. Ensuring the algorithms are sensitive, specific and timely is crucial for protecting public health. Here, we evaluate the performance of three detection algorithms extensively used for syndromic surveillance: the ‘rising activity, multilevel mixed effects, indicator emphasis’ (RAMMIE) method and the improved quasi-Poisson regression-based method known as ‘Farrington Flexible’ both currently used at Public Health England, and the ‘Early Aberration Reporting System’ (EARS) method used at the US Centre for Disease Control and Prevention. We model the wide range of data structures encountered within the daily syndromic surveillance systems used by PHE. We undertake extensive simulations to identify which algorithms work best across different types of syndromes and different outbreak sizes. We evaluate RAMMIE for the first time since its introduction. Performance metrics were computed and compared in the presence of a range of simulated outbreak types that were added to baseline data. Results We conclude that amongst the algorithm variants that have a high specificity (i.e. >90%), Farrington Flexible has the highest sensitivity and specificity, whereas RAMMIE has the highest probability of outbreak detection and is the most timely, typically detecting outbreaks 2–3 days earlier. Availability and implementation R codes developed for this project are available through https://github.com/FelipeJColon/AlgorithmComparison Supplementary information Supplementary data are available at Bioinformatics online.

An Analysis Capability for System of Systems Research

2009 ◽  
Vol 53 (12) ◽  
pp. 814-818
Author(s):  
Elizabeth K. Bowman ◽  
Jeffrey A. Smith
Keyword(s):  
Decision Making ◽  
Human Behavior ◽  
Complex Problem ◽  
System Of Systems ◽  
Systems Of Systems ◽  
Analysis Process ◽  
Systems Research ◽  
Utility Of Information ◽  
Human Decision ◽  
Definition Of

This paper proposes an analysis capability for systems of systems research in military settings. A new approach is needed due to the increasingly complex socio-technical nature of Command and Control (C2). This research seeks to advance the Army analysis process by developing a capability to examine cognitive, social and technical aspects of information sharing and consequential decision making requirement for C2. We first review the definition of system of systems. Next, we establish the agent-based modeling and simulation (ABMS) paradigm as a useful method for analysis because of its facility for exploring large and complex problem spaces. This is followed by some structural issues addressed by ABMS with an emphasis on the challenge of representing human behavior in psychologically plausible ways. We then present one instantiation of ABMS that incorporates a representation of human decision making and the utility of information in a small vignette. We consider the suitability of this ABMS for system of system analyses with respect to how the decision making processes represent human decision making behavior. Finally, we discuss an ongoing approach to improve human behavior representations in the agents of this ABMS.

From Cognitive Theory to Operational Transition: One Program’s Path Across the Valley of Death

2016 ◽  
Vol 60 (1) ◽  
pp. 163-167
Author(s):  
Wayne W Zachary ◽  
Stephen M. Fiore ◽  
Jeffery Morrison ◽  
Josey Wales ◽  
Christopher Wickens
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Cognitive Theory ◽  
Cognitive Engineering ◽  
Practical Application ◽  
End User ◽  
Program Manager ◽  
Human Decision ◽  
Applied Fields ◽  
Valley Of Death

Cognitive engineering and decision support are applied fields that build on cognitive theory and empirical data but ultimately seek to design and build interactive artifacts that improve human decision-making, performance, and use-experiences. However, the path from theory to operational transition has often been very difficult, often ending in failure in a “valley of death” between successful research and successful practical application. This panel presents different perspectives on the trek through this valley – researcher, end-user/operator, program manager, and what-can-we-learn-from-past-failures– set in the issues of current research program making that trip.

scholarly journals Exploration of Face Detection Methods in Digital Images

2019 ◽  
Vol 8 (4) ◽  
pp. 12130-12136
Keyword(s):  
Face Detection ◽  
Digital Images ◽  
Recognition System ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Surveillance Systems ◽  
Human Beings ◽  
Survey Paper ◽  
Wide Range ◽  
The Face

Face detection is a challenging computer vision task that identifies and localizes the faces of human beings from digital images or video streams. It is predominantly the first phase in the process of developing a wide range of face applications such as face recognition, emotion recognition, authentication, surveillance systems etc. The process of face detection is easy from the human perspective but, a complex task for computers that involves searching of the face in variable circumstances of pose, colour, size, occlusion, illumination etc. If the outcome of face detection is intended to be input for another algorithm, an accurate, well informed selection of an appropriate face detection technique is essential because the overall performance of face application is dependent on face detection algorithm’s precision. The survey paper presents a review of three commonly used face detection algorithms available in literature namely Viola Jones, Neural networks (NN) and Local Binary Pattern (LBP) for the purpose of ascertaining the most suitable face detection algorithm to implement for our future work in developing an ‘Online student concentration level recognition system’.

scholarly journals Key elements of infectious disease syndromic surveillance systems: A scoping review

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Stephanie Hughes ◽  
Alex Elliot ◽  
Scott McEwen ◽  
Amy Greer ◽  
Ian Young ◽  
...  
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Data Quality ◽  
Scoping Review ◽  
Syndromic Surveillance ◽  
Public Health Practice ◽  
Data Sources ◽  
Surveillance Systems ◽  
Health Practice ◽  
Wide Range

IntroductionSyndromic surveillance is an alternative type of public healthsurveillance which utilises pre-diagnostic data sources to detectoutbreaks earlier than conventional (laboratory) surveillance andmonitor the progression of illnesses in populations. These systems areoften noted for their ability to detect a wider range of cases in under-reported illnesses, utilise existing data sources, and alert public healthauthorities of emerging crises. In addition, they are highly versatileand can be applied to a wide range of illnesses (communicable andnon-communicable) and environmental conditions. As a result, theirimplementation in public health practice is expanding rapidly. Thisscoping review aimed to identify all existing literature detailing thenecessary components in the defining, creating, implementing, andevaluating stages of human infectious disease syndromic surveillancesystems.MethodsA full scoping review protocol was developeda priori. Theresearch question posed for the review was “What are the essentialelements of a fully functional syndromic surveillance system forhuman infectious disease?” Five bibliographic databases (Pubmed,Scopus, CINAHL, Web of Science, ProQuest) and eleven websites(Google, Public Health Ontario, Public Health England, Public HealthAgency of Canada, Centers for Disease Control and Prevention,European Centre for Disease Prevention and Control, InternationalSociety for Disease Surveillance, Syndromic Surveillance Systems inEurope, Eurosurveillance, Kingston Frontenac, Lennox & AddingtonPublic Health (x2)) were searched for peer-reviewed, government,academic, conference, and book literature. A total of 1237 uniquecitations were identified from this search and uploaded into thescoping review softwareCovidence. The titles and abstracts werescreened for relevance to the subject material, resulting in 142documents for full-text screening. Following this step, 55 documentsremained for data extraction and inclusion in the scoping review. Twoindependent reviewers conducted each step.ResultsThe scoping review identified many essential elements in thedefining, creating, implementing, and evaluating of syndromicsurveillance systems. These included the defining of “syndromicsurveillance”, classification of syndromes, data quality andcompleteness, statistical methods, privacy and confidentialityissues, costs, operational challenges, management composition,collaboration with other public health agencies, and evaluationcriteria. Several benefits and limitations of the systems were alsoidentified, when comparing them to other public health surveillancemethods. Benefits included the timeliness of analyses and reporting,potential cost savings, complementing traditional surveillancemethods, high sensitivity, versatility, ability to perform short- andlong-term surveillance, non-specificity of the systems, ability to fillin gaps of under-reported illnesses, and the collaborations whichare fostered through its platform; limitations included the potentialresources and costs required, inability to replace traditional healthcareand surveillance methods, the false alerts which may occur, non-specificity of the systems, poor data quality and completeness, timelags in analyses, limited effectiveness at detecting smaller-scaleoutbreaks, and privacy issues with accessing data.ConclusionsOver the past decade, syndromic surveillance systems have becomean integral part of public health practice internationally. Their abilityto monitor a wide variety of illnesses and conditions, detect illnessesearlier than traditional surveillance methods, and be created usingexisting data sources make them a valuable public health tool.The results from this scoping review demonstrate the benefits andlimitations and overall role of the systems in public health practice.In addition, this study also shows that a complete set of key elementsare required in order to properly define, create, implement, andevaluate these systems to ensure their effectiveness and performance.

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