scholarly journals Evaluation of an Electronic Smart-Card Based School Absenteeism Surveillance System

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Dennis Ip ◽  
Eric H.Y. Lau ◽  
Yat-hung Tam ◽  
Teresa So ◽  
Chi-kin Lam ◽  
...  
Keyword(s):  
Smart Card ◽  
Surveillance System ◽  
Data Stream ◽  
Potential Benefit ◽  
Cost Effective ◽  
Emerging Diseases ◽  
Surveillance Systems ◽  
School Absenteeism ◽  
Community Settings ◽  
Card System

We evaluated the performance of an electronic smart-card based school absenteeism surveillance system which was initiated in 2008 in Hong Kong. The result demonstrated the feasibility and potential benefit of employing electronic school absenteeism data as captured automatically by a smart card system as an alternative data stream for monitoring influenza activities, and flexibility in establishing surveillance for emerging diseases. The increasing popularity of usage of smart card technology in various community settings might also represent potentially timely and cost-effective opportunities for innovative surveillance systems.

Systematic review of surveillance systems and methods for early detection of exotic, new and re-emerging diseases in animal populations

2014 ◽  
Vol 143 (10) ◽  
pp. 2018-2042 ◽  
Author(s):  
V. RODRÍGUEZ-PRIETO ◽  
M. VICENTE-RUBIANO ◽  
A. SÁNCHEZ-MATAMOROS ◽  
C. RUBIO-GUERRI ◽  
M. MELERO ◽  
...  
Keyword(s):  
Public Health ◽  
Systematic Review ◽  
Early Detection ◽  
Literature Review ◽  
Cost Effective ◽  
Emerging Diseases ◽  
Detection Methods ◽  
Surveillance Systems ◽  
Animal Populations ◽  
Globalized World

SUMMARYIn this globalized world, the spread of new, exotic and re-emerging diseases has become one of the most important threats to animal production and public health. This systematic review analyses conventional and novel early detection methods applied to surveillance. In all, 125 scientific documents were considered for this study. Exotic (n = 49) and re-emerging (n = 27) diseases constituted the most frequently represented health threats. In addition, the majority of studies were related to zoonoses (n = 66). The approaches found in the review could be divided in surveillance modalities, both active (n = 23) and passive (n = 5); and tools and methodologies that support surveillance activities (n = 57). Combinations of surveillance modalities and tools (n = 40) were also found. Risk-based approaches were very common (n = 60), especially in the papers describing tools and methodologies (n = 50). The main applications, benefits and limitations of each approach were extracted from the papers. This information will be very useful for informing the development of tools to facilitate the design of cost-effective surveillance strategies. Thus, the current literature review provides key information about the advantages, disadvantages, limitations and potential application of methodologies for the early detection of new, exotic and re-emerging diseases.

scholarly journals Avian Flu, Ebola, MERS, and Other Emerging Challenges for Influenza Surveillance Practitioners

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Alan Siniscalchi ◽  
Brooke Evans
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Ebola Virus ◽  
Virus Disease ◽  
Cost Effective ◽  
Emerging Diseases ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Public Health Agencies ◽  
Public Health Practitioners

Public health agencies strive to develop and maintain cost-effective disease surveillance systems to better understand the burden of disease within their jurisdiction. The emergence of novel avian influenza and other respiratory viruses such as MERS-CoV along with other emerging diseases including Ebola virus disease offer new challenges to public health practitioners. The authors conducted a series of surveys of influenza surveillance coordinators to identify and define these challenges. The results emphasize the importance of maintaining sufficient infrastructure and the trained personnel needed to operate these surveillance systems for optimal disease detection and public health preparedness and response readiness.

scholarly journals Ebola, Enterovirus, MERS, Novel Flu, and other Challenges for Public Health Surveillance Practitioners

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Alan Siniscalchi ◽  
Brooke Evans
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Ebola Virus ◽  
Virus Disease ◽  
Cost Effective ◽  
Emerging Diseases ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Public Health Agencies ◽  
Public Health Practitioners

Public health agencies strive to develop and maintain cost-effective disease surveillance systems to better understand the burden of disease within their jurisdiction. The emergence of novel influenza and other respiratory viruses such as MERS-CoV along with other emerging diseases including Ebola virus disease offer new challenges to public health practitioners. The authors conducted a series of surveys of influenza surveillance coordinators to identify and define these challenges. The results emphasize the importance of maintaining sufficient infrastructure and the trained personnel needed to operate these surveillance systems for optimal disease detection and public health preparedness and response readiness.

scholarly journals Optimising passive surveillance of a neglected tropical disease in the era of elimination: A modelling study

2020 ◽  
Author(s):  
Joshua Longbottom ◽  
Charles Wamboga ◽  
Paul R. Bessell ◽  
Steve J. Torr ◽  
Michelle C. Stanton
Keyword(s):  
Infectious Diseases ◽  
Disease Surveillance ◽  
Human African Trypanosomiasis ◽  
Cost Effective ◽  
Emerging Diseases ◽  
Surveillance Systems ◽  
Passive Surveillance ◽  
Resistance Surface ◽  
Western Uganda ◽  
North Western

AbstractBackgroundSurveillance is an essential component of global programs to eliminate infectious diseases and avert epidemics of (re-)emerging diseases. As the numbers of cases decline, costs of treatment and control diminish but those for surveillance remain high even after the ‘last’ case. Reducing surveillance may risk missing persistent or (re-)emerging foci of disease. Here, we use a simulation-based approach to determine the minimal number of passive surveillance sites required to ensure maximum coverage of a population at-risk (PAR) of an infectious disease.Methodology and Principal FindingsFor this study, we use Gambian human African trypanosomiasis (g-HAT) in north-western Uganda, a neglected tropical disease (NTD) which has been reduced to historically low levels (<1000 cases/year globally), as an example. To quantify travel time to diagnostic facilities, a proxy for surveillance coverage, we produced a high spatial-resolution resistance surface and performed cost-distance analyses. We simulated travel time for the PAR with different numbers (1-170) and locations (170,000 total placement combinations) of diagnostic facilities, quantifying the percentage of the PAR within 1h and 5h travel of the facilities, as per in-country targets. Our simulations indicate that a 70% reduction (51/170) in diagnostic centres still exceeded minimal targets of coverage even for remote populations, with >95% of a total PAR of ~3million individuals living ≤1h from a diagnostic centre, and we demonstrate an approach to best place these facilities, informing a minimal impact scale back.ConclusionsOur results highlight that surveillance of g-HAT in north-western Uganda can be scaled back without reducing coverage of the PAR. The methodology described can contribute to cost-effective and equable strategies for the surveillance of NTDs and other infectious diseases approaching elimination or (re-)emergence.Author SummaryDisease surveillance systems are an essential component of public health practice and are often considered the first line in averting epidemics for (re-)emerging diseases. Regular evaluation of surveillance systems ensures that they remain operating at maximum efficiency; systems that survey diseases of low incidence, such as those within elimination settings, should be simplified to reduce the reporting burden. A lack of guidance on how to optimise disease surveillance in an elimination setting may result in added expense, and/or the underreporting of disease. Here, we propose a framework methodology to determine systematically the optimal number and placement of surveillance sites for the surveillance of infectious diseases approaching elimination. By utilising estimates of geographic accessibility, through the construction of a resistance surface and a simulation approach, we identify that the number of operational diagnostic facilities for Gambian human African trypanosomiasis in north-western Uganda can be reduced by 70% without affecting existing coverage, and identify the minimum number of facilities required to meet coverage targets. Our analysis can be used to inform the number and positioning of surveillance sites for diseases within an elimination setting. Passive surveillance becomes increasingly important as cases decline and active surveillance becomes less cost-effective; methods to evaluate how best to engage this passive surveillance capacity given facility capacity and geographic distribution are pertinent for several NTDs where diagnosis is complex. Not only is this a complicated research area for diseases approaching elimination, a well-designed surveillance system is essential for the detection of emerging diseases, with this work being topical in a climate where emerging pathogens are becoming more commonplace.

scholarly journals An Event-Driven Multiple Objects Surveillance System

2018 ◽  
Vol 9 (1) ◽  
pp. 35-44 ◽  
Author(s):  
Saeed Mina Qaisar ◽  
Dija Sidiya ◽  
Mohammad Akbar ◽  
Abdulhamit Subasi
Keyword(s):  
Power Consumption ◽  
Surveillance System ◽  
Cost Effective ◽  
Self Organization ◽  
False Alarms ◽  
Sleep Mode ◽  
Surveillance Systems ◽  
Effective Combination ◽  
Event Driven ◽  
Processing Activity

Traditional surveillance systems are constrained because of a fixed and preset pattern of monitoring. It can reduce the reliability of the system and cause an increased generation of false alarms. It results in an increased processing activity of the system, which causes an augmented consumption of system resources and power. Within this framework, a human surveillance system is proposed based on the event-driven awakening and self-organization principle. The proposed system overcomes these downsides up to a certain level. It is achieved by intelligently merging an assembly of sensors with two cameras, actuators, a lighting module and cost-effective embedded processors. With the exception of low-power event detectors, all other system modules remain in the sleep mode. These modules are activated only upon detection of an event and as a function of the sensing environment condition. It reduces power consumption and processing activity of the proposed system. An effective combination of a sensor assembly and a robust classifier suppresses generation of false alarms and improves system reliability. An experimental setup is realized in order to verify the functionality of the proposed system. Results confirm proper functionality of the implemented system. A 62.3-fold system memory utilization and bandwidth consumption reduction compared to traditional counterparts is achieved, i.e. a result of the proposed system self-organization and event-driven awakening features. It confirms that the proposed system outperforms its classical counterparts in terms of processing activity, power consumption and usage of resources

From Subsurface to Riser: An Integrated Approach to Subsea Surveillance

2010 ◽  
Author(s):  
Jon Machin
Keyword(s):  
Surveillance System ◽  
Production Control ◽  
High Reliability ◽  
Cost Effective ◽  
Integrated Approach ◽  
Production Optimization ◽  
Surveillance Systems ◽  
Physical Layers ◽  
Key Enabling Technologies ◽  
Reliability Performance

The high reliability performance of a subsea surveillance system, from subsurface to riser, is of the utmost importance for maximizing production availability. In designing such a surveillance system, there are a multitude of considerations that need to be addressed. These have traditionally focused on safe and cost effective production control system availability. However, they are now being extended to also address enablers for secondary recovery, production optimization, and increased recovery activities. This paper addresses the idea that latest-generation surveillance systems must operate seamlessly from the subsurface to the seabed and in turn from seabed to riser. In doing so they must integrate a number of key enabling technologies over different physical layers and predefined technical interfaces. They must also serve to integrate these technologies over the project management interfaces which arise from the selection of the different proprietary technologies, and the commercial and contractual barriers which can result.

Quality Assessment of Hospital Discharge Database for Routine Surveillance of Hip and Knee Arthroplasty–Related Infections

2014 ◽  
Vol 35 (6) ◽  
pp. 646-651 ◽  
Author(s):  
Leslie Grammatico-Guillon ◽  
Sabine Baron ◽  
Christophe Gaborit ◽  
Emmanuel Rusch ◽  
Pascal Astagneau
Keyword(s):  
Hospital Discharge ◽  
Knee Arthroplasty ◽  
Predictive Value ◽  
Surveillance System ◽  
Cost Effective ◽  
International Classification Of Diseases ◽  
Case Definition ◽  
Surveillance Systems ◽  
Routine Surveillance ◽  
Hospital Stays

Objective.Surgical site infection (SSI) surveillance represents a key method of nosocomial infection control programs worldwide. However, most SSI surveillance systems are considered to be poorly cost effective regarding human and economic resources required for data collection and patient follow up. This study aims to assess the efficacy of using hospital discharge databases (HDDs) as a routine surveillance system for detecting hip or knee arthroplasty–related infections (HKAIs).Methods.A case-control study was conducted among patients hospitalized in the Centre region of France between 2008 and 2010. HKAI cases were extracted from the HDD with various algorithms based on the International Classification of Diseases, Tenth Revision, and procedure codes. The control subjects were patients with hip or knee arthroplasty (HKA) without infection selected at random from the HDD during the study period. The gold standard was medical chart review. Sensitivity (Se), specificity (Spe), positive predictive value (PPV), and negative predictive value (NPV) were calculated to evaluate the efficacy of the surveillance system.Results.Among 18,265 hospital stays for HKA, corresponding to 17,388 patients, medical reports were checked for 1,010 hospital stays (989 patients). We identified 530 cases in total (incidence rate, 1% [95% confidence interval (CI), 0.4%–1.6%), and 333 cases were detected by routine surveillance. As compared with 480 controls, Se was 98%, Spe was 71%, PPV was 63%, and NPV was 99%. Using a more specific case definition, based on a sample of 681 hospital stays, Se was 97%, Spe was 95%, PPV was 87%, and NPV was 98%.Conclusions.This study demonstrates the potential of HDD as a tool for routine SSI surveillance after low-risk surgery, under conditions of having an appropriate algorithm for selecting infections.Infect Control Hosp Epidemiol 2014;35(6):646–651

scholarly journals Observing the Unobserved: A Newspaper Based Dengue Surveillance System for the Low-Income Regions of Bangladesh

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Nazia Tasnim ◽  
Md. Istiak Hossain Shihab ◽  
Moqsadur Rahman ◽  
Jillur Rahman Saurav ◽  
Sheikh Rabiul Islam ◽  
...  
Keyword(s):  
Low Income ◽  
Surveillance System ◽  
Temporal Trends ◽  
Ground Truth ◽  
Cost Effective ◽  
Emerging Diseases ◽  
Medical Expenditure ◽  
High Morbidity ◽  
Potential Control ◽  
Spatio Temporal

Dengue is one of the emerging diseases of this century, which established itself as both endemic and epidemic - particularly in the tropical and subtropical-regions. Because of its high morbidity and mortality rates, Dengue is a significant economic and health burden for middle to lower-income countries. The lack of a stable, cost-effective, and suitable surveillance system has made the identification of dengue zones and designing potential control programs very challenging. As a result, it is not feasible to assess the effect of the intervention actions properly. Therefore, most of the prevention and mitigation efforts by the associated health officials are failing. In this work, we chose Bangladesh, a developing country from the South-East Asia region with its occasional history of dengue outbreaks and with a high out-of-pocket medical expenditure, as a use case. We use some well known data-mining techniques on the local newspapers, written in Bengali, to unearth valuable insights and develop a dengue news surveillance system. We categorize dengue-news and detect the spatio-temporal trends among crucial variables. Our technique provides an f-score of 91.45\% and very closely follows the ground truth of reported cases. Additionally, we identify the under-reported regions of the country effectively while establishing a meaningful relationship between complex socio-economic factors and reporting of dengue.

scholarly journals Early detection of wildlife morbidity and mortality through an event-based surveillance system

2021 ◽  
Vol 288 (1954) ◽  
pp. 20210974
Author(s):  
Terra R. Kelly ◽  
Pranav S. Pandit ◽  
Nicole Carion ◽  
Devin F. Dombrowski ◽  
Krysta H. Rogers ◽  
...  
Keyword(s):  
Early Detection ◽  
Language Processing ◽  
Clinical Data ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Emerging Diseases ◽  
Wildlife Disease ◽  
Morbidity And Mortality ◽  
Added Value ◽  
Surveillance Systems

The ability to rapidly detect and respond to wildlife morbidity and mortality events is critical for reducing threats to wildlife populations. Surveillance systems that use pre-diagnostic clinical data can contribute to the early detection of wildlife morbidities caused by a multitude of threats, including disease and anthropogenic disturbances. Here, we demonstrate proof of concept for use of a wildlife disease surveillance system, the ‘Wildlife Morbidity and Mortality Event Alert System’, that integrates pre-diagnostic clinical data in near real-time from a network of wildlife rehabilitation organizations, for early and enhanced detection of unusual wildlife morbidity and mortality events. The system classifies clinical pre-diagnostic data into relevant clinical classifications based on a natural language processing algorithm, generating alerts when more than the expected number of cases is recorded across the rehabilitation network. We demonstrated the effectiveness and efficiency of the system in alerting to events associated with both common and emerging diseases. Tapping into this readily available unconventional general surveillance data stream offers added value to existing wildlife disease surveillance programmes through a relatively efficient, low-cost strategy for the early detection of threats.

Situational Strategic Awareness Monitoring Surveillance System–Microcomputer and Microcomputer Clustering used for Intelligent, Economical, Scalable, and Deployable Approach for Safeguarding Materials

2020 ◽  
Vol 2020 (3) ◽  
pp. 60408-1-60408-10
Author(s):  
Kenly Maldonado ◽  
Steve Simske
Keyword(s):  
Surveillance System ◽  
Cost Effective ◽  
Government Agencies ◽  
Electronic Systems ◽  
Time Data ◽  
Potential Threat ◽  
Intelligent Surveillance ◽  
World Markets ◽  
Programming Software ◽  
And Control

The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.

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