scholarly journals Electronic Integrated Disease Surveillance System and Pathogen Asset Control System

2012 ◽  
Vol 79 (2) ◽  
Author(s):  
Tom G. Wahl ◽  
Aleksey V. Burdakov ◽  
Andrey O. Oukharov ◽  
Azamat K. Zhilokov
Keyword(s):  
Control System ◽  
Real Time ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Data Exchange ◽  
Laboratory Data ◽  
World Health ◽  
Open Architecture ◽  
Case Definitions ◽  
Disease Surveillance System

Electronic Integrated Disease Surveillance System (EIDSS) has been used to strengthen and support monitoring and prevention of dangerous diseases within One Health concept by integrating veterinary and human surveillance, passive and active approaches, case-based records including disease-specific clinical data based on standardised case definitions and aggregated data, laboratory data including sample tracking linked to each case and event with test results and epidemiological investigations. Information was collected and shared in secure way by different means: through the distributed nodes which are continuously synchronised amongst each other, through the web service, through the handheld devices. Electronic Integrated Disease Surveillance System provided near real time information flow that has been then disseminated to the appropriate organisations in a timely manner. It has been used for comprehensive analysis and visualisation capabilities including real time mapping of case events as these unfold enhancing decision making. Electronic Integrated Disease Surveillance System facilitated countries to comply with the IHR 2005 requirements through a data transfer module reporting diseases electronically to the World Health Organisation (WHO) data center as well as establish authorised data exchange with other electronic system using Open Architecture approach. Pathogen Asset Control System (PACS) has been used for accounting, management and control of biological agent stocks. Information on samples and strains of any kind throughout their entire lifecycle has been tracked in a comprehensive and flexible solution PACS.Both systems have been used in a combination and individually. Electronic Integrated Disease Surveillance System and PACS are currently deployed in the Republics of Kazakhstan, Georgia and Azerbaijan as a part of the Cooperative Biological Engagement Program (CBEP) sponsored by the US Defense Threat Reduction Agency (DTRA).

Disease Surveillance System for Big Climate Data Processing and Dengue Transmission

2017 ◽  
Vol 8 (2) ◽  
pp. 88-105 ◽  
Author(s):  
Gunasekaran Manogaran ◽  
Daphne Lopez
Keyword(s):  
Climate Change ◽  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Sensor Data ◽  
Climate Data ◽  
The Real ◽  
Disease Surveillance System

Ambient intelligence is an emerging platform that provides advances in sensors and sensor networks, pervasive computing, and artificial intelligence to capture the real time climate data. This result continuously generates several exabytes of unstructured sensor data and so it is often called big climate data. Nowadays, researchers are trying to use big climate data to monitor and predict the climate change and possible diseases. Traditional data processing techniques and tools are not capable of handling such huge amount of climate data. Hence, there is a need to develop advanced big data architecture for processing the real time climate data. The purpose of this paper is to propose a big data based surveillance system that analyzes spatial climate big data and performs continuous monitoring of correlation between climate change and Dengue. Proposed disease surveillance system has been implemented with the help of Apache Hadoop MapReduce and its supporting tools.

scholarly journals Australian National Enterovirus Reference Laboratory annual report, 2017

2020 ◽  
Vol 44 ◽  
Author(s):  
Jason A Roberts ◽  
Linda K Hobday ◽  
Aishah Ibrahim ◽  
Bruce R Thorley
Keyword(s):  
Surveillance System ◽  
Disease Surveillance ◽  
Performance Criterion ◽  
World Health ◽  
Reference Laboratory ◽  
Surveillance Systems ◽  
Disease Surveillance System ◽  
Enterovirus A71 ◽  
Clinical Surveillance ◽  
Health Organization

Australia monitors its polio-free status by conducting surveillance for cases of acute flaccid paralysis (AFP) in children less than 15 years of age, as recommended by the World Health Organization (WHO). Cases of AFP in children are notified to the Australian Paediatric Surveillance Unit or the Paediatric Active Enhanced Disease Surveillance System and faecal specimens are referred for virological investigation to the National Enterovirus Reference Laboratory. In 2017, no cases of poliomyelitis were reported from clinical surveillance and Australia reported 1.33 non-polio AFP cases per 100,000 children, meeting the WHO performance criterion for a sensitive surveillance system. Three non-polio enteroviruses, coxsackievirus B1, echovirus 11 and enterovirus A71, were identified from clinical specimens collected from AFP cases. Australia established enterovirus and environmental surveillance systems to complement the clinical system focussed on children and an ambiguous vaccine-derived poliovirus type 2 was isolated from sewage in Melbourne. In 2017, 22 cases of wild polio were reported with three countries remaining endemic: Afghanistan, Nigeria and Pakistan.

scholarly journals The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Lisa Lix ◽  
James Ayles ◽  
Sharon Bartholomew ◽  
Charmaine Cooke ◽  
Joellyn Ellison ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Health Agency ◽  
Population Based ◽  
Population Characteristics ◽  
Administrative Databases ◽  
Distributed Model ◽  
Case Definitions ◽  
Disease Surveillance System

Chronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageous because it does not require individual-level data to be shared across jurisdictional boundaries. Our objective is to describe the process, structure, benefits, and challenges of a distributed model for chronic disease surveillance across all Canadian provinces and territories (P/Ts) using linked administrative data. The Public Health Agency of Canada (PHAC) established the Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to facilitate standardized, national estimates of chronic disease prevalence, incidence, and outcomes. The CCDSS primarily relies on linked health insurance registration files, physician billing claims, and hospital discharge abstracts. Standardized case definitions and common analytic protocols are applied to the data for each P/T; aggregate data are shared with PHAC and summarized for reports and open access data initiatives. Advantages of this distributed model include: it uses the rich data resources available in all P/Ts; it supports chronic disease surveillance capacity building in all P/Ts; and changes in surveillance methodology can be easily developed by PHAC and implemented by the P/Ts. However, there are challenges: heterogeneity in administrative databases across jurisdictions and changes in data quality over time threaten the production of standardized disease estimates; a limited set of databases are common to all P/Ts, which hinders potential CCDSS expansion; and there is a need to balance comprehensive reporting with P/T disclosure requirements to protect privacy. The CCDSS distributed model for chronic disease surveillance has been successfully implemented and sustained by PHAC and its P/T partners. Many lessons have been learned about national surveillance involving jurisdictions that are heterogeneous with respect to healthcare databases, expertise and analytical capacity, population characteristics, and priorities.

scholarly journals Spatiotemporal analysis of the first wave of COVID-19 hospitalisations in Birmingham, UK

BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e050574
Author(s):  
Samuel I Watson ◽  
Peter J Diggle ◽  
Michael G Chipeta ◽  
Richard J Lilford
Keyword(s):  
Disease Control ◽  
Real Time ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Temporal Correlation ◽  
Spatiotemporal Analysis ◽  
Control Measures ◽  
University Hospitals ◽  
Disease Surveillance System ◽  
Local Areas

ObjectivesTo evaluate the spatiotemporal distribution of the incidence of COVID-19 hospitalisations in Birmingham, UK during the first wave of the pandemic to support the design of public health disease control policies.DesignA geospatial statistical model was estimated as part of a real-time disease surveillance system to predict local daily incidence of COVID-19.ParticipantsAll hospitalisations for COVID-19 to University Hospitals Birmingham NHS Foundation Trust between 1 February 2020 and 30 September 2020.Outcome measuresPredictions of the incidence and cumulative incidence of COVID-19 hospitalisations in local areas, its weekly change and identification of predictive covariates.ResultsPeak hospitalisations occurred in the first and second weeks of April 2020 with significant variation in incidence and incidence rate ratios across the city. Population age, ethnicity and socioeconomic deprivation were strong predictors of local incidence. Hospitalisations demonstrated strong day of the week effects with fewer hospitalisations (10%–20% less) at the weekend. There was low temporal correlation in unexplained variance. By day 50 at the end of the first lockdown period, the top 2.5% of small areas had experienced five times as many cases per 10 000 population as the bottom 2.5%.ConclusionsLocal demographic factors were strong predictors of relative levels of incidence and can be used to target local areas for disease control measures. The real-time disease surveillance system provides a useful complement to other surveillance approaches by producing real-time, quantitative and probabilistic summaries of key outcomes at fine spatial resolution to inform disease control programmes.

scholarly journals Success in Revitalizing Weekly Disease Surveillance System in Zimbabwe Using Cell-phone Mediated Data Transmission, 2009-2013

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Henry Chidawanyika ◽  
Ponesai Nyika ◽  
Joshua Katiyo ◽  
Anthony Sox ◽  
Tongai Chokuda ◽  
...  
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Cell Phone ◽  
Cell Phones ◽  
Decision Makers ◽  
Surveillance Data ◽  
Innovative Approach ◽  
Disease Surveillance System

Innovative approach to revitalizing Disease Surveillance System in Zimbabwe using cell-phone mediated data transmission has been a huge success. Cell phones have been successfully integrated into disease surveillance system resulting in expansion of surveillance coverage, improved completeness and timeliness. Decision makers are now able to access disease surveillance data in near real-time.

Open Architecture of Robot Control System Based on PROFI-BUS

2009 ◽  
Vol 419-420 ◽  
pp. 581-584
Author(s):  
Xiao Dong Tan ◽  
Feng Tan ◽  
Kun Zhang ◽  
Bao Liang Li
Keyword(s):  
Control System ◽  
Real Time ◽  
Robot Control ◽  
Data Exchange ◽  
Modular Design ◽  
Industrial Robot ◽  
Open Architecture ◽  
Field Bus ◽  
Real Time System ◽  
Robot Control System

A PROFI-BUS based industrial robot control system is introduced from the viewpoint of both software and hardware. It is discussed about how to use PC technology and field-bus technology to design an open robot control system. The system adopts a three- layer structure, which is mainly configured with universal control devices, to realize a modular and universal design. A high-speed field-bus is designed for connecting servo system and IPC, to ensure real-time capability; another low-speed Field-bus is used to connect IPC and PLC, HMI, teaching panel and other devices for data exchange, while reducing the occupancy of system resources. The software system adopts the modular design with Windows NT and RTX, which fully exploits the powerful functions of Window NT system and meets the requirements of real-time system. This open structure greatly enhances the system's flexibility and openness.

scholarly journals Australian National Enterovirus Reference Laboratory annual report, 2020

2021 ◽  
Vol 45 ◽  
Author(s):  
Matthew B Kaye ◽  
Arnau Garcia-Clapes ◽  
Linda K Hobday ◽  
Aishah Ibrahim ◽  
Presa Chanthalavanh ◽  
...  
Keyword(s):  
Surveillance System ◽  
Disease Surveillance ◽  
Performance Criterion ◽  
World Health ◽  
Reference Laboratory ◽  
Wild Poliovirus ◽  
Disease Surveillance System ◽  
Clinical Surveillance ◽  
Health Organization ◽  
Free Status

Australia monitors its polio-free status by conducting surveillance for cases of acute flaccid paralysis (AFP) in children less than 15 years of age, as recommended by the World Health Organization (WHO). Cases of AFP in children are notified to the Australian Paediatric Surveillance Unit or the Paediatric Active Enhanced Disease Surveillance System and faecal specimens are referred for virological investigation to the National Enterovirus Reference Laboratory. In 2020, no cases of poliomyelitis were reported from clinical surveillance; Australia reported 1.09 non-polio AFP cases per 100,000 children, thereby meeting the WHO’s performance criterion for a sensitive surveillance system. The non-polio enteroviruses coxsackievirus A10 and coxsackievirus A16 were identified from clinical specimens collected from AFP cases. Australia also performs enterovirus surveillance and environmental surveillance to complement the clinical system focussed on children. In 2020, there were 140 cases of wild poliovirus reported from the two remaining endemic countries: Afghanistan and Pakistan. Another 28 countries reported cases of circulating vaccine-derived poliovirus.

scholarly journals The Canadian Chronic Disease Surveillance System: A Distributed Surveillance Model

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Lisa Lix ◽  
Kim Reimer
Keyword(s):  
Health Insurance ◽  
Chronic Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Feasibility Studies ◽  
Mental Illnesses ◽  
Population Characteristics ◽  
Case Definitions ◽  
Disease Surveillance System ◽  
Disease Case

ObjectiveTo describe the process, benefits, and challenges of implementinga distributed model for chronic disease surveillance across thirteenCanadian jurisdictions.IntroductionThe Public Health Agency of Canada (PHAC) established theCanadian Chronic Disease Surveillance System (CCDSS) in 2009 tofacilitate national estimates of chronic disease prevalence, incidence,and health outcomes. The CCDSS uses population-based linkedhealth administrative databases from all provinces/territories (P/Ts)and a distributed analytic protocol to produce standardized diseaseestimates.MethodsThe CCDSS is founded on deterministic linkage of threeadministrative health databases in each Canadian P/T: health insuranceregistration files, physician billing claims, and hospital dischargeabstracts. Data on all residents who are eligible for provincial orterritorial health insurance (about 97% of the Canadian population) arecaptured in the health insurance registration files. Thus, the CCDSScoverage is near-universal. Disease case definitions are developed byexpert Working Groups after literature reviews are completed andvalidation studies are undertaken. Feasibility studies are initiatedin selected P/Ts to identify challenges when implementing thedisease case definitions. Analytic code developed by PHAC is thendistributed to all P/Ts. Data quality surveys are routinely conductedto identify database characteristics that may bias disease estimatesover time or across P/Ts or affect implementation of the analytic code.The summary data produced in each P/T are approved by ScientificCommittee and Technical Committee members and then submitted toPHAC for further analysis and reporting.ResultsNational surveillance or feasibility studies are currently ongoing fordiabetes, hypertension, selected mental illnesses, chronic respiratorydiseases, heart disease, neurological conditions, musculoskeletalconditions, and stroke. The advantages of the distributed analyticprotocol are (Figure 1): (a) changes in methodology can be easilymade, and (b) technical expertise to implement the methodology is notrequired in each P/T. Challenges in the use of the distributed analyticprotocol are: (a) heterogeneity in healthcare databases across P/Tsand over time, (b) the requirement that each P/T use the minimum setof data elements common to all jurisdictions when producing diseaseestimates, and (c) balancing disclosure guidelines to ensure dataconfidentiality with comprehensive reporting. Additional challenges,which include incomplete data capture for some databases and poormeasurement validity of disease diagnosis codes for some chronicconditions, must be continually addressed to ensure the scientificrigor of the CCDSS methodology.ConclusionsThe CCDSS distributed analytic protocol offers one model fornational chronic disease surveillance that has been successfullyimplemented and sustained by PHAC and its P/T partners. Manylessons have been learned about national chronic disease surveillanceinvolving jurisdictions that are heterogeneous with respect tohealthcare databases, expertise, and population characteristics.

Disease Surveillance System for Big Climate Data Processing and Dengue Transmission

Web Services ◽  
2019 ◽  
pp. 490-509 ◽  
Author(s):  
Gunasekaran Manogaran ◽  
Daphne Lopez
Keyword(s):  
Climate Change ◽  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Sensor Data ◽  
Climate Data ◽  
The Real ◽  
Disease Surveillance System

Ambient intelligence is an emerging platform that provides advances in sensors and sensor networks, pervasive computing, and artificial intelligence to capture the real time climate data. This result continuously generates several exabytes of unstructured sensor data and so it is often called big climate data. Nowadays, researchers are trying to use big climate data to monitor and predict the climate change and possible diseases. Traditional data processing techniques and tools are not capable of handling such huge amount of climate data. Hence, there is a need to develop advanced big data architecture for processing the real time climate data. The purpose of this paper is to propose a big data based surveillance system that analyzes spatial climate big data and performs continuous monitoring of correlation between climate change and Dengue. Proposed disease surveillance system has been implemented with the help of Apache Hadoop MapReduce and its supporting tools.

scholarly journals Assessment of the core functions of hepatitis B surveillance system in the southeastern Iran: a qualitative study

2019 ◽  
Author(s):  
Mozhgan Mahmoodi ◽  
Abbas Yazdanpanah ◽  
Abbas Ghavam ◽  
Khodadad Sheikhzadeh
Keyword(s):  
Hepatitis B ◽  
World Health Organization ◽  
Surveillance System ◽  
Disease Surveillance ◽  
High Efficiency ◽  
World Health ◽  
The Core ◽  
Disease Surveillance System ◽  
Content Analysis Method ◽  
Health Organization

Introduction: Viral hepatitis has been declared as one of the major health problems by World Health Organization. Hepatitis B surveillance system is one of the most important tools for managing the disease and achieving the targets of disease elimination. Despite its high efficiency, hepatitis B surveillance system has always been faced with many challenges. Therefore, the present study aimed to investigate the core functions of the hepatitis B surveillance system in southeastern region of Iran. Method: Semi-structured in-depth interviews were conducted with 14 hepatitis B surveillance experts in five counties of Sistan and Baluchestan Province, southeast Iran. The data were analyzed using content analysis method, based on the structure of the disease surveillance system. Purposeful sampling method was carried out and continued until saturation of the themes was achieved. Results: The main studied themes were case finding, case reporting, case registration, case confirmation, data analysis, sending feedback, and implementing interventions. The results of this study showed that all of the core functions of the hepatitis B surveillance system were running in the studied counties, although they did not meet the relevant standards in some cases. Conclusion: It seemed that, despite the numerous efforts and activities, it was still far from reaching the targets of the program. Considering the goal of World Health Organization to eliminate hepatitis B by 2030, it is essential to address these challenges and make attempt to overcome them.

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