scholarly journals Critical issues in implementing a national integrated all-vaccine preventable disease surveillance system

Vaccine ◽  
2013 ◽  
Vol 31 ◽  
pp. C94-C98 ◽  
Author(s):  
Terri B. Hyde ◽  
Jon K. Andrus ◽  
Vance J. Dietz ◽  
Jon K. Andrus ◽  
Terri B. Hyde ◽  
...  
Vaccine ◽  
2013 ◽  
Vol 31 ◽  
pp. C88-C93 ◽  
Author(s):  
C.M. Toscano ◽  
M. Vijayaraghavan ◽  
H.M. Salazar-Bolaños ◽  
H.M. Bolaños-Acuña ◽  
A.I. Ruiz-González ◽  
...  

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
F Magurano ◽  
M Baggieri ◽  
P Bucci ◽  
E D'Ugo ◽  
M Sabbatucci ◽  
...  

Abstract Background Measles is a vaccine-preventable infectious disease and it remains one of the leading causes of infant mortality globally. The World Health Organization (WHO) has adopted the goal of eliminating measles and rubella. Detection and control of communicable diseases would not be possible without accurate laboratory results regarding when and where a particular disease circulates. Methods WHO/Europe therefore works with all Member States to steadily improve the quality of the laboratory data in order to determine the Region's progress towards measles and rubella elimination. For this purpose coordinates the European Measles and Rubella Laboratory Network (MR LabNet). National labs in this network undergoes regular external quality assessment through an annual accreditation programme. Results In Italy, a Sub-national Reference Laboratories Network for measles and rubella (MoRoNET) has been developed since March 2017 and currently includes 15 laboratories. MoRoNet was developed following the indications of the MR LabNet. It is accreditate, coordinated and supervised by the National Reference Laboratory. Conclusions Strengthening the role of national laboratories in overseeing the performance of subnational laboratories has become a critical need in order to properly monitor the Region's measles and rubella elimination efforts. MoRoNet permits to Italy to develop a country-specific work plan for establishing national networks and oversight mechanism, including preliminary monitoring and evaluation indicators compliant with MR LabNet standards. This is very significant not only to optimize the participation in national and regional processes to verify disease elimination, but also to strengthen the quality of vaccine-preventable disease surveillance. MoRoNet Group: A Amendola; F Baldanti; MR Capobianchi; M Chironna; MG Cusi; P D'Agaro; P Lanzafame; T Lazzarotto; K Marinelli; A Orsi; E Pagani; G Palù; F Pittaluga, A Sacchi; F Tramuto. Key messages MoRoNet has permitted to Italy to develop a country-specific work plan for establishing national networks and oversight mechanism, compliant with WHO MR LabNet standards. MoRoNet network has permitted to optimize the participation in processes to verify disease elimination, but also to strengthen the quality of vaccine-preventable disease surveillance.


2021 ◽  
Vol 64 (5) ◽  
pp. 338-357
Author(s):  
Natalie Troke ◽  
Chloë Logar‐Henderson ◽  
Nathan DeBono ◽  
Mamadou Dakouo ◽  
Selena Hussain ◽  
...  

2017 ◽  
Vol 8 (2) ◽  
pp. 88-105 ◽  
Author(s):  
Gunasekaran Manogaran ◽  
Daphne Lopez

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.


2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Revati K Phalkey ◽  
Sharvari Shukla ◽  
Savita Shardul ◽  
Nutan Ashtekar ◽  
Sapna Valsa ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document