scholarly journals Leapfrogging with technology: introduction of a monitoring platform to support a large-scale Ebola vaccination program in Rwanda

2021 ◽  
pp. 1-11
Author(s):  
Paula Mc Kenna ◽  
Serge Masyn ◽  
Annik Willems ◽  
Anne De Paepe ◽  
Romain Rutten ◽  
...  
Keyword(s):  
Large Scale ◽  
Vaccination Program ◽  
Technology Introduction ◽  
Monitoring Platform

scholarly journals COVID-19 Vaccination of HCWs in the First Phase of a Large-Scale Mass Vaccination Program within a Healthcare System

2021 ◽  
Vol 1 (S1) ◽  
pp. s11-s11
Author(s):  
Kimberly Korwek ◽  
E. Jackie Blanchard ◽  
Julia Moody ◽  
Katherine Lange ◽  
Ryan Sledge ◽  
...  
Keyword(s):  
Human Resources ◽  
Healthcare Workers ◽  
Large Scale ◽  
Rapid Development ◽  
Vaccination Strategy ◽  
State Level ◽  
Mass Vaccination ◽  
Vaccine Uptake ◽  
Vaccination Program ◽  
Vaccination Rates

Background: The approval of the first SARS-COV-2 vaccines for COVID-19 were accompanied by unprecedented efforts to provide vaccination to healthcare workers and first responders. More information about vaccine uptake in this group is needed to better refine and target educational messaging. Methods: HCA Healthcare used federal guidance and internal experience to create a systemwide mass vaccination strategy. A closed point-of-dispensing (POD) model was developed and implemented. The previously developed enterprise-wide emergency operations strategy was adapted and implemented, which allowed for rapid development of communications and operational processes. A tiering strategy based on recommendations from the National Academies was used in conjunction with human resources data to determine vaccine eligibility for the first phase of vaccination. A comprehensive data and reporting strategy was built to connect human resources and vaccine consent data for tracking vaccination rates across the system. Results: Vaccination of employed and affiliated colleagues began December 15, 2020, and was made available based on state-level release of tiers. Within the first 6 weeks, in total, 203,544 individuals were eligible for vaccine based on these criteria. Of these, 181,282 (89.1%) consented to and received vaccine, 19,788 (9.7%) declined, and 2,474 (1.2%) indicated that they had already been vaccinated. Of those eligible, the highest acceptance of vaccine was among the job codes of specialists and professionals (n = 7,914 total, 100% consent), providers (n = 23,335, 99.6%,), and physicians (n = 3,218, 98.4%). Vaccine was most likely to be declined among job codes of clerical and other administrative (n = 12,889 total, 80.1% consent), clinical specialists and professionals (n = 22,853, 81.0%,) and aides, orderlies and technicians (n = 17,803, 82.6%,). Registered nurses made up the largest eligible population (n = 56,793), and 89.5% of those eligible consented to receive vaccination. Average age among those who consented was slightly older (48.3 years) than those that declined (44.7 years), as was length of employment tenure (6.9 vs 5.0 years). Conclusion: A large-scale, closed POD, mass vaccination program was able to vaccinate nearly 200,000 healthcare workers for SARS-CoV-2 in 6 weeks. This program was implemented in acute-care sites across 20 different US states, and it was able to meet the various state-level requirements for management of processes, product, and required reporting. The development of a standardized strategy and custom, centralized monitoring and reporting facilitated insight into the characteristics of early vaccine adopters versus those who decline vaccination. These data can aid in the refining and targeting of educational materials and messaging about the SARS-CoV-2 vaccine.Funding: NoDisclosures: None

Large-Scale Electric Vehicle Operation Monitoring Platform Based on Cloud Computing

2013 ◽  
Vol 278-280 ◽  
pp. 1878-1882
Author(s):  
Ming Yu Zhao ◽  
Zhi Yuan Lu ◽  
Gang Wang ◽  
Wei Guo Zhang
Keyword(s):  
Cloud Computing ◽  
Electric Vehicle ◽  
Large Scale ◽  
New Technology ◽  
Demand Forecasting ◽  
Value Added ◽  
Vehicle Operation ◽  
Substantial Investment ◽  
And Storage ◽  
Monitoring Platform

With the development of electric vehicles in China, the demand on computing ability and storage for large-scale electric vehicle operation monitoring platform is increasing. Value-added technology of grid collaborative and proactive demand forecasting, multi-source data management technology, and storage technology of value-added services platform are new technology for the platform with the help of cloud computing. By using the new technology, the platform can provide powerful computing ability without substantial investment and make sufficient technical preparation for the extensive use of the electric vehicle.

scholarly journals Design and Implementation of Large-Scale Public Building Energy Consumption Monitoring Platform Based on BP Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiancheng Liu ◽  
Congxiang Tian
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Bp Neural Network ◽  
Large Scale ◽  
Rapid Development ◽  
Building Energy ◽  
Building Energy Consumption ◽  
Fast Training ◽  
Simulation Calculation ◽  
Monitoring Platform

With the rapid development of network technology, people are increasingly dependent on the internet. When BP neural network (BNN) performs simulation calculation, it has the advantages of fast training speed, high accuracy, and strong robustness and is widely used in large-scale public (LSP) building energy consumption (BEC) monitoring platforms (LPB). Therefore, the purpose of this paper to study the energy consumption monitoring platform of large public (LP) buildings is to better monitor the energy consumption of public buildings, so as to supplement or remedy at any time. This article mainly uses the data analysis method and the experimental method to carry on the relevant research and the system test to the BNN. The experimental results show that the monitoring system (MS) platform designed in this paper has real-time performance, and its time consumption is between 2 s and 3 s, and the data accords with theory and reality.

scholarly journals IN5 ECONOMIC EVALUATION OF A LARGE-SCALE MENINGOCOCCAL C VACCINATION PROGRAM IN THE NETHERLANDS

2002 ◽  
Vol 5 (6) ◽  
pp. 453-454 ◽  
Author(s):  
R Welte ◽  
MJ Postma ◽  
JM Bos ◽  
L van Alphen
Keyword(s):  
Economic Evaluation ◽  
The Netherlands ◽  
Large Scale ◽  
Vaccination Program

scholarly journals Empirical Study on Structural Safety Diagnosis of Large-Scale Civil Infrastructure Using Laser Scanning and BIM

2018 ◽  
Vol 10 (11) ◽  
pp. 4024 ◽  
Author(s):  
Namhyuk Ham ◽  
Sang-Hyo Lee
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Structural Safety ◽  
Civil Infrastructure ◽  
Civil Infrastructures ◽  
Deformation State ◽  
Technology Introduction ◽  
Quantitative Basis ◽  
Saving Effect ◽  
Safety Diagnosis

Existing structural safety diagnosis methods are time-consuming due to personnel-oriented measurement methods and have a limitation that it is difficult to obtain consistent research results. In order to overcome these limitations, this study proposes a structural safety diagnosis method using laser scanning and BIM. In spite of the various studies related to laser scanning and BIM, it is difficult to find a study that verifies the effect of shortening the service period and cost reduction in terms of project management. Therefore, in this study, case analysis of structural safety diagnosis of large-scale civil infrastructure was conducted. In the structural safety diagnosis, the laser scanning data and the BIM model were compared and analyzed to determine the degree of deformation of pipe rack (e.g., truss, column). Laser scanning data reflects the deformation state of large-scale civil infrastructure. On the other hand, the BIM model was constructed by reflecting the state before the transformation with reference to the laser scanning data. Finally, proposed method of structural safety diagnosis saved four months. In terms of manpower saving, 125 man-month was saved. The research findings can provide a quantitative basis for the introduction of laser scanning and BIM technology in the structural safety diagnosis of aging large-scale civil infrastructures. However, the limitations of this study have not been analyzed economically by considering the investment cost (e.g., hardware, software, training, etc.) of laser scanning and BIM technology and the cost saving effect of technology introduction.

Rubella vaccination: Fertility control in a large-scale vaccination program for postpubertal women

1975 ◽  
Vol 121 (8) ◽  
pp. 1089-1094 ◽  
Author(s):  
Edna Halstead ◽  
Scott B. Halstead ◽  
Robert S. Jackson ◽  
Donald Char ◽  
Ralph Hale ◽  
...  
Keyword(s):  
Large Scale ◽  
Fertility Control ◽  
Vaccination Program ◽  
Rubella Vaccination

scholarly journals Requirements and Operational Guidelines for Secure and Sustainable Digital Phenotyping: Design and Development Study (Preprint)

2020 ◽  
Author(s):  
Raj R Jagesar ◽  
Jacob A Vorstman ◽  
Martien J Kas
Keyword(s):  
Large Scale ◽  
Rapid Development ◽  
Platform As A Service ◽  
Privacy Law ◽  
Sustainable Operation ◽  
Digital Phenotyping ◽  
Data Collection And Analysis ◽  
Further Development ◽  
Behavioral Monitoring ◽  
Monitoring Platform

BACKGROUND Digital phenotyping, the measurement of human behavioral phenotypes using personal devices, is rapidly gaining popularity. Novel initiatives, ranging from software prototypes to user-ready research platforms, are innovating the field of biomedical research and health care apps. One example is the BEHAPP project, which offers a fully managed digital phenotyping platform as a service. The innovative potential of digital phenotyping strategies resides among others in their capacity to objectively capture measurable and quantitative components of human behavior, such as diurnal rhythm, movement patterns, and communication, in a real-world setting. The rapid development of this field underscores the importance of reliability and safety of the platforms on which these novel tools are operated. Large-scale studies and regulated research spaces (eg, the pharmaceutical industry) have strict requirements for the software-based solutions they use. Security and sustainability are key to ensuring continuity and trust. However, the majority of behavioral monitoring initiatives have not originated primarily in these regulated research spaces, which may be why these components have been somewhat overlooked, impeding the further development and implementation of such platforms in a secure and sustainable way. OBJECTIVE This study aims to provide a primer on the requirements and operational guidelines for the development and operation of a secure behavioral monitoring platform. METHODS We draw from disciplines such as privacy law, information, and computer science to identify a set of requirements and operational guidelines focused on security and sustainability. Taken together, the requirements and guidelines form the foundation of the design and implementation of the BEHAPP behavioral monitoring platform. RESULTS We present the base BEHAPP data collection and analysis flow and explain how the various concepts from security and sustainability are addressed in the design. CONCLUSIONS Digital phenotyping initiatives are steadily maturing. This study helps the field and surrounding stakeholders to reflect upon and progress toward secure and sustainable operation of digital phenotyping–driven research.

Research on a Remote Network Monitoring Model for Large-Scale Materials Manufacturing

2011 ◽  
Vol 474-476 ◽  
pp. 1999-2003 ◽  
Author(s):  
Xiao Hui Zeng ◽  
Man Hua Li ◽  
Wen Lang Luo
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Graph Drawing ◽  
Network Monitoring ◽  
Control Module ◽  
Control Center ◽  
Monitoring Model ◽  
Internet Browser ◽  
Monitoring Platform ◽  
Module Graph

A remote network monitoring model for large-scale materials manufacturing is proposed, including five modules: center control module, data collection and fault alarm module, graph drawing module and data storage module. The center control module not only interacts with users, but also controls the other four modules to work together in harmony. According to this monitoring model, a remote network monitoring platform is designed and realized. The user can interact with the control center module through an Internet browser, and the information about the monitored manufacturing machines and devices can be displayed by means of text, chart, graphic and sound, etc. Moreover, the details about the problems or faults from the monitored objects can be obtained in time. The experimental results indicate that the network monitoring platform can accurately get the information of the monitored objects, and users can conveniently get the online running state of those monitored objects.

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