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Rothman RE, Hsieh YH, DuVal A, Talan DA, Moran GJ, Krishnadasan A, Shaw-Saliba K, Dugas AF. Front-Line Emergency Department Clinician Acceptability and Use of a Prototype Real-Time Cloud-Based Influenza Surveillance System. Front Public Health 2021; 9:740258. [PMID: 34805066 PMCID: PMC8601200 DOI: 10.3389/fpubh.2021.740258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 10/11/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: To assess emergency department (ED) clinicians' perceptions of a novel real-time influenza surveillance system using a pre- and post-implementation structured survey. Methods: We created and implemented a laboratory-based real-time influenza surveillance system at two EDs at the beginning of the 2013-2014 influenza season. Patients with acute respiratory illness were tested for influenza using rapid PCR-based Cepheid Xpert Flu assay. Results were instantaneously uploaded to a cloud-based data aggregation system made available to clinicians via a web-based dashboard. Clinicians received bimonthly email updates summating year-to-date results. Clinicians were surveyed prior to, and after the influenza season, to assess their views regarding acceptability and utility of the surveillance system data which were shared via dashboard and email updates. Results: The pre-implementation survey revealed that the majority (82%) of the 151 ED clinicians responded that they “sporadically” or “don't,” actively seek influenza-related information during the season. However, most (75%) reported that they would find additional information regarding influenza prevalence useful. Following implementation, there was an overall increase in the frequency of clinician self-reporting increased access to surveillance information from 50 to 63%, with the majority (75%) indicating that the surveillance emails impacted their general awareness of influenza. Clinicians reported that the additional real-time surveillance data impacted their testing (65%) and treatment (51%) practices. Conclusions: The majority of ED clinicians found surveillance data useful and indicated the additional information impacted their clinical practice. Accurate and timely surveillance information, distributed in a provider-friendly format could impact ED clinician management of patients with suspected influenza.
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Affiliation(s)
- Richard E Rothman
- Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Yu-Hsiang Hsieh
- Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Anna DuVal
- Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - David A Talan
- Ronald Reagan University of California, Los Angeles (UCLA) Medical Center, Los Angeles, CA, United States
| | - Gregory J Moran
- University of California, Olive-View Medical Center, Los Angeles, CA, United States
| | - Anusha Krishnadasan
- University of California, Olive-View Medical Center, Los Angeles, CA, United States
| | - Katy Shaw-Saliba
- Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Andrea F Dugas
- Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD, United States
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Kil BH, Park JS, Ryu MH, Park CY, Kim YS, Kim JD. Cloud-Based Software Architecture for Fully Automated Point-of-Care Molecular Diagnostic Device. Sensors (Basel) 2021; 21:6980. [PMID: 34770286 DOI: 10.3390/s21216980] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 10/09/2021] [Accepted: 10/19/2021] [Indexed: 01/02/2023]
Abstract
This paper proposes a cloud-based software architecture for fully automated point-of-care molecular diagnostic devices. The target system operates a cartridge consisting of an extraction body for DNA extraction and a PCR chip for amplification and fluorescence detection. To facilitate control and monitoring via the cloud, a socket server was employed for fundamental molecular diagnostic functions such as DNA extraction, amplification, and fluorescence detection. The user interface for experimental control and monitoring was constructed with the RESTful application programming interface, allowing access from the terminal device, edge, and cloud. Furthermore, it can also be accessed through any web-based user interface on smart computing devices such as smart phones or tablets. An emulator with the proposed software architecture was fabricated to validate successful operation.
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Hashmi M, Beane A, Murthy S, Dondorp AM, Haniffa R. Leveraging a Cloud-Based Critical Care Registry for COVID-19 Pandemic Surveillance and Research in Low- and Middle-Income Countries. JMIR Public Health Surveill 2020; 6:e21939. [PMID: 33147162 PMCID: PMC7717923 DOI: 10.2196/21939] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/04/2020] [Accepted: 10/20/2020] [Indexed: 02/06/2023] Open
Abstract
The COVID-19 pandemic has revealed limitations in real-time surveillance needed for responsive health care action in low- and middle-income countries (LMICs). The Pakistan Registry for Intensive CarE (PRICE) was adapted to enable International Severe Acute Respiratory and emerging Infections Consortium (ISARIC)–compliant real-time reporting of severe acute respiratory infection (SARI). The cloud-based common data model and standardized nomenclature of the registry platform ensure interoperability of data and reporting between regional and global stakeholders. Inbuilt analytics enable stakeholders to visualize individual and aggregate epidemiological, clinical, and operational data in real time. The PRICE system operates in 5 of 7 administrative regions of Pakistan. The same platform supports acute and critical care registries in eleven countries in South Asia and sub-Saharan Africa. ISARIC-compliant SARI reporting was successfully implemented by leveraging the existing PRICE infrastructure in all 49 member intensive care units (ICUs), enabling clinicians, operational leads, and established stakeholders with responsibilities for coordinating the pandemic response to access real-time information on suspected and confirmed COVID-19 cases (N=592 as of May 2020) via secure registry portals. ICU occupancy rates, use of ICU resources, mechanical ventilation, renal replacement therapy, and ICU outcomes were reported through registry dashboards. This information has facilitated coordination of critical care resources, health care worker training, and discussions on treatment strategies. The PRICE network is now being recruited to international multicenter clinical trials regarding COVID-19 management, leveraging the registry platform. Systematic and standardized reporting of SARI is feasible in LMICs. Existing registry platforms can be adapted for pandemic research, surveillance, and resource planning.
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Affiliation(s)
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- Collaboration for Research, Improvement and Training in Critical Care in Asia, Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Please see acknowledgements section for list of collaborators, Bangkok, Thailand
| | - Madiha Hashmi
- Department of Critical Care, Ziauddin University, Karachi, Pakistan
| | - Abi Beane
- Collaboration for Research, Improvement and Training in Critical Care in Asia, Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Srinivas Murthy
- Department of Pediatrics, University of British Colombia, Vancouver, BC, Canada
| | - Arjen M Dondorp
- Collaboration for Research, Improvement and Training in Critical Care in Asia, Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Rashan Haniffa
- Collaboration for Research, Improvement and Training in Critical Care in Asia, Mahidol Oxford Tropical Medicine Research Unit, Bangkok, Thailand
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Kalantar KL, Carvalho T, de Bourcy CFA, Dimitrov B, Dingle G, Egger R, Han J, Holmes OB, Juan YF, King R, Kislyuk A, Lin MF, Mariano M, Morse T, Reynoso LV, Cruz DR, Sheu J, Tang J, Wang J, Zhang MA, Zhong E, Ahyong V, Lay S, Chea S, Bohl JA, Manning JE, Tato CM, DeRisi JL. IDseq-An open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring. Gigascience 2020; 9:giaa111. [PMID: 33057676 PMCID: PMC7566497 DOI: 10.1093/gigascience/giaa111] [Citation(s) in RCA: 135] [Impact Index Per Article: 33.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 08/28/2020] [Accepted: 09/22/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Metagenomic next-generation sequencing (mNGS) has enabled the rapid, unbiased detection and identification of microbes without pathogen-specific reagents, culturing, or a priori knowledge of the microbial landscape. mNGS data analysis requires a series of computationally intensive processing steps to accurately determine the microbial composition of a sample. Existing mNGS data analysis tools typically require bioinformatics expertise and access to local server-class hardware resources. For many research laboratories, this presents an obstacle, especially in resource-limited environments. FINDINGS We present IDseq, an open source cloud-based metagenomics pipeline and service for global pathogen detection and monitoring (https://idseq.net). The IDseq Portal accepts raw mNGS data, performs host and quality filtration steps, then executes an assembly-based alignment pipeline, which results in the assignment of reads and contigs to taxonomic categories. The taxonomic relative abundances are reported and visualized in an easy-to-use web application to facilitate data interpretation and hypothesis generation. Furthermore, IDseq supports environmental background model generation and automatic internal spike-in control recognition, providing statistics that are critical for data interpretation. IDseq was designed with the specific intent of detecting novel pathogens. Here, we benchmark novel virus detection capability using both synthetically evolved viral sequences and real-world samples, including IDseq analysis of a nasopharyngeal swab sample acquired and processed locally in Cambodia from a tourist from Wuhan, China, infected with the recently emergent SARS-CoV-2. CONCLUSION The IDseq Portal reduces the barrier to entry for mNGS data analysis and enables bench scientists, clinicians, and bioinformaticians to gain insight from mNGS datasets for both known and novel pathogens.
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Affiliation(s)
- Katrina L Kalantar
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Tiago Carvalho
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | | | - Boris Dimitrov
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Greg Dingle
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Rebecca Egger
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Julie Han
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Olivia B Holmes
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Yun-Fang Juan
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Ryan King
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Andrey Kislyuk
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Michael F Lin
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Maria Mariano
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Todd Morse
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Lucia V Reynoso
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - David Rissato Cruz
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Jonathan Sheu
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Jennifer Tang
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - James Wang
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Mark A Zhang
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Emily Zhong
- Chan Zuckerberg Initiative, Science, PO Box 8040 Redwood City, CA 94063, USA
| | - Vida Ahyong
- Chan Zuckerberg Biohub, 499 Illinois St, San Francisco, CA 94158, USA
| | - Sreyngim Lay
- Malaria and Vector Research Laboratory, National Institute of Allergy and Infectious Diseases, Phnom Penh, Cambodia
| | - Sophana Chea
- Malaria and Vector Research Laboratory, National Institute of Allergy and Infectious Diseases, Phnom Penh, Cambodia
| | - Jennifer A Bohl
- Malaria and Vector Research Laboratory, National Institute of Allergy and Infectious Diseases, Phnom Penh, Cambodia
| | - Jessica E Manning
- Malaria and Vector Research Laboratory, National Institute of Allergy and Infectious Diseases, Phnom Penh, Cambodia
| | - Cristina M Tato
- Chan Zuckerberg Biohub, 499 Illinois St, San Francisco, CA 94158, USA
| | - Joseph L DeRisi
- Chan Zuckerberg Biohub, 499 Illinois St, San Francisco, CA 94158, USA
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Vereb T, Boda K, Czakó L, Vaszilkó M, Fülöp G, Klenk G, Janovszky Á, Oberna F, Piffkó J, Seres L. Cloud-Based Multicenter Data Collection and Epidemiologic Analysis of Bisphosphonate-Related Osteonecrosis of the Jaws in a Central European Population. J Clin Med 2020; 9:E426. [PMID: 32033299 DOI: 10.3390/jcm9020426] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 01/29/2020] [Accepted: 01/31/2020] [Indexed: 12/01/2022] Open
Abstract
Objective: Bisphosphonate-related osteonecrosis of the jaws is considered to be a rare but severe complication of bisphosphonate therapy. To understand this condition better, data collection is essential. Although the number of scientific papers about this subject is large, to date only a few multicenter reports have been published. Study design: We present a novel cloud-based data collection system for the evaluation of the risk factors of bisphosphonate-related osteonecrosis of the jaws. Web-based questionnaire and database have been set up and made available to voluntary researchers and clinicians in oral and maxillofacial surgery in Hungary and Slovakia. Results: To date, fifteen colleagues from eight maxillofacial units have joined the study. Data of 180 patients have been recorded. Collected data were statistically analysed and evaluated from an epidemiological point of view. Conclusions: Authors consider cloud-based multicenter data collection a useful tool that allows for real-time collaboration between users, facilitates fast data entry and analysis, and thus considerably contributes to widening our knowledge of bisphosphonate-related osteonecrosis of the jaws.
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Drakos A, Protonotarios V, Manouselis N. agINFRA: a research data hub for agriculture, food and the environment. F1000Res 2015; 4:127. [PMID: 26339472 PMCID: PMC4544381 DOI: 10.12688/f1000research.6349.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/11/2015] [Indexed: 11/20/2022] Open
Abstract
The agINFRA project (www.aginfra.eu) was a European Commission funded project under the 7th Framework Programme that aimed to introduce agricultural scientific communities to the vision of open and participatory data-intensive science. agINFRA has now evolved into the European hub for data-powered research on agriculture, food and the environment, serving the research community through multiple roles. Working on enhancing the interoperability between heterogeneous data sources, the agINFRA project has left a set of grid- and cloud- based services that can be reused by future initiatives and adopted by existing ones, in order to facilitate the dissemination of agricultural research, educational and other types of data. On top of that, agINFRA provided a set of domain-specific recommendations for the publication of agri-food research outcomes. This paper discusses the concept of the agINFRA project and presents its major outcomes, as adopted by existing initiatives activated in the context of agricultural research and education.
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Affiliation(s)
- Andreas Drakos
- Polytechnic Building, University of Alcala, Barcelona, 28871, Spain
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