Average Turnaround Time Research Articles

Development of a framework for improving the turnaround time of the application process at the South African Civil Aviation Authority

Drones are considered to become more significant as technology develops and be used in creative ways. The aim of this paper is to develop a framework to improve the turnaround time (TAT) of the drone application process at South African Civil Aviation Authority (SACAA). According to some of the drone companies, application process of drone approval takes time to complete. These delays impact negatively to drone companies in South Africa. Drone operators were interviewed, and the current status of the application process was captured. Thirteen drone operators were interviewed using a structured set of questionnaires. Results show that application process is not well implemented and that the structure does not create a positive outcome to the South African drone industry. Findings indicate that the average turnaround time to complete the approval process is long, and it is time consuming. The framework to improve the current turnaround time of the application process was developed. The proposed framework consists of three techniques (process activities improvement, capacity enhancement and process redesign). The proposed framework can be used as a guide to improve the situation at SACAA. .

A Cost, Time, and Demographic Analysis of Participant Recruitment and Urine Sample Collection Through Social Media Optimization.

Clinical research can be expensive and time consuming due to high associated costs and/or duration of the study. We hypothesized that urine sample collection using online recruitment and engagement of research participants via social medial has the potential to reach a large population in a small timeframe, at a reasonable cost. We performed a retrospective cost analysis of a cohort study comparing cost per sample and time per sample for both online and clinically recruited participants for urine sample collection. During this time, cost data were collected based on study associated costs from invoices and budget spreadsheets. The data were subsequently analyzed using descriptive statistics. Each sample collection kit contained 3 urine cups, 1 for the disease sample and 2 for control samples. Out of the 3,576 (1,192 disease + 2,384 control) total sample cups mailed, 1,254 (695 control) samples were returned. Comparatively, the 2 clinical sites collected 305 samples. Although the initial startup cost of online recruitment was higher, cost per sample for online recruited was found to be $81.45 compared to $398.14 for clinic sample. We conducted a nationwide, contactless, urine sample collection through online recruitment in the midst of the COVID-19 pandemic. Results were compared with the samples collected in the clinical setting. Online recruitment can be utilized to collect urine samples rapidly, efficiently, and at a cost per sample that was 20% of an in-person clinic, and without risk of COVID-19 exposure.

Evaluation of users' level of satisfaction for an artificial intelligence-based diagnostic program in pediatric rare genetic diseases.

The artificial intelligence (AI)-based genetic diagnostic program has been applied to genome sequencing to facilitate the diagnostic process. The objective of the current study was to evaluate the experience and level of satisfaction of participants using an AI-based diagnostic program for rare pediatric genetic diseases. The patients with neurodevelopmental disorders or hearing impairments, their guardians, and their physicians from 16 tertiary general hospitals were enrolled. The study period was from April 2020 to March 2021. A survey was designed to assess their experience and level of satisfaction. A total of 30 physicians and 243 patients and guardians (199 neurodevelopmental disorders and 44 hearing impairments) completed the survey. DNA samples of the subjects were collected through buccal swabs or blood collection: 211 subjects (86.8%) through buccal swab and 29 subjects (11.9%) through blood collection. Average turnaround time for result receipt was 57.54 ± 32.42 days. For the sampling method, 193 patients and guardians (81.1%) and 28 physicians (93.3%) preferred buccal swab. The level of satisfaction of the 2 groups participating in the AI-based diagnostic program was 8.31 ± 1.71 out of 10 in the patient and guardian group and 8.42 ± 1.23 in the physician group. Clinicians, patients, and guardians are satisfied with the AI-based diagnostic program in general. With an increase in AI-based precision medicine solutions, the evaluation of the user's satisfaction with appropriate provision will help improve personal health care.

Establishing a committee for antemortem reviews of suspect Creutzfeldt-Jakob disease cases in Ireland

BackgroundCreutzfeldt-Jakob disease (CJD) is a rapidly progressive, neurodegenerative disease. In Ireland, clinical diagnostics and laboratory testing remain the responsibility of the managing clinician and the Neuropathology Department at the Beaumont Hospital, respectively. Centralized review of individual cases is not undertaken.AimsTo determine how diagnostic processes for CJD could be improved in Ireland and to outline the structure and referral process for a new CJD review panel at the Beaumont Hospital.MethodsWe surveyed Irish neurologists’ experiences on the management of CJD in Ireland. We measured turnaround times (TAT) for CSF samples referred for diagnostic CJD testing. Finally, we retrospectively reviewed imaging of autopsy-proven CJD cases to compare with initial reports.ResultsNinety-three percent of neurologists supported a national central review of suspect CJD cases. A second clinical opinion was considered to be of likely benefit by 79%. Additionally, 93% reported that a centralized review of neuroradiology would be useful. All respondents felt that expediting turnaround of CSF analysis would be of benefit. The average TAT for CSF testing was 35.4 days. In retrospective review of imaging, all patients demonstrated MRI findings consistent with CJD. However, in only one of these cases were the initial pre-autopsy radiological findings reported as being consistent with CJD.ConclusionsThese findings support the need for improvements to the Irish National CJD Surveillance Unit to maximize antemortem diagnostic accuracy. On foot of this, a clinical CJD Multidisciplinary Team (CJD MDT) has been established to provide a second opinion on (i) the patient’s clinical history, (ii) neuroradiology and (iii) and neurophysiology reports (where available).

Spatial Network Analysis of Container Port Operations: The Case of Ship Turnaround Times

This research investigates the determinants of ship turnaround times at about 2,300 container ports between 1977 and 2016, based on nearly 3 million daily vessel movements. It adopts a multilevel approach combining territorial and network indicators to characterize ports, and proposes a new methodology calculating shipping delays. Main results reveal that port connectivity, Gross Domestic Product per capita, the number of vessel calls, and island location foster efficient port operations. Conversely, urban population, voyage delays at sea, maximum ship size, and upstream location increase turnaround time. While average turnaround time and inter-port sailing time have both regularly declined, operational and technological changes in the ports and maritime sector - especially after the 2007/8 global financial crisis - accelerated intra-port time and slowed down inter-port time. This relational and spatial approach also underlines the geographic differentiation of ship times nationally and regionally, as it is far from being randomly distributed on the globe. ... Yutani, H.

#16 Chasing the Small Tail of Infectious Diseases: The Rapid, Non-invasive, Culture-independent Detection Of Rat-Bite Fever With A Plasma-based Microbial Cell-free DNA Next-generation Sequencing Test (The Karius Test)

Abstract Background Rat-bite fever (RBF) is a rare, systemic illness caused by infection with Streptobacillus moniliformis. RBF has a case-fatality risk of 7%-10% among untreated patients. Over 200 cases of RBF have been documented in the United States, but this is likely a significant under-representation because RBF is not a reportable disease. The diagnosis of these infections can be limited by: (1) Streptobacillus moniliformis fastidious nature and difficulty to culture; (2) the nonspecific manifestations of the infections and clinical overlap with a broad differential diagnosis; and (3) the unreliability of rat exposure history. We demonstrate use of unbiased microbial cell free DNA (mcfDNA) next-generation sequencing (NGS) to overcome these diagnostic limitations. Method The Karius Test (KT) was developed and validated in Karius’s CLIA certified/CAP accredited lab (Redwood City, CA) to detect and interpret mcfDNA in plasma. After mcfDNA is extracted and NGS performed, mcfDNA sequences are aligned to a curated database of > 1000 organisms. McfDNA from organisms observed above background at statistical significance are reported and quantified in molecules/µL (MPM). KT detections of Streptobacillus moniliformis were reviewed from January 2017 - June 2021; clinical information was obtained with test requisition or consultation upon result reporting. Results KT detected 7 cases of Streptobacillus moniliformis at an average of 673 MPM (35-3078; SD 1185) with an average turnaround time of 28.5 hours (SD 8.4) from sample receipt from 6 unique institutions (Table 1). Six patients were children; all were immunocompetent. Fever and rash were the most common presentation in the majority of the cases. Five of seven patients had arthritis or osteomyelitis while the remaining two patients had arthralgia. A history of rat exposure was elicited in all cases (some after microbiological diagnosis). In all patients blood cultures were negative and mcfDNA NGS was the only means of microbiological diagnosis. Conclusion Unbiased plasma-based mcfDNA NGS provides a rapid, non-invasive test to diagnose diverse clinical infections by Streptobacillus moniliformis. These cases highlight the potential of the KT to effectively identify infections caused by fastidious/unculturable pathogens with non-specific clinical manifestations and broad differential diagnoses.

Utilization and financial coverage of blood based next generation sequencing for solid tumors: A study from Augusta-Georgia.

e18592 Background: There is an increasing trend of integrating molecular profiling to devise treatment plans for solid malignancies. Tumor testing for specific clonal abnormalities is being supplanted by broad multigene panel testing from blood specimen, aptly labelled liquid biopsy. Due to varying utility across malignancies in differing contexts and issues of access and affordability, their adoption is not uniform. We attempt to characterize the pattern of utilization across tumor types and financial coverage schemes in an academic cancer institute in southeastern United States. Methods: All blood based next generation testing samples ordered by providers affiliated to Georgia Cancer center between January 1, 2017, and December 31, 2021, via Guardant platform for all solid tumors was included in this analysis. Guardant360 and Guardant360CDx assays tested for upto 83 cancer related genes in circulating cell-free DNA in patients of solid tumors. Primary cancer diagnosis, insurance information and turnaround time was obtained from Guardant. Results: 296 tests were sent from January 1, 2017, through December 31, 2021. The total number of tests performed in year 2017, 2018, 2019, 2020 and 2021 were 1, 3, 28, 99 and 165 respectively. Billing information was available for all cases, clinical information was available for 262 cases. Average turnaround time was 8.5 days overall. 221 Guardant360 was sent with average turnaround time of 10 days. 41 Guardant360CDx was sent with average turnaround time of 7 days. The frequency of malignancies in the order of dimensioning frequency were lung 50.7%, prostate 12.1%, breast 6.9%, kidney 3.8% and colorectal 3.4%. The remaining 22.1% comprised of pancreatic, melanoma, glioblastoma, and bladder malignancies. The test was covered by private insurance/employee health plan in 53.4% (158/296), Medicare in 31.1% (92/296) and Medicaid in 10.5% (31/296) (table). 4.7% (14/296) qualified for free of charge testing (financial indigent) and 0.3% (1/296) were self-pay (table). Conclusions: There is an increase in the utilization of liquid biopsy to perform comprehensive genomic analysis. The distribution of tumor types is not entirely explained by the incidence and availability of targeted therapies for each type. Private insurers accounted for most of the tests being done. The disparities in utilization of this platform across different tumor types and payment models deserve further exploration. T[Table: see text]

Using cell-free circulating tumor DNA (cfDNA) to identify guideline-relevant biomarkers for therapy selection in 14,000 patients (pts) with metastatic colorectal cancer (mCRC).

3601 Background: Two cfDNA assays are FDA-approved for use in advanced cancer pts across solid tumors. While several NCCN guidelines recommend cfDNA as a valid and useful method for molecular testing, the utility varies by cancer type. Despite the growing number of molecular alterations pertinent to first-line treatment in mCRC, current guidelines offer little guidance on the use of cfDNA in mCRC. Here we assess the ability of cfDNA to detect guideline-relevant actionable biomarkers informative for first-line therapy selection and beyond in patients with mCRC. Methods: We queried consecutive samples from advanced cancer pts with a diagnosis of CRC who underwent testing via a commercially available cfDNA assay (Guardant360) from September 2018 to January 2022. Validation and content of this assay has been previously described. To enrich for less heavily treated pts, we limited analysis to those whose first cfDNA test was done during the study period and only included the pt’s first test. The maximum variant allele fraction (maxVAF) for each test was used as a proxy for tumor shed and was compared between cancers with a Mann-Whitney test. The frequency of suspected germline alterations was assessed only in pts who received testing via a panel version with expanded mismatch repair (MMR) gene coverage. Tissue frequencies for select biomarkers were obtained from the MSK-IMPACT Clinical Sequencing Cohort in cBioPortal. Results: In total, 14,345 pts with mCRC received their first cfDNA test during the study period, with 92% of pts (13,190) having >1 cfDNA alteration detected. Median age was 62 and 44% of pts were female. The frequencies of key biomarkers are listed in Table 1. The median maxVAF was 5.6%, compared to 2.5% and 1.8% for pts with advanced gastric and NSCLC, respectively (p = < 0.0001 for both). The average turnaround time (TAT) for tests was 7 calendar days. Conclusions: cfDNA results from pts with mCRC demonstrated detection of biomarkers essential to first-line treatment decisions at a frequency comparable to what has been reported via tissue genotyping. mCRC pts had significantly higher tumor shed compared to other cancer types with guidelines that recommend cfDNA as an option for molecular testing, suggesting a potential gap in coverage. Tissue availability in mCRC does not guarantee comprehensive testing is completed quickly (compared to the 7-day TAT seen for cfDNA here), making it an attractive alternative strategy for first-line therapy selection in mCRC. [Table: see text]

48-OR: Barriers to Follow-Up Specialized Eye Care following Retinopathy Identification with Traditional vs. Autonomous Artificial Intelligence (AI) Camera

Point-of-care retinal imaging is effective at identifying diabetic retinopathy. However, appropriate follow-up, referral, and access to specialized eye care remains a barrier for the treatment of identified eye disease. We tested the hypothesis that rapid results and immediate referrals afforded by use of an automated diabetic retinopathy screening platform with AI technology (EyeArt) would result in greater patient follow up with ophthalmology specialists as compared to “traditional” tele-retinal screening (images acquired in clinic and transmitted electronically for interpretation by a vitreoretinal specialist) . All images were acquired during a patient’s regularly scheduled diabetes clinic visit. With traditional tele-retinal screening, the average turnaround time to patient notification of findings was days. Among the 357 patients that underwent traditional screening, 42 (12%) were found to have referable (more-than-mild) retinopathy, and of these, 32 (76%) followed up in ophthalmology clinic. In contrast, the fully autonomous diabetic retinopathy screening platform using AI technology provided an immediate assessment on the presence of retinopathy (within 60 seconds of photo acquisition) . Patients were given this point-of-care summary of their eye-exam findings. When indicated, an ophthalmology referral was ordered and patients were provided with contact information for the ophthalmology office. Of the 81 patients screened with AI technology, 22 (27%) had referable retinopathy detected, 15 (68%) of whom followed up in ophthalmology clinic. The higher detection rate with AI screening raises the question of “overcalling” the presence of disease. We conclude that although AI screening offers immediate results allowing for immediate ophthalmology referral, there remains a substantial barrier to ophthalmology follow up after a positive retinopathy screen identified by either screening method. Disclosure M.Wahl: None. R.Kiani: None. J.Neuberger: None. B.Wilson: None. M.Hartnett: None. S.Fisher: None.

Effective load balancing strategy using fuzzy golden eagle optimization in fog computing environment

Fog computing (FC) is becoming popular for connecting real-time Internet of Things (IoT) applications such as driverless cars and health care. Although fog has low latency compared to the cloud, the fog becomes overloaded when serving a large number of IoT devices. FC struggles while distributing the load to the resources that may result in certain fog nodes being overloaded or underloaded. To overcome these issues, an effective load balancing algorithm named Fuzzy Golden Eagle Load Balancing (FGELB) is proposed. The proposed load balancing strategy consists of three stages, namely: assigning priority to the tasks, resource ranking and scheduling, and power management. Initially, the priority is assigned to the incoming task by considering the deadline time, task size, and predefined priority using a fuzzy algorithm. This prioritization of tasks helps to execute the important task without delay. Then the Golden Eagle Optimization algorithm (GEOA) is used to rank and schedule the resources. This ranking and scheduling help the tasks to be executed with suitable resources. Ranked resources execute the tasks in the resource engine, and the power engine manages the power by enabling/disabling the resources based on their necessity. The performance of the approach is tested and it is compared with the results of existing methods in terms of energy consumption, failure rate, computational cost, communication overhead, average turnaround time, and waiting time. The results show that the proposed FGELB approach achieves higher performance than the existing load balancing approaches.

Performance of Idylla™RAS-BRAF mutation test for formalin-fixed paraffin-embedded tissues of colorectal cancer

BackgroundThe Biocartis Idylla™ platform is a fully automated, real-time PCR-based diagnostic system. The Idylla™KRAS and NRAS-BRAF Mutation Tests have been developed for the qualitative detection of mutations in KRAS, NRAS and BRAF genes, facilitating the genomic profiling of patients with colorectal cancer. The aim of the present study was to evaluate clinical performances of these tests in Japan.MethodsThe RAS and BRAF mutation statuses of 253 formalin-fixed paraffin-embedded (FFPE) colorectal cancer tissues were analyzed using the Investigational Use Only Idylla™KRAS Mutation Test and the Idylla™NRAS-BRAF Mutation Test and an in vitro diagnostics (IVD) kit (MEBGEN RASKET™-B kit).ResultsThe success rate for obtaining a valid mutational data without retest of the Idylla tests was 97.6% (247/253): 111 KRAS mutations (43.8%), 9 NRAS mutations (3.6%), and 36 BRAF V600E mutations (14.2%) were detected using the Idylla tests. Compared with the MEBGEN RASKET-B results, the positive concordance rate was 97.4%, the negative concordance rate was 95.7%, and the overall concordance rate was 95.3% (κ = 0.919, 95% CI 0.871–0.967). The average turnaround time to Idylla™KRAS and NRAS-BRAF Mutation Test was 5.6 working days (range: 3–11 days).ConclusionThis result demonstrates a high concordance between the Idylla™KRAS and NRAS-BRAF Mutation Tests and an existing IVD kit. In this manner, the Idylla™ mutation tests were validated for the detection of clinically significant KRAS, NRAS, and BRAF mutations in FFPE samples from colorectal cancer patients.

Performance of rapid on-site evaluation of touch imprints of lung tissue biopsies for the diagnosis of pulmonary cryptococcosis in patients without HIV infection.

The diagnosis of pulmonary cryptococcosis depends on serum testing, histopathology and mycological culture; there are few studies on touch imprints of lung tissue biopsies for the diagnosis of pulmonary cryptococcosis in patients without HIV infection. The purpose of the current study was to investigate the accuracy and timeliness of on-site touch imprint cytology in the diagnosis of pulmonary cryptococcosis during CT-guided percutaneous lung biopsy. We retrospectively analysed the diagnosis and treatment of 56 patients with final proof of pulmonary cryptococcosis through histopathology and culture or surgical resection from September 2015 to February 2021. Diagnostic methods and treatment and the turnaround time for diagnosis were analysed. The sensitivity of rapid on-site evaluation was 89.3%, and the sensitivity of serology, histopathology and mycological culture was 53.6%, 91.1% and 61.5%, respectively, compared with the final diagnosis. The average turnaround time to diagnose pulmonary cryptococcosis by on-site touch imprint cytology was 8.3±0.9min, which was significantly faster than serum testing, histopathology and mycological culture. On-site touch imprint cytology showed good sensitivity and timeliness in the diagnosis of pulmonary cryptococcosis. In addition, it contributed to the triage of biopsies based on the preliminary diagnosis. On-site touch imprint cytology should be applied and promoted in the diagnosis of pulmonary cryptococcosis during biopsy.

P125 The advancement of digital health technology in the outpatient setting, is speech recognition software useful?

Abstract Background/Aims Over the last 20 years, innovation in digital health technology have been propelling health systems forwards. With the advent of the electronic health record, digital prescribing and artificial intelligence and machine learning comes new opportunities. The use of voice recognition systems in the transcription of rheumatology clinics has the potential for cost and time effectiveness which is ever important within the NHS. Here we review the use, user-interface acceptability and potential cost savings. Methods In speech recognition software the speech is converted to a sequence of words in written text. This is not a new technology and in particular has been widely used within radiology departments across the UK. Rheumatology is largely a clinic-based specialty, with high output of clinic letters. Speech recognition software removes the need for transcription-based services. As a new technology we have reviewed its use within the rheumatology, dermatology, endocrinology, renal and paediatric departments at a large district general hospital. Results 143 staff members have been provided with a license and on average 64% are regularly using the available software. Over 3 months an average of 14,843 minutes per month of dictation has been completed. It has been estimated that over 12 months’ use there has been £100,000 savings through administerial time saved. The average turnaround time for clinic letters from dictation to delivery (electronically) to GPs has improved from approximately 1-2 weeks (but delays up to 4 weeks seen) to an approximately 24-36 hours. Preliminary data from users of this software suggest that compared to traditional dictation devices: 33% found it ‘much better’, 33% ‘better’ and 33% ‘the same’. 67% of participants found it ‘easy, or very easy’ to use whilst 16% found it ‘difficult’. 50% of participants found it ‘usually’ saved time, 33% ‘sometimes’ and 16% ‘rarely’ saved time. Conclusion This preliminary data suggest potential time and cost savings with largely positive feedback from users. Further work is needed to assess potential patient safety issues including errors and inaccuracies compared to traditional dictation means. We aim to complete this work prior to presentation of this abstract should it be accepted. Disclosure H. Crawshaw: None. S. Jamal: None. R. Andev: None.

Fuzzy Based Optimal QoS Constraint Services Composition in Mobile Ad Hoc Networks

In recent years, computational capability of mobile devices such as Laptops, mobile phones, PDAs, etc., are greatly improved. Implementation of SOA ("Service Oriented Architectures") in mobile ad hoc networks increases the flexibility of using mobile devices. On composing different available services to satisfy end user requirement is a critical challenge in MANETs ("Mobile Ad Hoc Network") due to dynamic topology, Resource heterogeneity, Band width constraint and highly distributed service providers. Existing composition services approaches are not suitable for MANETs due to lack of constraints consideration while choosing services. In this paper, we proposed Fuzzy based optimal QoS constrained Service Composition in MANETs. We consider Energy constraint, hop count, Response time & service throughput as QoS Constraints composing optimal services. We proposed fuzzy logic based system to provide rating to the services for optimal selection of services. We also considered that each node can provide one or more services. The service composition failure rate will be reduced by selecting optimal services in available services. The simulation result demonstrates that the proposed method outperformed than the traditional AODV in terms of average packet delay, energy constraint, throughput and turnaround time.

A new median-average round Robin scheduling algorithm: An optimal approach for reducing turnaround and waiting time

A variety of algorithms handles processes on the CPU. The round-robin algorithm is an efficient CPU scheduling mechanism for a time-sharing operating system. The system processes the methods based on the time slice; however, determining the time slice has proven highly challenging for the researchers. As a result, a variety of dynamic time quantum scheduling techniques are presented by various academics to address this challenge. This study aims to determine how to best schedule resources to maximize efficiency. It is important to note that this scheduling mechanism rotates between the processes after the static quantum time is complete. However, the quantum decision affects how effectively and efficiently the procedures may be scheduled. Additionally, the quantum decision has an impact on the scheduling of processes. The average waiting time, turnaround time, and context switch times of the Round Robin scheduling algorithm are high enough to influence the system's performance. To get over the round-drawbacks, robin's the authors in this study suggest using the improved algorithm Median-Average Round Robin (MARR). Using the median and average of the burst time of each process, the author proposes a dynamic time quantum for the system. The authors compared the proposed model with four other scheduling algorithms. The results vividly depict that the proposed algorithms successfully give effective results with reduced average turnaround time and waiting time. In the future, cost and RAM utilization will be considered to enhance the algorithm.

PAS: Performance-Aware Job Scheduling for Big Data Processing Systems

Big data analytics has become increasingly vital in many modern enterprise applications such as user profiling and business process optimization. Today’s big data processing systems, such as Hadoop MapReduce, Spark, and Hive, treat big data applications as a batch of jobs for scheduling. Existing schedulers in production systems often maintain fair allocation without considering application performance and resource utilization simultaneously. It is challenging to perform job scheduling in big data systems to achieve both low turnaround time and high resource utilization due to the high complexity in data processing logics and the dynamic variation in workloads. In this article, we propose a performance-aware scheduler, referred to as PAS, which dynamically schedules big data jobs in Hadoop YARN and Spark and autonomously adjusts scheduling policies to improve application performance and resource utilization. Specifically, PAS schedules multiple concurrent jobs using different policies based on the predicted job completion time and employs a greedy approach and a one-step lookahead strategy to opportunistically maximize the average job performance while still maintaining a satisfactory level of resource utilization. We implement PAS in Hadoop YARN and evaluate its performance with HiBench, a well-known big data processing benchmark. Experimental results show that PAS reduces the average turnaround time by 25% and the makespan by 15% in comparison with four state-of-the-art schedulers.

Assessment of COVID-19 Molecular Testing Capacity in Jordan: A Cross-Sectional Study at the Country Level.

Coronavirus disease 2019 (COVID-19) pandemic control measures rely on the accurate and timely diagnosis of infected individuals. Real-time polymerase chain reaction (qPCR) remains the gold-standard method for laboratory diagnosis of the disease. Delayed diagnosis due to challenges that face laboratories performing COVID-19 testing can hinder public health control measures. Such challenges may be related to shortages in staff, equipment or materials, improper inventory management, flawed workflow, or long turnaround time (TAT). The aim of the current study was to assess the overall COVID-19 molecular testing capacity in Jordan as of April 2021. In addition, the study’s objectives included the identification of potential defects that could comprise the utility of the COVID-19 molecular testing capacity in the country. All laboratories certified by the Ministry of Health (MoH) in Jordan to conduct molecular testing for SARS-CoV-2 were invited to participate in this study. Data were obtained from the participating laboratories (those which agreed to participate) by either telephone interviews or a self-reported written questionnaire with items assessing the key aspects of COVID-19 molecular testing. The full molecular testing capacity in each laboratory was self-reported considering 24 working hours. The total number of participating laboratories was 51 out of 77 (66.2%), with the majority being affiliated with MoH (n = 17) and private laboratories (n = 20). The total molecular COVID-19 testing capacity among the participating laboratories was estimated at 574,441 tests per week, while the actual highest number of tests performed over a single week was 310,047 (54.0%, reported in March 2021). Laboratories affiliated with the MoH were operating at a level closer to their maximum capacity (87.2% of their estimated full capacity for COVID-19 testing) compared to private hospital laboratories (41.3%, p = 0.004), private laboratories (20.8%, p < 0.001), and academic/research laboratories (14.7%, p < 0.001, ANOVA). The national average daily COVID-19 molecular testing was 349.2 tests per 100,000 people in April 2021. The average TAT over the first week of April 2021 for COVID-19 testing was 932 min among the participating laboratories, with the longest TAT among MoH laboratories (mean: 1959 min) compared to private laboratories (mean: 333 min, p < 0.001). Molecular COVID-19 testing potential in Jordan has not been fully utilized, particularly for private laboratories and those belonging to academic/research centers. Supply-chain challenges and shortages in staff were identified as potential obstacles hindering the exploitation of full molecular testing capacity for COVID-19 in the country.

Application Value of Metagenomic Next-Generation Sequencing for Bloodstream Infections in Pediatric Patients Under Intensive Care.

PurposeThis study aimed to analyze the application value of metagenomic next-generation sequencing (mNGS) as a basis for the proper adjustment of the clinical treatment of bloodstream infections (BSIs) in pediatric patients under intensive care.MethodsWe retrospectively enrolled 46 pediatric patients with clinically diagnosed BSIs who were hospitalized in the pediatric intensive care unit of the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University from June 2018 to July 2021. Blood samples were collected for cultivation and for mNGS detection of pathogens.ResultsAmong the 46 children, the average turnaround time for blood culture tests was 3.2 days, and the results revealed pathogens in three children (6.5%). The average turnaround time for mNGS was 2.2 days, and pathogens were found in 30 children (65.2%). The difference in positivity rates between blood culture and mNGS was significant (p<0.05). Blood culture tests found three pathogens, while mNGS identified 28 pathogens, indicating that mNGS detected significantly more types of pathogens than the traditional diagnostic method for pathogenic microorganisms. In some children, more than one pathogen was detected.ConclusionmNGS can help identify pathogenic microorganisms associated with BSI in some pediatric patients under intensive care.

Two-test algorithms for infectious disease diagnosis: Implications for COVID-19.

Diagnostic assays for various infectious diseases, including COVID-19, have been challenged for their utility as standalone point-of-care diagnostic tests due to suboptimal accuracy, complexity, high cost or long turnaround times for results. It is therefore critical to optimise their use to meet the needs of users. We used a simulation approach to estimate diagnostic outcomes, number of tests required and average turnaround time of using two-test algorithms compared with singular testing; the two tests were reverse transcription polymerase chain reaction (RT-PCR) and an antigen-based rapid diagnostic test (Ag-RDT). A web-based application of the model was developed to visualise and compare diagnostic outcomes for different disease prevalence and test performance characteristics (sensitivity and specificity). We tested the model using hypothetical prevalence data for COVID-19, representing low- and high-prevalence contexts and performance characteristics of RT-PCR and Ag-RDTs. The two-test algorithm when RT-PCR was applied to samples negative by Ag-RDT predicted gains in sensitivity of 27% and 7%, respectively, compared with Ag-RDT and RT-PCR alone. Similarly, when RT-PCR was applied to samples positive by Ag-RDT, specificity gains of 2.9% and 1.9%, respectively, were predicted. The algorithm using Ag-RDT followed by RT-PCR as a confirmatory test for positive patients limited the requirement of RT-PCR testing resources to 16,400 and 3,034 tests when testing a population of 100,000 with an infection prevalence of 20% and 0.05%, respectively. A two-test algorithm comprising a rapid screening test followed by confirmatory laboratory testing can reduce false positive rate, produce rapid results and conserve laboratory resources, but can lead to large number of missed cases in high prevalence setting. The web application of the model can identify the best testing strategies, tailored to specific use cases and we also present some examples how it was used as part of the Access to Covid-19 Tools (ACT) Accelerator Diagnostics Pillar.

Real-world Evaluation of a Sample Pooling Strategy for Large-Scale Rapid COVID-19 Testing

BackgroundThe worldwide outbreak of COVID-19 has become a public health crisis of unprecedented proportions. The fast spread of emerging variants increases the needs of rapid diagnostic and screening testing. Sample pooling efficiently expands the testing capacity under limited resources. ObjectivesWe evaluated the performance of sample pooling on the Point-of-Care (POC) Liat® and cobas® 6800 systems and provided real-world experiences for implementing these systems in large-scale screenings. MethodsPositive nasopharyngeal (NP) specimens with Ct values < 25, 25∼30 or > 30 were tested individually and in pools to optimize the POC Liat® and cobas® 6800 systems, which were then implemented in community screenings. ResultsThe 5-sample pooling strategy did not affect the positive detection rates on Liat® or cobas® 6800 in samples with Ct values <25 or 25∼30. However, in samples with low viral loads (Ct values >30), five-sample pooling has a higher positive detection rate on POC Liat® (20/20; 100%), compared to cobas® 6800 (9/20; 45%). Five-sample pooled on POC Liat® and two-sample pooled on cobas® 6800 appear to be appropriate for SARS-CoV-2 detection. By implementing the pooling strategies in two large-scale community screenings, 7,606 NP specimens was tested within 36 h; the average turn-around time was 4.8 h for cobas® 6800 and 1.3 h for POC Liat®. Eight positive specimens (0.11%; 8/7,606) were identified, with Ct values ranging from 18.85 to 37.68. ConclusionThe performance of sample pooling on POC Liat® was demonstrated to be an effective, accurate, and economical approach for large-scale community screenings for COVID-19.