Suboptimal Detection Research Articles

Implementation of the 7-1-7 target for detection, notification, and response to public health threats in five countries: a retrospective, observational study

Suboptimal detection and response to recent outbreaks, including COVID-19 and mpox (formerly known as monkeypox), have shown that the world is insufficiently prepared for public health threats. Routine monitoring of detection and response performance of health emergency systems through timeliness metrics has been proposed to evaluate and improve outbreak preparedness and contain health threats early. We implemented 7-1-7 to measure the timeliness of detection (target of ≤7 days from emergence), notification (target of ≤1 day from detection), and completion of seven early response actions (target of ≤7 days from notification), and we identified bottlenecks to and enablers of system performance. In this retrospective, observational study, we conducted reviews of public health events in Brazil, Ethiopia, Liberia, Nigeria, and Uganda with staff from ministries of health and national public health institutes. For selected public health events occurring from Jan 1, 2018, to Dec 31, 2022, we calculated timeliness intervals for detection, notification, and early response actions, and synthesised identified bottlenecks and enablers. We mapped bottlenecks and enablers to Joint External Evaluation (second edition) indicators. Of 41 public health events assessed, 22 (54%) met a target of 7 days to detect (median 6 days [range 0-157]), 29 (71%) met a target of 1 day to notify (0 days [0-24]), and 20 (49%) met a target of 7 days to complete all early response actions (8 days [0-72]). 11 (27%) events met the complete 7-1-7 target, with variation among event types. 25 (61%) of 41 bottlenecks to and 27 (51%) of 53 enablers of detection were at the health facility level, with delays to notification (14 [44%] of 32 bottlenecks) and response (22 [39%] of 56 bottlenecks) most often at an intermediate public health (ie, municipal, district, county, state, or province) level. Rapid resource mobilisation for responses (six [9%] of 65 enablers) from the national level enabled faster responses. The 7-1-7 target is feasible to measure and to achieve, and assessment with this framework can identify areas for performance improvement and help prioritise national planning. Increased investments must be made at the health facility and intermediate public health levels for improved systems to detect, notify, and rapidly respond to emerging public health threats. Bill & Melinda Gates Foundation.

Wind turbine anomaly detection based on SCADA: A deep autoencoder enhanced by fault instances

An increasing number of deep autoencoder-based algorithms for intelligent condition monitoring and anomaly detection have been reported in recent years to improve wind turbine reliability. However, most existing studies have only focused on the precise modeling of normal data in an unsupervised manner; few studies have utilized the information of fault instances in the learning process, which results in suboptimal detection performance and low robustness. To this end, we first developed a deep autoencoder enhanced by fault instances, that is, a triplet-convolutional deep autoencoder (triplet-Conv DAE), jointly integrating a convolutional autoencoder and deep metric learning. Aided by fault instances, triplet-Conv DAE can not only capture normal operation data patterns but also acquire discriminative deep embedding features. Moreover, to overcome the difficulty of scarce fault instances, we adopted an improved generative adversarial network-based data augmentation method to generate high-quality synthetic fault instances. Finally, we validated the performance of the proposed anomaly detection method using a multitude of performance measures. The experimental results show that our method is superior to three other state-of-the-art methods. In addition, the proposed augmentation method can efficiently improve the performance of the triplet-Conv DAE when fault instances are insufficient.

Zero echo time MRI in shoulder MRI protocols for the diagnosis of rotator cuff calcific tendinopathy improves identification of calcific deposits compared to conventional MR sequences but remains sub-optimal compared to radiographs.

To compare the diagnostic performance of standard MRI and standard MRI + ZTE images for the detection of rotator cuff calcific tendinopathy (RCCT) and to describe the artifacts encountered with ZTE images, using computed radiography (CR) as a reference. In a retrospective study, patients with suspicion of rotator cuff tendinopathy who underwent standard MRI + ZTE images after radiography were enrolled between June 2021 and June 2022. Images were independently analyzed for calcific deposit presence and ZTE images artifacts, by two radiologists. Diagnostic performance was calculated individually with MRI + CR as the reference standard. A total of 46 RCCT subjects (27 women; mean age, 55.3years ± 12.4) and 51 control subjects (27 men; mean age, 45.5 ± 12.9) were evaluated. For both readers, there was an increase in the sensitivity for the identification of calcific deposits of MRI + ZTE compared to MRI (77% (95% CI: 64.5-86.8) and 75.4% (95% CI: 62.7-85.5) versus 57.4% (95% IC: 44.1-70) and 47.5% (95% IC: 34.6-60.7), for R1 and R2, respectively). Specificity was quite similar for both readers and both imaging techniques and ranged from 96.6% (95% IC: 93.3-98.5) to 98.7% (95% IC: 96.3-99.7). Hyperintense joint fluid (62.8% of patients), long head of the biceps tendon (in 60.8%), and subacromial bursa (in 27.8%) on ZTE were considered artifactual. The addition of ZTE images to a standard MRI protocol improved MRI diagnostic performance of RCCT, but with a suboptimal detection rate and a relatively high frequency of artifactual soft tissue signal hyperintensity. • Adding ZTE images to standard shoulder MRI improves the MR-based detection of rotator cuff calcific tendinopathy, but half of the calcification unseen with standard MRI remained unseen with ZTE MRI. On ZTE images, joint fluid and long head biceps tendon were hyperintense in about 60% of the shoulders, as well as the subacromial bursa in about 30%, without calcific deposit on conventional radiographs. • The detection rate of calcific deposits using ZTE images was dependent on the disease phase. In the calcific stage, it reached 100% in this study but remained at a maximum of 80.7% in the resorptive phase.

Prevalence and influences of diabetes and prediabetes among adults living with HIV in Africa: a systematic review and meta-analysis.

In people living with human immunodeficiency virus (PLHIV), traditional cardiovascular risk factors, exposure to HIV per se and antiretroviral therapy (ART) are assumed to contribute to cardiometabolic diseases. Nevertheless, controversy exists on the relationship of HIV and ART with diabetes. To clarify the relationship between HIV and type 2 diabetes, this review determined, in PLHIV in Africa, diabetes and prediabetes prevalence, and the extent to which their relationship was modified by socio-demographic characteristics, body mass index (BMI), diagnostic definitions used for diabetes and prediabetes, and HIV-related characteristics, including CD4 count, and use and durationof ART. For this systematic review and meta-analysis (PROSPERO registration CRD42021231547), a comprehensive search of major databases (PubMed-MEDLINE, Scopus, Web of Science, Google Scholar and WHO Global Health Library) was conducted. Original research articles published between 2000 and 2021 in English and French were included, irrespective of study design, data collection techniques and diagnostic definitions used. Observational studies comprising at least 30 PLHIV and reporting on diabetes and/or prediabetes prevalence in Africa were included. Study-specific estimates were pooled using random effects models to generate the overall prevalence for each diagnostic definition. Data analyses used R statistical software and "meta" package. Of the 2614 records initially screened, 366 full-text articles were assessed for eligibility and 61 were selected. In the systematic review, all studies were cross-sectional by design and clinic-based, except for five population-based studies. Across studies included in the meta-analysis, the proportion of men was 16-84%. Mean/median age was 30-62 years. Among 86,412 and 7976 participants, diabetes and prediabetes prevalence rates were 5.1% (95% CI: 4.3-5.9) and 15.1% (9.7-21.5). Self-reported diabetes (3.5%) was lower than when combined with biochemical assessments (6.2%; 7.2%). While not statistically significant, diabetes and prediabetes were higher with greater BMI, in older participants, urban residents and more recent publications. Diabetes and prediabetes were not significantly different by HIV-related factors, including CD4 count and ART. Although HIV-related factors did not modify prevalence, the diabetes burden in African PLHIV was considerable with suboptimal detection, and likely influenced by traditional risk factors. Furthermore, high prediabetes prevalence foreshadows substantial increases in future diabetes in African PLHIV.

Low-Complexity Suboptimal ML Detection for OFDM-IM Systems

Orthogonal frequency division multiplexing with index modulation (OFDM-IM) is a novel multicarrier scheme, which uses <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> out of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${n}$ </tex-math></inline-formula> subcarriers as active subcarriers to transmit data. For detecting the subcarrier activation pattern (SAP) at the receiver, maximum likelihood (ML) detection cannot be used because of its high computational complexity. Instead, the detector selecting the most likely active <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> subcarriers is used, which is called a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> largest values ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> lv) detector. However, this method degrades the detection performance especially if the ratio of illegal SAPs to SAPs is high. In this letter, the suboptimal ML detector is proposed, which is a simple modification of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> lv detector, but very efficient. The proposed detector has a similar detection performance compared to the ML detection, which is suitable for flexible implementation of OFDM-IM systems.

Robust unsupervised network intrusion detection with self-supervised masked context reconstruction

Modern network intrusion detection systems always utilize deep learning to improve their intelligence and feature learning abilities. To overcome the difficulties of accessing a large amount of labeled data and achieve early warning, lots of intrusion detection systems focus on unsupervised anomaly detection methods. However, most unsupervised anomaly detection methods ignore the temporal context and anomaly contamination in network intrusion data, which leads to suboptimal detection results. By considering the above practical problems, we propose a robust unsupervised intrusion detection system, i.e, RUIDS, by introducing a masked context reconstruction module into a transformer-based self-supervised learning scheme. The self-supervised learning scheme is designed to learn the intrinsic relationship within temporal contexts. And the masked context reconstruction module can learn more robust representations which are less sensitive to anomaly contamination. Extensive experiments on four intrusion datasets are conducted to show the effectiveness and robustness of RUIDS. Specifically, RUIDS achieves 9.04% and 9.58% improvements over the second-best method on the UNSW-NB15 and CICIDS-WED datasets in terms of AUC value respectively. We also test the robustness of our method with different anomaly contamination ratios, and our algorithm’s performance has hardly decreased. The ablation study confirmed the effectiveness of the self-supervised learning scheme and the masked context reconstruction module.

A decade of blood-brain barrier permeability assays: Revisiting old traumatic brain injury rat data for new insights and experimental design.

Increased microvascular permeability at the level of the blood-brain barrier (BBB) often leads to vasogenic brain edema following traumatic brain injury (TBI). These pathologic conditions compromise the integrity of the neurovascular unit resulting in severe brain dysfunction. To quantify this permeability and assess ionic equillibrium, preclinical researchers have relied on the use of various molecular weight permeable dyes such as Evans Blue that normally cannot enter the brain parenchyma under homeostatic conditions. Evans Blue, the most cited of the molecular weight dyes, has reported reproducibility issues because of harsh extraction processes, suboptimal detection via absorbance, and wide excitation fluorescence spectra associated with the dye. Our laboratory group transitioned to Alexa Fluor 680, a far-red dye with improved sensitivity compared to Evans Blue and thus improved reproducibility to alleviate this issue. To evaluate our reproducibility and increase the rigor of our experimental design, we retrospectively analyzed our controlled cortical impact (CCI) experiments over the past 10years to evaluate effect size with larger samples and potential sources of variability. All of our BBB permeability experiments were performed with Male, Sprague Dawley rats weighing between 225 and 300g. Historically, Sprague Dawleys were randomly divided into treatment groups: SHAM, CCI, and a stem cell-based treatment from years 2007-2020. The assessment of microvascular hyperpermeability were evaluated by comparing the mean at minimum threshold, area at 1k-2k, and intensity density obtained from Alexa Fluor 680 permeability data. Studies utilizing Evans Blue were further compared by tip depth, diameter size, and the hemisphere of injury. Statistical evaluation utilizing the G Power software analysis did not yield a significant difference in sample size comparing experimental groups for Evans Blue and Alexa Fluor 680 analyzed brain tissue. Our analysis also demonstrated a trend in that recent studies (years 2018-2020) have yielded more compact sample sizes between experimental groups in Alexa Fluor 680 analyzed rats. This retrospective study further revealed that Alexa Fluor 680 image analysis provides greater sensitivity to BBB permeability following TBI in comparison to Evans Blue. Significant differences in sample size were not detected between Evans Blue and Alexa Fluor 680; there were significant differences found throughout year to year analysis at the lower range of thresholds. SUMMARY STATEMENT: This work provides a comparative analysis of BBB permeability assay techniques after CCI model of injury in rats.

Concurrent Transmission and Multiuser Detection of LoRa Signals

This article investigates a new model to improve the scalability of low-power long-range (LoRa) networks by allowing a group of multiple end devices (EDs) to communicate with multiple multi-antenna gateways simultaneously (i.e., in the same time slot) on the same frequency band and using the same spreading factor. The maximum-likelihood (ML) decision rule is first derived for noncoherent detection of information bits transmitted by multiple devices in a group. To overcome the high complexity of the ML detection, we propose a suboptimal two-stage detection algorithm to balance the computational complexity and error performance. In the first stage, we identify transmitted chirps (without knowing which EDs transmit them). In the second stage, we determine the EDs that transmit the specific chirps identified from the first stage. To improve the detection performance in the second stage, we also optimize the transmit powers of EDs to minimize the similarity, measured by the Jaccard coefficient, between the received powers of any pair of EDs in the same group. As the power control optimization problem is nonconvex, we use concepts from successive convex approximation to transform it to an approximate convex optimization problem that can be solved iteratively and guaranteed to reach a suboptimal solution. Simulation results demonstrate and justify the tradeoff between transmit power penalties and network scalability of the proposed LoRa network model. In particular, by grouping two or three EDs in each group for concurrent transmission, the uplink capacity of the proposed network can be doubled or tripled over that of a conventional LoRa network, albeit at the expense of additional 3.0 or 4.7 dB transmit power.

Error Analysis of Free Space Communication System Using Machine Learning

Free space optical (FSO) communication offers huge bandwidth, license-free spectrum and a more secure channel. PIN diodes are normally used for detection, but avalanche photodiodes (APD) are preferred for detecting high-speed FSO signals in many applications. In the case of APD, the noise distribution is input-dependent Gaussian noise (IDGN) rather than input-independent Gaussian noise (IIGN). We investigate the error analysis using on-off keying (OOK) for various detection approaches. This paper proposes a machine learning approach and compares its performance with soft and hard decisions. Soft values in the case of IDGN and IIGN are derived, and the optimum and sub-optimum detection thresholds are evaluated. The proposed novel ML approach shows better performance gains than the other approaches. It is also demonstrated that the IDGN model should have an optimum detection and achieve a gain of 2.5[dB] and about 1[dB] at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> = 0[dB] and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> = 10[dB], respectively. Experimental results are plotted for the FSO channel data, and a model fit curve is plotted using the ML approach.

FFN: Fountain Fusion Net for Arbitrary-Oriented Object Detection

Arbitrary-oriented object detection (AOOD) is widely used in aerial images because of its efficient object representation. However, current detectors employ the over-standardized feature extraction structure, resulting in detectors has no ability to adaptively readjust feature representations of detection units. Meanwhile, we observe that many detection units could not focus on the objects of interest in their receptive field and are easily affected by the background information and interference targets, leading to the weaking of feature expression ability. We call them sub-optimal detection units. To address this issue, we propose a novel feature enhancement module called fountain feature enhancement module (FFEM). FFEM ingeniously uses the fountain-like structure to reconstruct the features of sub-optimal detection units, generating fountain features that can automatically condense spatial regional features, which effectively enhances detectors’ overall representation ability. Then, a high-performance AOOD detector called fountain fusion net (FFN) is proposed with FFEM embedded, and many novel AOOD components are tested for their progressiveness. We validated our FFN and FFEM using three remote sensing datasets ‒ DOTA, HRSC2016, and UCAS-AOD as well as one scene text dataset‒ICDAR 2015. Extensive experiments demonstrate the effectiveness of our proposed method on improving current detectors to achieve state-of-the-art performance based on this novel idea.

Over-the-air beamforming with reconfigurable intelligent surfaces

Reconfigurable intelligent surface (RIS)-empowered communication is a revolutionary technology that enables to manipulate wireless propagation environment via smartly controllable low-cost reflecting surfaces. However, in order to outperform conventional communication systems, an RIS-aided system with solely passive reflection requires an extremely large surface. To meet this challenge, the concept of active RIS, which performs simultaneous amplification and reflection on the incident signal at the expense of additional power consumption, has been recently introduced. In this paper, deploying an active RIS, we propose a novel beamforming concept, over-the-air beamforming, for RIS-aided multi-user multiple-input single-output (MISO) transmission schemes without requiring any pre/post signal processing hardware designs at the transmitter and receiver sides. In the proposed over-the-air beamforming-based transmission scheme, the reflection coefficients of the active RIS elements are customized to maximize the sum-rate gain. To tackle this issue, first, a non-convex quadratically constrained quadratic programming (QCQP) problem is formulated. Then, using semidefinite relaxation (SDR) approach, this optimization problem is converted to a convex feasibility problem, which is efficiently solved using the CVX optimization toolbox. Moreover, taking inspiration from this beamforming technique, a novel high-rate receive index modulation (IM) scheme with a low-complexity sub-optimal detector is developed. Through comprehensive simulation results, the sum-rate and bit error rate (BER) performance of the proposed designs are investigated.

Nucleic acid vaccination strategies for ovarian cancer.

High grade serous carcinoma (HGSC) is one of the most lethal ovarian cancers that is characterised by asymptomatic tumour growth, insufficient knowledge of malignant cell origin and sub-optimal detection. HGSC has been recently shown to originate in the fallopian tube and not in the ovaries. Conventional treatments such as chemotherapy and surgery depend upon the stage of the disease and have resulted in higher rates of relapse. Hence, there is a need for alternative treatments. Differential antigen expression levels have been utilised for early detection of the cancer and could be employed in vaccination strategies using nucleic acids. In this review the different vaccination strategies in Ovarian cancer are discussed and reviewed. Nucleic acid vaccination strategies have been proven to produce a higher CD8+ CTL response alongside CD4+ T-cell response when compared to other vaccination strategies and thus provide a good arena for antitumour immune therapy. DNA and mRNA need to be delivered into the intracellular matrix. To overcome ineffective naked delivery of the nucleic acid cargo, a suitable delivery system is required. This review also considers the suitability of cell penetrating peptides as a tool for nucleic acid vaccine delivery in ovarian cancer.

Endoscopist Characteristics and Polyp Detection in Colonoscopy: Cross-Sectional Analyses of Screening of Swedish Colons

Endoscopist Characteristics and Polyp Detection in Colonoscopy: Cross-Sectional Analyses of Screening of Swedish Colons

Large Scale MIMO Analysis Using Enhanced LAMA

In this research work, we propose a enhanced large scale multi-input multi-output (MIMO) approximate message passing (LAMA) based optimal data detector for large scale MIMO systems. Existing LAMA and sub-optimal detection techniques suffer from iteration complexity and performance loss in finite dimensional systems due to large scale user fading. To overcome these, Gram matrix and message damping techniques are incorporated in the traditional LAMA. The effectiveness of the proposed enhanced LAMA and existing techniques are analyzed with 64, 32 and 16 user antennas, 256, 128, 64 and 16 base station elements with 64QAM, 16QAM, QPSK and BPSK. The simulation results show that the proposed enhanced LAMA gives better performance when compared to existing matrix inversion methods such as Gauss-Seidel and Neumann, box techniques such as optimal co-ordinate descent and alternating direction method of multipliers based on the infinity norm, minimum mean square error and LAMA.

Knowledge, attitude and practice of community pharmacy personnel in tuberculosis patient detection: a multicentre cross-sectional study in a high-burden tuberculosis setting

IntroductionControl of tuberculosis (TB) is hampered by suboptimal case detection and subsequent delays in treatment, which is worsened by the COVID-19 pandemic. The community pharmacy is reported as the place...

Trends in TB and HIV care and treatment cascade, Kenya, 2008-2018.

BACKGROUND: HIV infection is associated with high mortality among people with TB. Antiretroviral therapy (ART) reduces TB incidence and mortality among people living with HIV (PLHIV). Since 2005, Kenya has scaled up TB and HIV prevention, diagnosis and treatment. We evaluated the impact of these services on trends and TB treatment outcomes.METHODS: Using Microsoft Excel (2016) and Epi-Info 7, we analysed Kenya Ministry of Health TB surveillance data from 2008 to 2018 to determine trends in TB notifications, TB classification, HIV and ART status, and TB treatment outcomes.RESULTS: Among the 1,047,406 people reported with TB, 93% knew their HIV status, and 37% of these were HIV-positive. Among persons with TB and HIV, 69% received ART. Between 2008 and 2018, annual TB notifications declined from 110,252 to 96,562, and HIV-coinfection declined from 45% to 27%. HIV testing and ART uptake increased from 83% to 98% and from 30% to 97%, respectively. TB case fatality rose from 3.5% to 3.9% (P <0.018) among HIV-negative people and from 5.1% to 11.2% (P <0.001) among PLHIV on ART.CONCLUSION: TB notifications decreased in settings with suboptimal case detection. Although HIV-TB services were scaled-up, HIV-TB case fatality rose significantly. Concerted efforts are needed to address case detection and gaps in quality of TB care.

A Sea-Surface-Zoning Method Based on Fractal Characteristics

In this paper, a criterion for sea surface zoning based on the fractal characteristics of disturbances is demonstrated. To improve radar detection performance in heavy-tailed sea clutter, a multitude of sea clutter models and corresponding optimum and suboptimum detectors have been designed in recent years. However, there are cases where these models and detectors become insufficient to describe the coexistence of noise and sea clutter. The commonly used signal-to-clutter ratio (SCR) can hardly serve as an indicator revealing which kind of disturbances dominate in a certain area since it is difficult to decide the level of SCR at which sea clutter or noise exceeds the other. Therefore, it is necessary that a set of rules reflecting essential differences between sea clutter and noise are proposed to tell areas where sea clutter dominates, areas where sea clutter and noise coexist and areas where noise dominates. Analyzing fractal characteristics of disturbances, we consider the Hurst exponent H as a feature distinguishing sea clutter and noise from each other. A modified Sigmoid function is employed to model the variation in H with range bins, and the derivative of the function helps to formulate a set of rules for sea surface zoning.

Racial disparities in hypertension management among multiple sclerosis patients

BackgroundHypertension adversely impacts the multiple sclerosis (MS) disease course and is more common among Black Americans. Disparities in care due to structural racism may lead to suboptimal hypertension detection and control in Black American MS patients. ObjectivesTo determine if uncontrolled hypertension is more common in Black or White Americans with MS and whether race impacts the likelihood of receiving anti-hypertensive treatment. MethodsA retrospective cohort study was conducted using longitudinal data from American participants in the Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) multi-institutional registry. Data was collected from 7 sites in the United States between May 2015 and November 2020. Patients with uncontrolled hypertension, defined as ≥2 blood pressure measurements ≥140/90 mmHg, were identified in the dataset. Racial differences in uncontrolled hypertension and odds of anti-hypertensive treatment were evaluated using logistic regression. Predictors of anti-hypertensive treatment in those with uncontrolled hypertension were determined by race. ResultsThe analysis included 10,673 MS patients, of whom 1,442 (13.5%) were Black Americans. Despite a lower mean age (45.7 vs. 49.2 years), Black Americans had a 31% increased odds of uncontrolled hypertension compared to White Americans. After adjustment for relevant covariates, mean systolic blood pressure was 1.84 mmHg (95% confidence interval=1.07-2.61) higher in Black Americans than White Americans, and mean diastolic blood pressure was 1.28 mmHg (95% confidence interval=0.74-1.82) higher. Black Americans were also more likely to be on anti-hypertensive therapy (OR=1.68, 95% confidence interval=1.30-2.18) and were exposed to an adjusted average of 0.61 (95% confidence interval=0.45-0.78) more anti-hypertensive treatments than White Americans (p<0.001). Age, comorbid diabetes mellitus, and comorbid hyperlipidemia were positively associated with use of anti-hypertensive treatments in all patients with uncontrolled hypertension. ConclusionBlack American MS patients have significantly increased odds of uncontrolled hypertension, but also higher odds of receiving anti-hypertensive treatment.

Redesign and Validation of a Real-Time RT-PCR to Improve Surveillance for Avian Influenza Viruses of the H9 Subtype.

Avian influenza viruses of the H9 subtype cause significant losses to poultry production in endemic regions of Asia, Africa and the Middle East and pose a risk to human health. The availability of reliable and updated diagnostic tools for H9 surveillance is thus paramount to ensure the prompt identification of this subtype. The genetic variability of H9 represents a challenge for molecular-based diagnostic methods and was the cause for suboptimal detection and false negatives during routine diagnostic monitoring. Starting from a dataset of sequences related to viruses of different origins and clades (Y439, Y280, G1), a bioinformatics workflow was optimized to extract relevant sequence data preparatory for oligonucleotides design. Analytical and diagnostic performances were assessed according to the OIE standards. To facilitate assay deployment, amplification conditions were optimized with different nucleic extraction systems and amplification kits. Performance of the new real-time RT-PCR was also evaluated in comparison to existing H9-detection methods, highlighting a significant improvement of sensitivity and inclusivity, in particular for G1 viruses. Data obtained suggest that the new assay has the potential to be employed under different settings and geographic areas for a sensitive detection of H9 viruses.

PREVALENCE OF DIABETES AND PREDIABETES AMONG ADULTS WITH HIV IN AFRICA: A SYSTEMATIC REVIEW AND META-ANALYSIS

Objective: Debate is ongoing on the relationship between HIV infection and type 2 diabetes mellitus with increased risk and no difference described in European populations. A systematic review and meta-analysis were conducted to 1) determine the pooled prevalence of diabetes and prediabetes among people living with HIV (PLWH) in Africa, and 2) examine the magnitude of diabetes and prediabetes by sociodemographic characteristics, body mass index, definitions used for diabetes and prediabetes diagnoses, and HIV-related characteristics. Design and method: A comprehensive search of major databases was conducted for original research articles published between 2000 and 2021. Relevant studies in English and French were included, irrespective of study design, data collection techniques and diagnostic definitions used. Study-specific estimates were pooled using random effects models to generate the overall prevalence of diabetes and prediabetes for each diagnostic definition and relevant sub-groups. Data analyses were conducted using the R statistical software and the “meta’’ package. Results: Of the 2211 records initially screened, 54 were selected from 346 full-text articles assessed for eligibility. Most included studies were from South Africa (n = 15), Tanzania (n = 7), Ethiopia (n = 6), with four each from Cameroon, Malawi and Uganda. All studies were cross-sectional by design and clinic-based, except for four population-based studies. The proportion of men ranged from 16–52%. Mean/median age ranged from 29–62 years. Diabetes prevalence was 4.8% (95%CI: 4.02–5.59) among 101,704 participants; biochemical testing combined with self-reported diabetes yielded a higher prevalence (oral glucose tolerance test: 6.2%, 95%CI: 2.5–11.3; fasting blood glucose: 6.4%, 95%CI: 4.9–8.1) than self-reported diabetes prevalence alone (3.7%, 95%CI: 2.5–5.2). Prediabetes prevalence was 13.7% (95%CI: 10.21–17.59) among 13,502 participants. There were no statistically significant differences in diabetes or prediabetes prevalence by sub-groups examined, including CD4 count, and antiretroviral treatment status and duration. Conclusions: Diabetes prevalence in PLWH in Africa probably reflects that of general populations with similar influences. The lower prevalence of self-reported diabetes vs. biochemical testing with self-report possibly demonstrates suboptimal diabetes detection in this vulnerable group who are in regular contact with healthcare services. The high prevalence of prediabetes likely foreshadows a substantial increase in future diabetes in African PLWH.