Kaposi's Sarcoma-Associated Herpesvirus-Related Solid Lymphoma Involving the Heart and Brain

Since its discovery in 1994, Kaposi's sarcoma-associated herpesvirus (KSHV) has been associated with lymphoproliferative disorders, particularly in patients infected with human immunodeficiency virus (HIV). The disorders most strongly linked to KSHV are multicentric Castleman's Disease (MCD), primary effusion lymphoma, and diffuse large B-cell lymphomas. We report an unusual case of KSHV-associated lymphoma in an HIV-infected patient manifesting with myocardial and central nervous system involvement. We discuss this case in the context of increasing array of KSHV-associated lymphomas. In the HIV-infected patient with a mass lesion, a history of cutaneous Kaposi's sarcoma and prolonged immunosuppression should alert clinicians as to the possibility of KSHV-associated lymphoproliferative disorders, in order to establish a timely diagnosis

The importance of implementation strategy in scaling up Xpert MTB/RIF for diagnosis of tuberculosis in the Indian health-care system: a transmission model.

BACKGROUND: India has announced a goal of universal access to quality tuberculosis (TB) diagnosis and treatment. A number of novel diagnostics could help meet this important goal. The rollout of one such diagnostic, Xpert MTB/RIF (Xpert) is being considered, but if Xpert is used mainly for people with HIV or high risk of multidrug-resistant TB (MDR-TB) in the public sector, population-level impact may be limited. METHODS AND FINDINGS: We developed a model of TB transmission, care-seeking behavior, and diagnostic/treatment practices in India and explored the impact of six different rollout strategies. Providing Xpert to 40% of public-sector patients with HIV or prior TB treatment (similar to current national strategy) reduced TB incidence by 0.2% (95% uncertainty range [UR]: -1.4%, 1.7%) and MDR-TB incidence by 2.4% (95% UR: -5.2%, 9.1%) relative to existing practice but required 2,500 additional MDR-TB treatments and 60 four-module GeneXpert systems at maximum capacity. Further including 20% of unselected symptomatic individuals in the public sector required 700 systems and reduced incidence by 2.1% (95% UR: 0.5%, 3.9%); a similar approach involving qualified private providers (providers who have received at least some training in allopathic or non-allopathic medicine) reduced incidence by 6.0% (95% UR: 3.9%, 7.9%) with similar resource outlay, but only if high treatment success was assured. Engaging 20% of all private-sector providers (qualified and informal [providers with no formal medical training]) had the greatest impact (14.1% reduction, 95% UR: 10.6%, 16.9%), but required >2,200 systems and reliable treatment referral. Improving referrals from informal providers for smear-based diagnosis in the public sector (without Xpert rollout) had substantially greater impact (6.3% reduction) than Xpert scale-up within the public sector. These findings are subject to substantial uncertainty regarding private-sector treatment patterns, patient care-seeking behavior, symptoms, and infectiousness over time; these uncertainties should be addressed by future research. CONCLUSIONS: The impact of new diagnostics for TB control in India depends on implementation within the complex, fragmented health-care system. Transformative strategies will require private/informal-sector engagement, adequate referral systems, improved treatment quality, and substantial resources. Please see later in the article for the Editors' Summary

Accelerating LSTM-based High-Rate Dynamic System Models

In this paper, we evaluate the use of a trained Long Short-Term Memory (LSTM) network as a surrogate for a Euler-Bernoulli beam model, and then we describe and characterize an FPGA-based deployment of the model for use in real-time structural health monitoring applications. The focus of our efforts is the DROPBEAR (Dynamic Reproduction of Projectiles in Ballistic Environments for Advanced Research) dataset, which was generated as a benchmark for the study of real-time structural modeling applications. The purpose of DROPBEAR is to evaluate models that take vibration data as input and give the initial conditions of the cantilever beam on which the measurements were taken as output. DROPBEAR is meant to serve an exemplar for emerging high-rate "active structures" that can be actively controlled with feedback latencies of less than one microsecond. Although the Euler-Bernoulli beam model is a well-known solution to this modeling problem, its computational cost is prohibitive for the time scales of interest. It has been previously shown that a properly structured LSTM network can achieve comparable accuracy with less workload, but achieving sub-microsecond model latency remains a challenge. Our approach is to deploy the LSTM optimized specifically for latency on FPGA. We designed the model using both high-level synthesis (HLS) and hardware description language (HDL). The lowest latency of 1.42 $\mu$S and the highest throughput of 7.87 Gops/s were achieved on Alveo U55C platform for HDL design.Comment: Accepted at 33rd International Conference on Field-Programmable Logic and Applications (FPL

Integrating facility-based surveillance with healthcare utilization surveys to estimate enteric fever incidence: Methods and challenges

Cohort studies and facility-based sentinel surveillance are common approaches to characterizing infectious disease burden, but present trade-offs; cohort studies are resource-intensive and may alter disease natural history, while sentinel surveillance underestimates incidence in the population. Hybrid surveillance, whereby facility-based surveillance is paired with a community-based healthcare utilization assessment, represents an alternative approach to generating population-based disease incidence estimates with moderate resource investments. Here, we discuss this method in the context of the Surveillance for Enteric Fever in Asia Project (SEAP) study. We describe how data are collected and utilized to adjust enteric fever incidence for blood culture sensitivity, facility-based enrollment, and healthcare seeking, incorporating uncertainty in these parameters in the uncertainty around incidence estimates. We illustrate how selection of surveillance sites and their coverage may influence precision and bias, and we identify approaches in the study design and analysis to minimize and control for these biases. Rigorously designed hybrid surveillance systems can be an efficient approach to generating population-based incidence estimates for infectious diseases

Drivers of Tuberculosis Transmission.

Measuring tuberculosis transmission is exceedingly difficult, given the remarkable variability in the timing of clinical disease after Mycobacterium tuberculosis infection; incident disease can result from either a recent (ie, weeks to months) or a remote (ie, several years to decades) infection event. Although we cannot identify with certainty the timing and location of tuberculosis transmission for individuals, approaches for estimating the individual probability of recent transmission and for estimating the fraction of tuberculosis cases due to recent transmission in populations have been developed. Data used to estimate the probable burden of recent transmission include tuberculosis case notifications in young children and trends in tuberculin skin test and interferon γ-release assays. More recently, M. tuberculosis whole-genome sequencing has been used to estimate population levels of recent transmission, identify the distribution of specific strains within communities, and decipher chains of transmission among culture-positive tuberculosis cases. The factors that drive the transmission of tuberculosis in communities depend on the burden of prevalent tuberculosis; the ways in which individuals live, work, and interact (eg, congregate settings); and the capacity of healthcare and public health systems to identify and effectively treat individuals with infectious forms of tuberculosis. Here we provide an overview of these factors, describe tools for measurement of ongoing transmission, and highlight knowledge gaps that must be addressed

Evaluation of a urine pooling strategy for the rapid and cost-efficient prevalence classification of schistosomiasis

A key epidemiologic feature of schistosomiasis is its focal distribution, which has important implications for the spatial targeting of preventive chemotherapy programs. We evaluated the diagnostic accuracy of a urine pooling strategy using a point-of-care circulating cathodic antigen (POC-CCA) cassette test for detection of Schistosoma mansoni, and employed simulation modeling to test the classification accuracy and efficiency of this strategy in determining where preventive chemotherapy is needed in low-endemicity settings.; We performed a cross-sectional study involving 114 children aged 6-15 years in six neighborhoods in Azaguié Ahoua, south Côte d'Ivoire to characterize the sensitivity and specificity of the POC-CCA cassette test with urine samples that were tested individually and in pools of 4, 8, and 12. We used a Bayesian latent class model to estimate test characteristics for individual POC-CCA and quadruplicate Kato-Katz thick smears on stool samples. We then developed a microsimulation model and used lot quality assurance sampling to test the performance, number of tests, and total cost per school for each pooled testing strategy to predict the binary need for school-based preventive chemotherapy using a 10% prevalence threshold for treatment.; The sensitivity of the urine pooling strategy for S. mansoni diagnosis using pool sizes of 4, 8, and 12 was 85.9%, 79.5%, and 65.4%, respectively, when POC-CCA trace results were considered positive, and 61.5%, 47.4%, and 30.8% when POC-CCA trace results were considered negative. The modeled specificity ranged from 94.0-97.7% for the urine pooling strategies (when POC-CCA trace results were considered negative). The urine pooling strategy, regardless of the pool size, gave comparable and often superior classification performance to stool microscopy for the same number of tests. The urine pooling strategy with a pool size of 4 reduced the number of tests and total cost compared to classical stool microscopy.; This study introduces a method for rapid and efficient S. mansoni prevalence estimation through examining pooled urine samples with POC-CCA as an alternative to widely used stool microscopy

Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis.

BACKGROUND: Congregate settings may serve as institutional amplifiers of tuberculosis (TB) and multidrug-resistant tuberculosis (MDR-TB). We analyze spatial, epidemiological, and pathogen genetic data prospectively collected from neighborhoods surrounding a prison in Lima, Peru, where inmates experience a high risk of MDR-TB, to investigate the risk of spillover into the surrounding community. METHODS: Using hierarchical Bayesian statistical modeling, we address three questions regarding the MDR-TB risk: (i) Does the excess risk observed among prisoners also extend outside the prison? (ii) If so, what is the magnitude, shape, and spatial range of this spillover effect? (iii) Is there evidence of additional transmission across the region? RESULTS: The region of spillover risk extends for 5.47 km outside of the prison (95% credible interval: 1.38, 9.63 km). Within this spillover region, we find that nine of the 467 non-inmate patients (35 with MDR-TB) have MDR-TB strains that are genetic matches to strains collected from current inmates with MDR-TB, compared to seven out of 1080 patients (89 with MDR-TB) outside the spillover region (p values: 0.022 and 0.008). We also identify eight spatially aggregated genetic clusters of MDR-TB, four within the spillover region, consistent with local transmission among individuals living close to the prison. CONCLUSIONS: We demonstrate a clear prison spillover effect in this population, which suggests that interventions in the prison may have benefits that extend to the surrounding community