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The COVID-19 pandemic has caused widespread disruptions including to health services. In the early response to the pandemic many countries restricted population movements and some health services were suspended or limited. In late 2020 and early 2021 some countries re-imposed restrictions. Health authorities need to balance the potential harms of additional SARS-CoV-2 transmission due to contacts associated with health services against the benefits of those services, including fewer new HIV infections and deaths. This paper examines these trade-offs for select HIV services. We used four HIV simulation models (Goals, HIV Synthesis, Optima HIV and EMOD) to estimate the benefits of continuing HIV services in terms of fewer new HIV infections and deaths. We used three COVID-19 transmission models (Covasim, Cooper/Smith and a simple contact model) to estimate the additional deaths due to SARS-CoV-2 transmission among health workers and clients. We examined four HIV services: voluntary medical male circumcision, HIV diagnostic testing, viral load testing and programs to prevent mother-to-child transmission. We compared COVID-19 deaths in 2020 and 2021 with HIV deaths occurring now and over the next 50 years discounted to present value. The models were applied to countries with a range of HIV and COVID-19 epidemics. Maintaining these HIV services could lead to additional COVID-19 deaths of 0.002 to 0.15 per 10,000 clients. HIV-related deaths averted are estimated to be much larger, 19-146 discounted deaths per 10,000 clients. While there is some additional short-term risk of SARS-CoV-2 transmission associated with providing HIV services, the risk of additional COVID-19 deaths is at least 100 times less than the HIV deaths averted by those services. Ministries of Health need to take into account many factors in deciding when and how to offer essential health services during the COVID-19 pandemic. This work shows that the benefits of continuing key HIV services are far larger than the risks of additional SARS-CoV-2 transmission.

Malawi has 991,600 people living with HIV and has expanded access to annual HIV viral load testing to enhance care quality for clients. However, significant delays persist in returning viral load (VL) results back to facilities and to clients. To address this, we implemented a digital VL results return (VLRR) application, using existing mobile phone platforms to expedite results return to clients and healthcare providers (HCPs).VLRR is a digital SMS/USSD platform leveraging mobile phones to reduce turnaround time (TAT) and improve access to VL results. To evaluate the VLRR intervention, we: (1) estimated the TAT for digital results return, (2) calculated open rates of digital results, (3) conducted a mixed methods evaluation with VLRR users, and (4) estimated the potential cost savings from avoiding unnecessary sample redraws. From April 2022 to June 2024, HCPs registered 4,067 clients. For each client, TAT was calculated separately for the periods before and after enrollment in the VLRR system. On average during this period, clients received results in 128 days before VLRR enrollment and 48.5 days after enrollment, reflecting a 62.4% improvement. By July 2023, VLRR clients and HCPs received results in an average of 30 and 38 days. The overall open rate for digital results (opened by either a client or HCP) was 60% and nearly 100% of clients and HCPs indicated they wanted to the application to continue. Lastly, if VLRR were scaled nationally, it has the potential cost savings of $1.8-6.7 million USD.VLRR is effective in reducing TAT and improving access to VL results. To enhance uptake and achieve national scale, VLRR can be integrated into Malawi’s existing EMR systems, further reducing TAT and enabling HCPs to deliver higher quality care and improve clinical outcomes.

To determine whether visual-tactile sensory substitution utilizing the Low-vision Enhancement Optoelectronic (LEO) Belt prototype is suitable as a new visual aid for those with reduced peripheral vision by assessing mobility performance and user opinions. Sighted subjects (n = 20) and subjects with retinitis pigmentosa (RP) (n = 6) were recruited. The LEO Belt was evaluated on two cohorts: normally sighted subjects wearing goggles to artificially reduce peripheral vision to simulate stages of RP progression, and subjects with advanced visual field limitation from RP. Mobility speed and accuracy was assessed using simple mazes, with and without the LEO Belt, to determine its usefulness across disease severities and lighting conditions. Sighted subjects wearing most narrowed field goggles simulating most advanced RP had increased mobility accuracy (44% mean reduction in errors, p = 0.014) and self-reported confidence (77% mean increase, p = 0.004) when using the LEO Belt. Additionally, use of LEO doubled mobility accuracy for RP subjects with remaining visual fields between 10° and 20°. Further, in dim lighting, confidence scores for this group also doubled. By patient reported outcomes, subjects largely deemed the device comfortable (100%), easy to use (92.3%) and thought it had potential future benefit as a visual aid (96.2%). However, regardless of severity of vision loss or simulated vision loss, all subjects were slower to complete the mazes using the device. The LEO Belt improves mobility accuracy and therefore confidence in those with severely restricted peripheral vision. The LEO Belt's positive user feedback suggests it has potential to become the next generation of visual aid for visually impaired individuals. Given the novelty of this approach, we expect navigation speeds may improve with experience.

Photoacoustic (PA) imaging combines optical excitation with ultrasonic detection to achieve high-resolution imaging of biological samples. A high-energy pulsed laser is often used for imaging at multi-centimeter depths in tissue. These lasers typically have a low pulse repetition rate, so to acquire images in real-time, only one pulse of the laser can be used per image. This single pulse necessitates the use of many individual detectors and receive electronics to adequately record the resulting acoustic waves and form an image. Such requirements make many PA imaging systems both costly and complex. This investigation proposes and models a method of volumetric PA imaging using a state-of-the-art compressed sensing approach to achieve real-time acquisition of the initial pressure distribution (IPD) at a reduced level of cost and complexity. In particular, a single exposure of an optical image sensor is used to capture an entire Fabry–Pérot interferometric acoustic sensor. Time resolved encoding as achieved through spatial sweeping with a galvanometer. This optical system further makes use of a random binary mask to set a predetermined subset of pixels to zero, thus enabling recovery of the time-resolved signals. The Two-Step Iterative Shrinking and Thresholding algorithm is used to reconstruct the IPD, harnessing the sparsity naturally occurring in the IPD as well as the additional structure provided by the binary mask. We conduct experiments on simulated data and analyze the performance of our new approach.

ObjectivesKey populations, including sex workers, men who have sex with men, and people who inject drugs, have a high risk of HIV and sexually transmitted infections. We assessed the health and economic impacts of different HIV and syphilis testing strategies among three key populations in Viet Nam using a dual HIV/syphilis rapid diagnostic test (RDT).SettingWe used the spectrum AIDS impact model to simulate the HIV epidemic in Viet Nam and evaluated five testing scenarios among key populations. We used a 15-year time horizon and a provider perspective for costs.ParticipantsWe simulate the entire population of Viet Nam in the model.InterventionsWe modelled five testing scenarios among key populations: (1) annual testing with an HIV RDT, (2) annual testing with a dual RDT, (3) biannual testing using dual RDT and HIV RDT, (4) biannual testing using HIV RDT and (5) biannual testing using dual RDT.Primary and secondary outcome measuresThe primary outcome is incremental cost-effectiveness ratios. Secondary outcomes include HIV and syphilis cases.ResultsAnnual testing using a dual HIV/syphilis RDT was cost-effective (US$10 per disability-adjusted life year (DALY)) and averted 3206 HIV cases and treated 27 727 syphilis cases compared with baseline over 15 years. Biannual testing using one dual test and one HIV RDT (US$1166 per DALY), or two dual tests (US$5672 per DALY) both averted an additional 875 HIV cases, although only the former scenario was cost-effective. Annual or biannual HIV testing using HIV RDTs and separate syphilis tests were more costly and less effective than using one or two dual RDTs.ConclusionsAnnual HIV and syphilis testing using dual RDT among key populations is cost-effective in Vietnam and similar settings to reach global reduction goals for HIV and syphilis.

BackgroundInnovative and efficient methods are needed to identify remaining people living with HIV unaware of their status. Routine health information system (RHIS) data, widely available in high-burden HIV settings, may help target areas of high risk to deliver timely prevention services. Often underused, RHIS data were leveraged at the facility level to predict changes in HIV test positivity in Malawi.MethodsFrom District Health Information Software-2 from January 2017 to March 2023, we analysed sexually transmitted infection (STI) cases and HIV tests and test results across 563 health facilities in Malawi. A multilevel model was employed to determine whether changes in STI diagnoses were predictive of changes in HIV test positivity. We considered STI types and their incubation periods, and controlled for facility type, ownership, quarter, season, zonal HIV and STI prevalence (2016 Population-Based HIV Impact Assessment).ResultsAmong 139 million HIV tests, overall positivity was 2.8%. Blantyre facilities had the highest positivity (6.0%) while those in the central-east zone had the lowest (1.8%). Key variables—changes in syndromic STI counts (lagged and cross-sectional)—showed weak or no associations with HIV positivity (OR: 1.01, CI: 1.01 to 1.01; OR: 1.00, CI: 1.00 to 1.00). However, contextual covariates, including zonal HIV prevalence (OR: 1.04, CI: 1.04 to 1.04), genital ulcers (OR: 1.16, CI: 1.16 to 1.16) and clinical STI diagnoses (OR: 1.29, CI: 1.29 to 1.29), were positively associated with HIV positivity.ConclusionsIn settings with high STI screening uptake, RHIS data can be used to monitor changes in STI diagnoses and contextual factors to identify HIV hotspots and guide targeted testing, prevention and treatment services.

The COVID-19 global pandemic has had considerable health impact, including sub-Saharan Africa. In Malawi, a resource-limited setting in Africa, gaining access to data to inform the COVID-19 response is challenging. Information on adherence to physical distancing guidelines and reducing contacts are nonexistent, but critical to understanding and communicating risk, as well as allocating scarce resources. We present a case study which leverages aggregated call detail records into a daily data pipeline which summarize population density and mobility in an easy-to-use dashboard for public health officials and emergency operations. From March to April 2021, we have aggregated 6-billion calls and text messages and continue to process 12 million more daily. These data are summarized into reports which describe, quantify, and locate mass gatherings and travel between subdistricts. These reports are accessible via web dashboards for policymakers within the Ministry of Health and Emergency Operations Center to inform COVID-19 response efforts and resource allocation.

Background Despite policies for universal HIV testing and treatment (UTT) regardless of CD4 count, there are still 1.8 million new HIV infections and 1 million AIDS-related deaths annually. The UNAIDS 90-90-90 goals target suppression of HIV viral load in 73% of all HIV-infected people worldwide by 2030. However, achieving these targets may not lead to expected reductions in HIV incidence if the remaining 27% (persons with unsuppressed viral load) are the drivers of HIV transmission through high-risk behaviors. We aim to conduct a systematic review and meta-analysis to understand the demographics, mobility, geographic distribution, and risk profile of adults who are not virologically suppressed in sub-Saharan Africa in the era of UTT. Methods We will review the published and grey literature for study sources that contain data on demographic and behavioral strata of virologically suppressed and unsuppressed populations since 2014. We will search PubMed and Embase using four sets of search terms tailored to identify characteristics associated with virological suppression (or lack thereof) and each of the individual 90-90-90 goals. Record screening and data abstraction will be done independently and in duplicate. We will use random effects meta-regression analyses to estimate the distribution of demographic and risk features among groups not virologically suppressed and for each individual 90-90-90 goal. Discussion The results of our review will help elucidate factors associated with failure to achieve virological suppression in sub-Saharan Africa, as well as factors associated with failure to achieve each of the 90-90-90 goals. These data will help quantify the population-level effects of current HIV treatment interventions to improve strategies for maximizing virological suppression and ending the HIV epidemic. Systematic review registration PROSPERO CRD42018089505 .

The nature of Dark Energy is one of the most significant and compelling unsolved problems in physics today. Stage-IV spectroscopic surveys like the Dark Energy Spectroscopic Instrument (DESI) aim to try probe this unknown sector of physics using observables like Baryon Acoustic Oscillations (BAO). DESI recently released its Year Three results, with some of the tightest constraints on the composition of the universe recorded to date.DESI uses a state of the art software and data processing pipeline that makes significant use of a variety of machine learning algorithms. I present in this work a selection of four different machine learning and algebraic techniques developed for use as part of the DESI survey. The first algorithm applies deep learning to the problem of cosmic ray identification and rejection. Cosmic rays are a persistent source of error when extracting spectroscopy from raw CCD images and thus necessitate an accurate and fast algorithm for detection and masking.The second algorithm is QuasarNET, a deep convolutional neural network designed to automatically classify quasars in raw DESI spectra. QuasarNET also estimates a quasar redshift for each quasar identified. In my work we retrain QuasarNET using an algorithm called Active Learning, which automatically determines which unlabeled spectra would be beneficialto label. We then use those newly labeled spectra as a training dataset for QuasarNET, in the process discovering and later fixing a systemic problem with QuasarNET redshift estimates. This new weights file was used for DESI Year Three analysis and will be used in Year Five and beyond.The last two algorithms are centered on linear algebra and matrix decomposition. I present new unified coaddition scheme called “Bayesian Coaddition” that unifies three different coadds into a single Bayesian likelihood with a single hyper parameter prior. This work includes a coadd that reconstructs the true image without any telescope transmission effects, as well as a coadd with a diagonal covariance that is the statistically optimal way to weight exposures with different seeing when coadding. Finally I present an algorithm for non-negative matrix factorization that generates non-negative decomposed matrices of templates and coefficients that does not require the input data to be non-negative.

Inverse problems are prevalent in many fields of science and engineering, such as signal processing and medical imaging. In such problems, indirect data are used to recover information regarding some unknown parameters of interest. When these problems fail to be well-posed, the original problems must be modified to include additional constraints or optimization terms, giving rise to so-called regularizationtechniques. Classical methods for solving inverse problems are often deterministic and focus on finding point estimates for the unknowns. Some newer methods approach the solving of inverse problems by instead casting them in a statistical framework, allowing for novel point estimate approaches and for the recovery of uncertainty information. In this dissertation, we first use a deterministic approach in the context of a medical imaging application to reconstruct volumetric images of blood vessels while enforcing sparsity in the edge domain. We then propose and investigate methods for the statistical inference of complex-valued signals as well as techniques for volumetric reconstruction using complex-valued synthetic aperture radar data.