Areas Of Health Research Research Articles

A Review of the Relationship between Socioeconomic Status Change and Health.

This review aimed to identify and synthesize the existing literature on the effects of socioeconomic status (SES) changes on health. A review was conducted using Medline, Cochrane library, and CINAHL (Cumulative Index to Nursing and Allied Health Literature). All longitudinal or cross-sectional studies that examined links between changes to SES across different time periods and measured health outcomes were included. Screening was conducted using select inclusion and exclusion criteria in order of title, abstract, and full text. Two independent reviewers assessed the quality of the full text articles using the Downs and Black checklist. Our literature search led to 2719 peer reviewed articles, 2639 of which were title screened after duplicates were removed. A total of 117 abstracts and 12 full text articles were screened. Overall, findings from 11 articles form the basis of this review. Eight different types of measures of changes to SES were identified. These include education, occupation, economic security, income sufficiency, home ownership, car ownership, health insurance, and marital status. Assessed outcomes included measures related to physical health, cardiovascular disease, mental health, and oral health. A large proportion of studies found that an SES change impacts health. Evidence suggests that those with consistently high SES have the best health outcomes, followed by those who report their SES change from low to high (upward social mobility). Evidence on the relative health effects for those who report their SES change from high to low (downward social mobility) compared to those who report consistently low SES is inconsistent. Current evidence suggests that an SES change has an impact on an individual's health. More research on the effects of SES changes on health outcomes in adulthood is needed and can inform various areas of health research including health resiliency and development. Future studies should focus on individual SES indicators and their effects on health outcomes at multiple points throughout life.

Detection and Quantification of Ammonia as the Ammonium Cation in Human Saliva by 1H NMR: A Promising Probe for Health Status Monitoring, with Special Reference to Cancer.

Ammonia (NH3) has been shown to be a key biomarker for a wide variety of diseases, such as hepatic and chronic kidney diseases (CKD), and cancers. It also has relevance to the oral health research area, and, hence, its determination in appropriate biofluids and tissues is of much importance. However, since it contains exchangeable >N-H protons, its analysis via 1H NMR spectroscopy, which is a widely employed technique in untargeted metabolomic studies, is rendered complicated. In this study, we focused on the 1H NMR analysis of this biomarker in less invasively collected human saliva samples, and we successfully identified and quantified it as ammonium cation (NH4+) in post-collection acidulated forms of this biofluid using both the standard calibration curve and standard addition method (SAM) approaches. For this purpose, n = 27 whole mouth saliva (WMS) samples were provided by healthy human participants, and all donors were required to follow a fasting/oral environment abstention period of 8 h prior to collection. Following acidification (pH 2.00), diluted WMS supernatant samples treated with 10% (v/v) D2O underwent 1H NMR analysis (600 MHz). The acquired results demonstrated that NH4+ can be reliably determined in these supernatants via integration of the central line of its characteristic 1:1:1 intensity triplet resonance (complete spectral range δ = 6.97-7.21 ppm). Experiments performed also demonstrated that any urease-catalysed NH3 generation occurring post-sampling in WMS samples did not affect the results acquired during the usual timespan of laboratory processing required prior to analysis. Further experiments demonstrated that oral mouth-rinsing episodes conducted prior to sample collection, as reported in previous studies, gave rise to major decreases in salivary NH4+ levels thereafter, which renormalised to only 50-60% of their basal control concentrations at the 180-min post-rinsing time point. Therefore, the WMS sample collection method employed significantly affected the absolute levels of this analyte. The LLOD was 60 μmol/L with 128 scans. The mean ± SD salivary NH4+ concentration of WMS supernatants was 11.4 ± 4.5 mmol/L. The potential extension of these analytical strategies to the screening of other metabolites with exchangeable 1H nuclei is discussed, as is their relevance to the monitoring of human disorders involving the excessive generation and/or uptake of cellular/tissue material, or altered homeostasis, in NH3.

Increasing Effectiveness and Equity in Strengthening Health Research Capacity Using Data and Metrics: Recent Advances of the ESSENCE Mechanism.

The ESSENCE on Health Research initiative established a Working Group on Review of Investments in 2018 to improve coordination and collaboration among funders of health research capacity strengthening. The Working Group comprises more than a dozen ESSENCE members, including diverse representation by geography, country income level, the public sector, and philanthropy. The overall goal of the Working Group is increased research on national health priorities as well as improved pandemic preparedness, and, ultimately, fewer countries with very limited research capacity. We developed a basic set of metrics for national health research capacity, assessed different models of coordination and collaboration, took a deeper dive into eight countries to characterize their national research capacity, and began to identify opportunities to better coordinate our investments. In this article, we summarize the presentations, discussions, and outcomes of our second annual (virtual) meeting, which had more than 100 participants representing funders, researchers, and other stakeholders from higher- and lower-income countries worldwide. Presentations on the first day included the keynote speaker, Dr. Soumya Swaminathan, chief scientist of the World Health Organization (WHO), and updates on data and metrics for research capacity, which are critical to establish targets, road maps, and budgets. The second day focused on improving collaboration and coordination among funders and other stakeholders, the potential return on investment for health research, ongoing work to increase coordination at the country level, and examples of research capacity strengthening efforts in diverse health research areas from around the world. We concluded that an intentional data- and metric-driven approach to health research capacity strengthening, emphasizing coordination among funders, local leadership, and equitable partnerships and allocation of resources, will enhance the health systems of resource-poor countries as well as the world's pandemic preparedness.

Involving adolescents in the design, implementation, evaluation and dissemination of health research: an umbrella review protocol

IntroductionA lack of awareness on how to engage adolescents in research has been reported as one of the barriers to meaningful youth involvement in health research. Currently, available guidelines on...

Evaluation of the frequency and awareness of obesity among healthcare workers.

The aim of this study is to determine the frequency of obesity in healthcare workers and to evaluate the awareness of obesity by using Obesity Awareness Scale. This descriptive frequency study was conducted between January 1 and March 31, 2021, in 17 Family Health Centers in the Health Training and Research Area. 119 health personnel working in Family Health Centers were included in the study. The Body Mass Index (BMI) classification accepted by the World Health Organization for adults was used to determine obesity. Obesity Awareness Scale adapted to the Turkish language was used to evaluate obesity awareness. The frequency of obesity among healthcare workers was 11.8% and overweight was 37.8%. 51.9% of physicians were overweight, 14.8% were obese; 38.5% of midwives were overweight, 15.4% were obese; 24.4% of the nurses were overweight and 9.8% were obese. The mean BMI of the participants was 18.00±0.52 for underweight, 22.65±1.35 for normal, 27.32±1.43 for overweight, and 31.53±1.68 for obese. The obesity awareness total score average of the participants was 63.97±7.47 (high level). According to the obesity awareness scale sub-dimension mean scores, obesity awareness was 28.7±3.9 (high), nutrition awareness was 20.0±3.1 (high), and physical activity was 15.3±1.8 (good). The frequency of obesity was found to be low, and the awareness of obesity was found to be high among HCWs in Family Health Centers. In addition, obesity was mostly detected in physicians, midwives, and nurses. Urgent act policies are needed to encourage both patients and HCWs to the awareness and prevention of obesity and to have a healthy lifestyle.

Study of normal and pathogenic bacteria and yeasts in curd samples

Probiotics are very important for our daily life and as food. However, they must be safe to consume. There can be many bacterial contaminants present in curd bought from the market, which can cause infections. We studied curd samples and found many such pathogens as well as Acid fast bacilli. Hence, one should be cautious while consuming curd bought from market. This is an important but neglected area of public health research.

Study of Normal and Pathogenic Bacteria in Medicinal Probiotics

There are many medicinal probiotics available which are usually bacteria but sometimes also yeasts. These medicinal probiotics, sometimes contain some undesired products like pathogenic aerobic or anaerobic bacteria. These are hitherto unexplored areas of public health research. Hence here we have tried to study the presence of these types of pathogenic bacteria. Some pathogens were found in the medicinal probiotics.

Lost in the voidness of the Atlantic Ocean

Trindade is an oceanic island of volcanic origin in the South Atlantic. Although highly disturbed, the island hosts a rich biological diversity, serving as a habitat for many endemic species. Scientific research in Trindade has generated a vast amount of literature in the last 300 years. Nonetheless, an objective scientific synthesis summarizing the main research findings in the last century is still lacking, which prevents us to understand the knowledge gaps and to propose a way forward to better understand biodiversity and promote its conservation. Thus, this paper aims to present a synthesis of the research performed on Trindade Island, with emphasis on Biological Sciences studies. Therefore, an online search with specific strings on CrossRef, Google Scholar, and National Center for Biotechnology Information was performed, as well as a search on global extinction risk on the red list of the International Union for Conservation of Nature. Our search recovered 312 references, mainly from Biological, Health, and Agrarian Sciences research areas. More than 1000 species have occurrences reported on the island, most of them from oceanic environments. A total of 32 species occurring in Trindade are considered under threat of extinction. Animals and plants are the most studied organisms while the diversity of microorganisms is the main knowledge gap in the recognition of the island's biota. Data about the biological diversity of the island, conservation, and tion trends are shown and discussed. A list of all the reported species in the retrieved literature and their conservation status is also presented.

Principles for consumer involvement in health and medical research.

Principles for consumer involvement in health and medical research.

Development of an intervention program to reduce whole-body vibration exposure based on occupational and individual determinants among dumper operators

ABSTRACT Objectives. Studies related to a systematic approach for intervention design to reduce whole-body vibration (WBV) exposure are scarce. This study presents a systematic approach to identifying, selecting and prioritizing safety interventions to fulfill that research gap. Methods. A total of 130 vibration readings for dumper operators were taken from two surface iron ore mines to identify significant determinants of WBV exposure. Initially, age, weight, seat design, awkward posture, machine’s age, load tonnage, dumper speed and haul road condition were hypothesized as determinants. Data were collected through standardized questionnaires and field-based observation. A multivariate statistical approach was applied for the practical use of the intervention program. Results. As some of the hypothesized factors were correlated, exploratory factor analysis (EFA) followed by multiple linear regression (MLR) was used to investigate their association with WBV exposure. As per EFA results, hypothesized factors were clubbed under individual, ergonomics and occupational factors. Occupational and ergonomics factors were found to be significantly associated with WBV exposure through MLR and used to form safety interventions to reduce WBV exposure. Conclusions. Our methodological approach is original in the occupational health research area and can be helpful to tailor the safety interventions for the unit level with minimum effort.

Pilot study of a smartphone-based tinnitus therapy using structured counseling and sound therapy: A multiple-baseline design with ecological momentary assessment.

Tinnitus affects a considerable part of the population and develops into a severe disorder in some sufferers. App-based interventions are able to provide low-threshold, cost-effective, and location-independent care for tinnitus patients. Therefore, we developed a smartphone app combining structured counseling with sound therapy and conducted a pilot study to evaluate treatment compliance and symptom improvement (trial registration: DRKS00030007). Outcome variables were Ecological Momentary Assessment (EMA) measured tinnitus distress and loudness and Tinnitus Handicap Inventory (THI) at baseline and final visit. A multiple-baseline design with a baseline phase (only EMA) followed by an intervention phase (EMA and intervention) was applied. 21 patients with chronic tinnitus (≥ 6 months) were included. Overall compliance differed between modules (EMA usage: 79% of days, structured counseling: 72%, sound therapy: 32%). The THI score improved from baseline to final visit indicating a large effect (Cohens d = 1.1). Tinnitus distress and loudness did not improve significantly from baseline phase to the end of intervention phase. However, 5 of 14 (36%) improved clinically meaningful in tinnitus distress (ΔDistress ≥ 10) and 13 of 18 (72%) in THI score (ΔTHI ≥ 7). The positive relationship between tinnitus distress and loudness weakened over the course of the study. A trend but no level effect for tinnitus distress could be demonstrated by a mixed effect model. The improvement in THI was strongly associated with the improvement scores in EMA of tinnitus distress (r = -0.75; 0.86). These results indicate that app-based structured counseling combined with sound therapy is feasible, has an impact on tinnitus symptoms and reduces distress for several patients. In addition, our data suggest that EMA could be used as a measurement tool to detect changes in tinnitus symptoms in clinical trials as has already been shown in other areas of mental health research.

Frontiers of geriatric mental health research amidst COVID-19 pandemic: A bibliometric analysis

ABSTRACT Geriatric population got prominently affected by COVID-19 pandemic in global context. Compromised immunity, comorbidities, and psychosocial factors have contributed to the physical and mental health of the elderly. The aim of this study was to analyze published literature globally by medical fraternity in the field of geriatric mental health during and post-COVID-19 pandemic. Bibliometric information on literature regarding said topic using specific keywords was searched and collected from the Scopus database. VOSviewer (1.6.18) was applied to conduct bibliometric analysis (BA) and visualization. The study highlighted the most significant journals, authors, co-cited authors, institutions, keywords co-occurrence, and most contributed countries in the area of Geriatric Mental Health research during COVID-19 on the basis of BA of studies taken from the database of Scopus for the past 3 years (2020–first quarter of 2023). To give researchers, decision-makers, and stakeholders a comprehensive view of the field of geriatric mental health-related research at COVID-19, this study employed bibliometric and scientific mapping approaches. Publications on the topic displayed a great deal of support from developed nations, especially the United States, which also produced a lot of publications of high quality.

The Influence of Support System on the Readiness to Motherhood Transition in Padang Independent Midwive Practice

This study saw the influence of adult attachment style and support systems on the readiness for the transition to motherhood. It is hoped that there will be an optimization of the preparedness for the motherhood transition for women who give birth for the first time. The long-term goal of this study is to assist mothers in optimizing preparation for the transition period to motherhood and obtaining a healthy pregnancy, minimizing the incidence of complications and morbidity in mothers so that it can contribute to reducing the morbidity rate, maternal mortality rate, and infant mortality rate.The specific target of this study is the achievement of psychological well-being in puerperal mothers, which can be obtained from cooperation with their husbands and social support from their environment.This research activity plan aligns with UNAND's National Research Priorities and Development Master Plan. This research is included in one of PRN's research fields in the focus area of health and drug research. This research is also following the RIP of Andalas University, including the central theme of research, namely health, with the sub-theme of nutrition and health, the sub-topic of development.

Embedding research codesign knowledge and practice: Learnings from researchers in a new research institute in Australia

BackgroundResearch codesign is generally defined as end-users’ involvement in planning, implementation, and evaluation of projects. Recently, there has been a growing interest in codesign to maximise research acceptability, applicability, and impact and to address longstanding issues around power and depth of involvement. Frameworks have been developed to assist in understanding research codesign processes at a project level. However, little is known about how university based researchers construct or adopt a coherent approach to sustain research codesign in governance, methodological approaches, and practice. This study investigated the perspectives of researchers within a newly formed research institute about principles and practices of research codesign in the context of their previous and current projects. We also investigated their perceptions of institution-level enablers and barriers to codesign. University based researchers are our primary focus here and we intend to consult other stakeholders in future work.MethodsUsing an interview guide informed by exploratory work and a scoping review of the literature, we conducted 15 individual interviews with Caring Futures Institute (CFI) leaders and researchers at different career stages working across multiple areas of health, care, and social research. Qualitative thematic analysis was conducted.ResultsThe researchers we interviewed were involved in projects ranging from large nationally funded projects to small studies funded by the university or PhD projects. Research codesign activities were generally part of larger researcher-led projects but there were a few examples of community-led projects. There was agreement amongst participants on the principles and perceived benefits of research codesign such as partnership, co-learning, and power sharing. Less agreement was found regarding the definition of research codesign and best terminology to be used. Themes reflecting the success of research codesign included pre-existing community relationships, communication skills, knowledge, and training on codesign, balancing power relationships, use of external facilitators, and adequacy of funding, time, and resources.ConclusionsThe study reaffirmed the complexity of research codesign from researchers’ perspectives and identified areas of potential action that may be beneficial for university based research institutions in building codesign skills, capacity and culture for example training, peer learning and funding support. Implications for practice improvement centre on a dual strategy of building practical capacity in researchers and integrating institutional dimensions (such as governance and leadership) into codesign frameworks. This can help to ensure research codesign is integrated into organisational culture and through the work of individual researchers.

Can Machine Learning advance or hinder statistical modelling of dementia risk in the Population.

AbstractBackgroundMachine learning and Artificial intelligence is a rapidly growing area of health research in predicting individual and population disease risk. Predicting dementia in the population using neuropathology data is particularly challenged due to the lack of brain donation recourses. Machine learning is growing in popularity due to an increased focus on collecting health data and its powerful ability to compute complex statistics using smaller datasets while handling missing data.There is debate in the research community on the reliability of machine learning for predicting dementia. The thinking behind many machine learning techniques emphasizes use of very large amounts of data, whereas more classical statistical techniques emphasize a prediction of risk based on more specific and targeted data often resulting in smaller sample sizes.If these techniques complement or contradict each other’s ability to accurately predict risk of dementia in the population is yet unknown. Understanding this is paramount for the future of dementia research considering the ever‐growing integration between Neuropathology, data and statistical scienceMethodWe applied machine learning techniques for feature ranking and classification as an unbiased comparison of neuropathological features and assessment of their diagnostic performance using a cohort (n = 507) from the Cognitive Function and Ageing Studies (CFAS). This could then be compared to more traditional statistical modelling using logistic regression.ResultDecision Tree Classification gave clear and easy to interpret roots for dementia risk, visualising a hierarchy from pathologies that is less clear than logistic regression and odds ratios. It produces an individualised look at dementia risk based on specific combinations of pathology that is unclear in the statistical regression model however, does not deal with missing data well.The random forest model is strong in predicting cases of dementia however it misclassifies healthy cases as dementia cases 52% of the time.TDP 43 contributes the most to the model and Lewy bodies contributes the least.ConclusionMachine learning has the potential to analyse neuropathology of dementia in sophisticated ways, however almost half of dementia cases remained misclassified. This points towards a more complex model of dementia pathology that requires further neuropathological assessments and collection of high quality cohort data to analyse.

Infections in people with dementia and mortality: A population‐based cohort study

AbstractBackgroundInfections in older people are a major cause of mortality and morbidity and may be important modifiers of outcomes for people with dementia. There is limited evidence on the role of infections and associated hospital admissions on subsequent outcomes for people living with dementia. We explored mortality in individuals with dementia admitted to hospital for infections from a defined population in comparison to those not admitted and admitted for other reasons.MethodA retrospective cohort analysis was created using secondary care data from one of Europe’s largest mental health and dementia care providers in South London (UK). People with recorded dementia between January 2008 and March 2017 were linked to national hospitalisation and mortality data and classified as either admitted for infections, admitted for other causes or no admissions around first recorded dementia diagnosis and followed to death or a census date on 31st March 2019. Multivariate Cox proportional hazards regression with date of first dementia diagnosis as index date were applied.ResultIn total 14,375 people diagnosed with dementia were included, of whom 3,480 (24%) were admitted for infections, 3604 (25%) admitted for other causes and 7,291 (51%) not admitted to hospital. Individuals with dementia admitted for infections had lower MMSE scores, higher rates of co‐morbidity and ranked significantly higher on deprivation indices compared to those with no admissions. Adjusted multivariate Cox regression models indicated that people with dementia admitted to hospital for infections had significantly higher mortality rates compared to no admissions (Hazard ratio (HR): 2.3; 95% confidence interval (CI): 2.1 ‐ 2.5) and to admissions for other causes (HR: 1.5; 95% CI: 1.4 ‐ 1.6).ConclusionIn people with dementia, admissions for infections are critical events associated with substantial increased mortality risk. Addressing care patterns both before and after admission with a focus on infection could improve outcomes and is a key health research area, with optimisation of care a direct priority.

Ethical preparedness in health research and care: the role of behavioural approaches

BackgroundPublic health scholars have long called for preparedness to help better negotiate ethical issues that emerge during public health emergencies. In this paper we argue that the concept of ethical preparedness has much to offer other areas of health beyond pandemic emergencies, particularly in areas where rapid technological developments have the potential to transform aspects of health research and care, as well as the relationship between them. We do this by viewing the ethical decision-making process as a behaviour, and conceptualising ethical preparedness as providing a health research/care setting that can facilitate the promotion of this behaviour. We draw on an implementation science and behaviour change model, COM-B, to demonstrate that to be ethically prepared requires having the capability (ability), opportunity, and motivation (willingness) to work in an ethically prepared way.MethodsWe use two case examples from our empirical research—one pandemic and one non-pandemic related—to illustrate how our conceptualisation of ethical preparedness can be applied in practice. The first case study was of the UK NHSX COVID-19 contact tracing application case study involved eight in-depth interviews with people involved with the development/governance of this application. The second case involved a complex case regarding familial communication discussed at the UK Genethics Forum. We used deductive qualitative analysis based on the COM-B model categories to analyse the transcripbed data from each case study.ResultsOur analysis highlighted that being ethically prepared needs to go beyond merely equipping health professionals with skills and knowledge, or providing research governance actors with ethical principles and/or frameworks. To allow or support these different actors to utilise their skills and knowledge (or principles and frameworks), a focus on the physical and social opportunity is important, as is a better understanding the role of motivation.ConclusionsTo understand ethical preparedness, we need to view the process of ethical decision-making as a behaviour. We have provided insight into the specific factors that are needed to promote this behaviour—using examples from both in the pandemic context as well as in areas of health research and medicine where there have been rapid technological developments. This offers a useful starting point for further conceptual work around the notion of being ethically prepared.

Paid sick leave policy impacts on health and care utilization in the United States: why policy design matters.

The link between policy design choices and health is an important, yet understudied area of public health research. I investigate the impact of the generosity, inclusion, and autonomy of state paid sick leave laws on influenza-like-illness (ILI) rates and its components using data from the Centers for Disease Control and state-level paid sick leave statutes. I found that paid sick leave policies that include small firms and that allow for a larger number of medical uses have lower ILI rates, relative to states with less comprehensive policies. States with policies that had more generous accrual rates and that included a wide variety of worker types (temporary, part-time, students) increased the total number of reported medical cases, relative to states with less comprehensive policies. Policymakers contemplating paid sick leave policies should consider these design choices in their goals to incentivize health care utilization and to reduce contagion.Supplementary InformationThe online version contains supplementary material available at 10.1057/s41271-022-00371-9.

Wearables for Measuring Health Effects of Climate Change-Induced Weather Extremes: Scoping Review.

BackgroundAlthough climate change is one of the biggest global health threats, individual-level and short-term data on direct exposure and health impacts are still scarce. Wearable electronic devices (wearables) present a potential solution to this research gap. Wearables have become widely accepted in various areas of health research for ecological momentary assessment, and some studies have used wearables in the field of climate change and health. However, these studies vary in study design, demographics, and outcome variables, and existing research has not been mapped.ObjectiveIn this review, we aimed to map existing research on wearables used to detect direct health impacts and individual exposure during climate change–induced weather extremes, such as heat waves or wildfires.MethodsWe conducted a scoping review according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework and systematically searched 6 databases (PubMed [MEDLINE], IEEE Xplore, CINAHL [EBSCOhost], WoS, Scopus, Ovid [MEDLINE], and Google Scholar). The search yielded 1871 results. s and full texts were screened by 2 reviewers (MK and IM) independently using the inclusion and exclusion criteria. The inclusion criteria comprised studies published since 2010 that used off-the-shelf wearables that were neither invasive nor obtrusive to the user in the setting of climate change–related weather extremes. Data were charted using a structured form, and the study outcomes were narratively synthesized.ResultsThe review included 55,284 study participants using wearables in 53 studies. Most studies were conducted in upper–middle-income and high-income countries (50/53, 94%) in urban environments (25/53, 47%) or in a climatic chamber (19/53, 36%) and assessed the health effects of heat exposure (52/53, 98%). The majority reported adverse health effects of heat exposure on sleep, physical activity, and heart rate. The remaining studies assessed occupational heat stress or compared individual- and area-level heat exposure. In total, 26% (14/53) of studies determined that all examined wearables were valid and reliable for measuring health parameters during heat exposure when compared with standard methods.ConclusionsWearables have been used successfully in large-scale research to measure the health implications of climate change–related weather extremes. More research is needed in low-income countries and vulnerable populations with pre-existing conditions. In addition, further research could focus on the health impacts of other climate change–related conditions and the effectiveness of adaptation measures at the individual level to such weather extremes.

Paired serial limiting dilution assays.

Serial limiting dilution (SLD) assays are a widely used tool in many areas of public health research to measure the concentration of target entities. This concentration can be estimated via maximum likelihood. Asymptotic as well as exact inference methods have been proposed for hypothesis testing and confidence interval construction in this one-sample problem. However, in many scientific applications, it may be of interest to compare the concentration of target entities between a pair of samples and construct valid confidence intervals for the difference in concentrations. In this paper, an exact, computationally efficient inferential procedure is proposed for hypothesis testing and confidence interval construction in the two-sample SLD assay problem. The proposed exact method is compared to an approach based on asymptotic approximations in simulation studies. The methods are illustrated using data from the University of North Carolina HIV Cure Center.