Amplification-free detection of SARS-CoV-2 with CRISPR-Cas13a and mobile phone microscopy.

The December 2019 outbreak of a novel respiratory virus, SARS-CoV-2, has become an ongoing global pandemic due in part to the challenge of identifying symptomatic, asymptomatic, and pre-symptomatic carriers of the virus. CRISPR diagnostics can augment gold-standard PCR-based testing if they can be made rapid, portable, and accurate. Here, we report the development of an amplification-free CRISPR-Cas13a assay for direct detection of SARS-CoV-2 from nasal swab RNA that can be read with a mobile phone microscope. The assay achieved ∼100 copies/µL sensitivity in under 30 min of measurement time and accurately detected pre-extracted RNA from a set of positive clinical samples in under 5 min. We combined crRNAs targeting SARS-CoV-2 RNA to improve sensitivity and specificity and directly quantified viral load using enzyme kinetics. Integrated with a reader device based on a mobile phone, this assay has the potential to enable rapid, low-cost, point-of-care screening for SARS-CoV-2.

Monitoring viral load for the last mile: what will it cost?

INTRODUCTION: Routine viral load testing is the WHO-recommended method for monitoring HIV-infected patients on ART, and many countries are rapidly scaling up testing capacity at centralized laboratories. Providing testing access to the most remote populations and facilities (the "last mile") is especially challenging. Using a geospatial optimization model, we estimated the incremental costs of accessing the most remote 20% of patients in Zambia by expanding the transportation network required to bring blood samples from ART clinics to centralized laboratories and return results to clinics. METHODS: The model first optimized a sample transportation network (STN) that can transport 80% of anticipated sample volumes to centralized viral load testing laboratories on a daily or weekly basis, in line with Zambia's 2020 targets. Data incorporated into the model included the location and infrastructure of all health facilities providing ART, location of laboratories, measured distances and drive times between the two, expected future viral load demand by health facility, and local cost estimates. We then continued to expand the modelled STN in 5% increments until 100% of all samples could be collected. RESULTS AND DISCUSSION: The cost per viral load test when reaching 80% patient volumes using centralized viral load testing was a median of $18.99. With an expanded STN, the incremental cost per test rose to $20.29 for 80% to 85% and $20.52 for 85% to 90%. Above 90% coverage, the incremental cost per test increased substantially to $31.57 for 90% to 95% and $51.95 for 95% to 100%. The high numbers of kilometres driven per sample transported and large number of vehicles needed increase costs dramatically for reaching the clinics that serve the last 5% of patients. CONCLUSIONS: Providing sample transport services to the most remote clinics in low- and middle-income countries is likely to be cost-prohibitive. Other strategies are needed to reduce the cost and increase the feasibility of making viral load monitoring available to the last 10% of patients. The cost of alternative methods, such as optimal point-of-care viral load equipment placement and usage, dried blood/plasma spot specimen utilization, or use of drones in geographically remote facilities, should be evaluated.

Optimizing viral load testing access for the last mile: Geospatial cost model for point of care instrument placement.

INTRODUCTION: Viral load (VL) monitoring programs have been scaled up rapidly, but are now facing the challenge of providing access to the most remote facilities (the "last mile"). For the hardest-to-reach facilities in Zambia, we compared the cost of placing point of care (POC) viral load instruments at or near facilities to the cost of an expanded sample transportation network (STN) to deliver samples to centralized laboratories. METHODS: We extended a previously described geospatial model for Zambia that first optimized a STN for centralized laboratories for 90% of estimated viral load volumes. Amongst the remaining 10% of volumes, facilities were identified as candidates for POC placement, and then instrument placement was optimized such that access and instrument utilization is maximized. We evaluated the full cost per test under three scenarios: 1) POC placement at all facilities identified for POC; 2)an optimized combination of both on-site POC placement and placement at facilities acting as POC hubs; and 3) integration into the centralized STN to allow use of centralized laboratories. RESULTS: For the hardest-to-reach facilities, optimal POC placement covered a quarter of HIV-treating facilities. Scenario 2 resulted in a cost per test of $39.58, 6% less than the cost per test of scenario 1, $41.81. This is due to increased POC instrument utilization in scenario 2 where facilities can act as POC hubs. Scenario 3 was the most costly at $53.40 per test, due to high transport costs under the centralized model ($36 per test compared to $12 per test in scenario 2). CONCLUSIONS: POC VL testing may reduce the costs of expanding access to the hardest-to-reach populations, despite the cost of equipment and low patient volumes. An optimal combination of both on-site placement and the use of POC hubs can reduce the cost per test by 6-35% by reducing transport costs and increasing instrument utilization.

Point-of-care HIV viral load in pregnant women without prenatal care: a cost-effectiveness analysis.

BACKGROUND: Routine cesarean delivery has been shown to decrease mother-to-child-transmission of HIV in women with high viral load greater than 1000 copies/mL; however, women presenting late in pregnancy may not have viral load results before delivery. OBJECTIVE: Our study investigated the costs and outcomes of using a point-of-care HIV RNA viral load test to guide delivery compared with routine cesarean delivery for all in the setting of unknown viral load. STUDY DESIGN: A decision-analytic model was constructed using TreeAge software to compare HIV RNA viral load testing vs routine cesarean delivery for all in a theoretical cohort of 1275 HIV-positive women without prenatal care who presented at term for delivery, the estimated population of HIV-positive women without prenatal care in the United States annually. TreeAge Pro software is used to build decision trees modeling clinical problems and perform cost-effectiveness, sensitivity, and simulation analysis to identify the optimal outcome. The average cost per test was $15.22. To examine the downstream impact of a cesarean delivery and because most childbearing women in the United States will deliver 2 children, we incorporated a second pregnancy and delivery in the model. Primary outcomes were mother-to-child transmission, delivery mode, cesarean delivery-related complications, cost, and quality-adjusted life years. Model inputs were derived from the literature and varied in sensitivity analyses. The cost-effectiveness threshold was $100,000/quality-adjusted life year. RESULTS: Measuring viral load resulted in more HIV-infected neonates than routine cesarean delivery for all due to viral exposure during more frequent vaginal births in this strategy. There were no observed maternal deaths or differences in cesarean delivery-related complications. Quantifying viral load increased cost by $3,883,371 and decreased quality-adjusted life years by 63 compared with routine cesarean delivery for all. With the threshold set at $100,000/quality-adjusted life year, the viral load test is cost-effective only when the vertical transmission rate in women with high viral load was below 0.68% (baseline: 16.8%) and when the odds ratio of vertical transmission with routine cesarean delivery for all compared with vaginal delivery was above 0.885 (baseline: 0.3). CONCLUSIONS: For HIV-infected pregnant women without prenatal care, quantifying viral load to guide mode of delivery using a point-of-care test resulted in increased costs and decreased effectiveness when compared with routine cesarean delivery for all, even after including downstream complications of cesarean delivery.

Impact of a borderless sample transport network for scaling up viral load monitoring: results of a geospatial optimization model for Zambia.

INTRODUCTION: The World Health Organization recommends viral load (VL) monitoring at six and twelve months and then annually after initiating antiretroviral treatment for HIV. In many African countries, expansion of VL testing has been slow due to a lack of efficient blood sample transportation networks (STN). To assist Zambia in scaling up testing capacity, we modelled an optimal STN to minimize the cost of a national VL STN. METHODS: The model optimizes a STN in Zambia for the anticipated 1.5 million VL tests that will be needed in 2020, taking into account geography, district political boundaries, and road, laboratory and facility infrastructure. We evaluated all-inclusive STN costs of two alternative scenarios: (1) optimized status quo: each district provides its own weekly or daily sample transport; and (2) optimized borderless STN: ignores district boundaries, provides weekly or daily sample transport, and reaches all Scenario 1 facilities. RESULTS: Under both scenarios, VL testing coverage would increase to from 10% in 2016 to 91% in 2020. The mean transport cost per VL in Scenario 2 was $2.11 per test (SD $0.28), 52% less than the mean cost/test in Scenario 1, $4.37 (SD $0.69), comprising 10% and 19% of the cost of a VL respectively. CONCLUSIONS: An efficient STN that optimizes sample transport on the basis of geography and test volume, rather than political boundaries, can cut the cost of sample transport by more than half, providing a cost savings opportunity for countries that face significant resource constraints.

Does Economic Strengthening Improve Viral Suppression Among Adolescents Living with HIV? Results From a Cluster Randomized Trial in Uganda.

To assess the effect of a savings-led economic empowerment intervention on viral suppression among adolescents living with HIV. Using data from Suubi + Adherence, a longitudinal, cluster randomized trial in southern Uganda (2012-2017), we examine the effect of the intervention on HIV RNA viral load, dichotomized between undetectable (< 40 copies/ml) and detectable (≥ 40 copies/ml). Cluster-adjusted comparisons of means and proportions were used to descriptively analyze changes in viral load between study arms while multi-level modelling was used to estimate treatment efficacy after adjusting for fixed and random effects. At 24-months post intervention initiation, the proportion of virally suppressed participants in the intervention cohort increased tenfold (ΔT2-T0 = + 10.0, p = 0.001) relative to the control group (ΔT2-T0 = + 1.1, p = 0.733). In adjusted mixed models, simple main effects tests identified significantly lower odds of intervention adolescents having a detectable viral load at both 12- and 24-months. Interventions addressing economic insecurity have the potential to bolster health outcomes, such as HIV viral suppression, by improving ART adherence among vulnerable adolescents living in low-resource environments. Further research and policy dialogue on the intersections of financial security and HIV treatment are warranted.

Using a retention in care protocol to promote positive health and systems related outcomes.

People living with HIV can experience the full benefits of retention when they are continuously engaged in care. Continuous engagement in care promotes improved adherence to ART and positive health outcomes. An infectious disease clinic has implemented a protocol to primarily improve patient retention. The retrospective, facility-based, costing study took place in an infectious disease clinic in Washington DC. Retention was defined in two ways and over a 12-month period. Micro-costing direct measurement methods were used to collect unit costs in time series. Return on investment accounted for the cost of treatment based on CD4 strata. ROI was expressed in 2016USD. The difference in CD4 and viral load levels between the two periods of analysis were determined for active patients, infected with HIV. The year before the intervention was compared to the year of the intervention. Total treatment expenditure decreased from $2,435,653.00 to $2,283,296.23, resulting in a $152,356.77 gain from investment for the healthcare system over a 12-month investment period. The viral load suppression rate increased from 81 to 95 (p = 0.04) over the investment period. The number of patients in need of HIV related opportunistic infection prophylaxis decreased from 21 to 13 (p = 0.06). Improved immunologic, virologic and healthcare expenditure outcomes can be linked to the quality of retention practice.

Optimización de recursos para determinar la carga viral de HIV-1 en un país con pocos recursos / Optimizing resources to reduce costs to determine HIV viral load in limited resources settings

Resumen Introducción. Las metas globales para controlar la epidemia de HIV contemplan que la carga viral sea indetectable en 90 % de las personas en tratamiento. El costo de la medición de la carga viral en lotes de muestras puede reducirse y, así, aumentar la cobertura cuando los recursos son limitados; sin embargo, su eficacia disminuye al aumentar la prevalencia del fracaso del tratamiento antirretroviral. Objetivo. Evaluar estrategias para disminuir la proporción de pacientes con fracaso del tratamiento antirretroviral en los lotes de muestras y, de esta manera, aumentar el ahorro en las pruebas de carga viral. Materiales y métodos. Las estrategias evaluadas fueron: a) la organización de los lotes de muestras según el esquema de tratamiento antirretroviral, y b) la exclusión de aquellos pacientes con antecedente reciente de fracaso del tratamiento antirretroviral, aquellos con menos de 12 meses de tratamiento antirretroviral y aquellos sin tratamiento antirretroviral previo. Los resultados de los lotes se compararon con los resultados individuales. Resultados. El valor diagnóstico negativo fue similar para los pacientes con esquema de primera línea (100,0 %; IC95% 99,5-100,0) o de segunda línea de tratamiento (99,4 %; IC95% 96,9-99,9). La incidencia del fracaso del tratamiento antirretroviral fue menor en los pacientes con tratamiento de primera línea (p<0,01), lo cual permitió un mayor ahorro en las pruebas de laboratorio en este grupo (74,0 %; IC95% 71,0-76,7) que en los pacientes con tratamiento de segunda línea (50,9 %; IC95% 44,4-57,3) (p<0,01). Conclusión. La selección de las muestras que se incluyeron en los lotes para determinar la carga viral del HIV según el tipo de esquema de tratamiento, permitió maximizar el porcentaje de ahorro en pruebas de laboratorio.

Abstract Introduction: HIV viral load testing is a key factor to evaluate the accomplishment of the UNAIDS target of 90% of viral suppression among people receiving antiretroviral therapy. Pooled samples are a potentially accurate and economic approach in resource-constrained settings, but efficiency can be negatively affected by high prevalence rates of virological failure. Objective: Strategies were assessed to increase the relative efficiency of pooled HIV viral load testing in resource-constrained settings. Materials and methods: We evaluated two strategies: a) plasma samples were not included in pools if patients had <12 months on antiretroviral therapy, patients had previous viral load >1,000 copies/ml, or were antiretroviral therapy naïve patients, and b) plasma pools were organized separately for first and second-line antiretroviral therapy regimens. Individual viral load tests were used to compare pooled results. Results: Negative predictive values were similar for patients on first (100.0%; 95% CI 99.5 to 100.0) and second-line antiretroviral therapy regimens (99.4%; 95% CI 96.9 to 99.9). However, the incidence of virological failure among individuals on first-line antiretroviral therapy was lower than second-line antiretroviral therapypatients (p <0.01), resulting in greater savings in laboratory tests in patients on first-line antiretroviral therapy (74.0%; 95% CI 71.0 to 76.7) compared with the group of patients on second-line antiretroviral therapy (50.9%; 95% CI 44.4 to 57.3) (p<0.01). Conclusion: Selecting the samples to be included in the pools and selecting the pools according to ART regimens are criteria that could lead to decreased spending on laboratory tests for HIV viral load determination in resource-constrained settings.

A cheap and open HIV viral load technique applicable in routine analysis in a resource limited setting with a wide HIV genetic diversity.

BACKGROUND: HIV infection in Cameroon is characterized by a great viral diversity with all HIV-1 groups (M, N, O, and P) and HIV-2 in circulation. HIV group determination is very important if tailored viral load analysis and treatments are to be applied. In our laboratory, HIV viral load is carried out using two platforms; Biocentric and Abbott depending on the HIV group identified. Biocentric which quantifies HIV-1 group M is a cheap and open system useful in resource limited settings. The objective of this study was to compare the viral load analyses of serologically group-indeterminate HIV samples using the two platforms with the view of reducing cost. METHODS: Consecutive samples received between March and May 2014, and between August and September 2014 in our laboratory for HIV viral load analysis were included. All these samples were analyzed for their HIV groups using an in-house ELISA serotyping test. All HIV-1 group M samples were quantified using the Biocentric test while all other known atypical samples (HIV-1 groups N, O and P) were analyzed using the Abbott technique. HIV group-indeterminate samples (by serotyping) were quantified with both techniques. RESULTS: Among the 6355 plasma samples received, HIV-1 group M was identified in 6026 (94.82%) cases; HIV-1 group O, in 20 (0.31%); HIV-1 group M + O, in 3 (0.05%) and HIV-2, in 3 (0.05%) case. HIV-group indeterminate samples represented about 4.76% (303/6355) and only 231 of them were available for analysis by Abbott Real-Time HIV-1 and Generic HIV Viral Load techniques. Results showed that 188 (81.39%) samples had undetectable viral load in both techniques. All the detectable samples showed high viral load, with a mean of 4.5 log copies/ml (range 2.1-6.5) for Abbott Real-Time and 4.5 log copies/ml (range 2-6.4) for Generic HIV Viral Load. The mean viral load difference between the two techniques was 0.03 log10 copies/ml and a good correlation was obtained (r 2 = 0.89; P < 0.001). CONCLUSION: Our results suggest that cheaper and open techniques such as Biocentric could be useful alternatives for HIV viral load follow-up quantification in resource limited settings like Cameroon; even with its high viral diversity.

Cost-effectiveness of routine viral load monitoring in low- and middle-income countries: a systematic review.

INTRODUCTION: Routine viral load monitoring for HIV-1 management of persons on antiretroviral therapy (ART) has been recommended by the World Health Organization (WHO) to identify treatment failure. However, viral load testing represents a substantial cost in resource constrained health care systems. The central challenge is whether and how viral load monitoring may be delivered such that it maximizes health gains across the population for the costs incurred. We hypothesized that key features of program design and delivery costs drive the cost-effectiveness of viral load monitoring within programs. METHODS: We conducted a systematic review of studies on the cost-effectiveness of viral load monitoring in low- and middle-income countries (LMICs). We followed the Cochrane Collaboration guidelines and the PRISMA reporting guidelines. RESULTS AND DISCUSSION: We identified 18 studies that evaluated the cost-effectiveness of viral load monitoring in HIV treatment programs. Overall, we identified three key factors that make it more likely for viral load monitoring to be cost-effective: 1) Use of effective, lower cost approaches to viral load monitoring (e.g. use of dried blood spots); 2) Ensuring the pathway to health improvement is established and that viral load results are acted upon; and 3) Viral load results are used to simplify HIV care in patients with viral suppression (i.e. differentiated care, with fewer clinic visits and longer prescriptions). Within the context of differentiated care, viral load monitoring has the potential to double the health gains and be cost saving compared to the current standard (CD4 monitoring). CONCLUSIONS: The cost-effectiveness of viral load monitoring critically depends on how it is delivered and the program context. Viral load monitoring as part of differentiated HIV care is likely to be cost-effective. Viral load monitoring in differentiated care programs provides evidence that reduced clinical engagement, where appropriate, is not impacting health outcomes. Introducing viral load monitoring without differentiated care is unlikely to be cost-effective in most settings and results in lost opportunity for health gains through alternative uses of limited resources. As countries scale up differentiated care programs, data on viral suppression outcomes and costs should be collected to evaluate the on-going cost-effectiveness of viral load monitoring as utilized in practice.

HIV viral load monitoring among key populations in low- and middle-income countries: challenges and opportunities.

INTRODUCTION: Key populations bear a disproportionate HIV burden and have substantial unmet treatment needs. Routine viral load monitoring represents the gold standard for assessing treatment response at the individual and programme levels; at the population-level, community viral load is a metric of HIV programme effectiveness and can identify "hotspots" of HIV transmission. Nevertheless, there are specific implementation and ethical challenges to effectively operationalize and meaningfully interpret viral load data at the community level among these often marginalized populations. DISCUSSION: Viral load monitoring enhances HIV treatment, and programme evaluation, and offers a better understanding of HIV surveillance and epidemic trends. Programmatically, viral load monitoring can provide data related to HIV service delivery coverage and quality, as well as inequities in treatment access and uptake. From a population perspective, community viral load data provides information on HIV transmission risk. Furthermore, viral load data can be used as an advocacy tool to demonstrate differences in service delivery and to promote allocation of resources to disproportionately affected key populations and communities with suboptimal health outcomes. However, in order to perform viral load monitoring for individual and programme benefit, health surveillance and advocacy purposes, careful consideration must be given to how such key population programmes are designed and implemented. For example, HIV risk factors, such as particular sex practices, sex work and drug use, are stigmatized or even criminalized in many contexts. Consequently, efforts must be taken so that routine viral load monitoring among marginalized populations does not cause inadvertent harm. Furthermore, given the challenges of reaching representative samples of key populations, significant attention to meaningful recruitment, decentralization of care and interpretation of results is needed. Finally, improving the interoperability of health systems through judicious use of biometrics or identifiers when confidentiality can be maintained is important to generate more valuable data to inform monitoring programmes. CONCLUSIONS: Opportunities for expanded viral load monitoring could and should benefit all those affected by HIV, including key populations. The promise of the increasing routinization of viral load monitoring as a tool to advance HIV treatment equity is great and should be prioritized and appropriately implemented within key population programmatic and research agendas.

The case for viral load testing in adolescents in resource-limited settings.

INTRODUCTION: The success of HIV treatment programmes globally has resulted in children with perinatally acquired HIV reaching adolescence in large numbers. The number of adolescents living with HIV is growing further due to persisting high HIV incidence rates among adolescents in low- and middle-income settings, particularly in sub-Saharan Africa. Although expanding access to HIV viral load monitoring is necessary to achieve the 90-90-90 targets across the HIV care continuum, implementation is incomplete. We discuss the rationale for prioritizing viral load monitoring among adolescents and the associated challenges. DISCUSSION: Adolescents with HIV are a complex group to treat successfully due to extensive exposure to antiretroviral therapy for those with perinatally acquired HIV and the challenges in sustained medication adherence in this age group. Given the high risk of treatment failure among adolescents and the limited drug regimens available in limited resource settings, HIV viral load monitoring in adolescents could prevent unnecessary and costly switches to second-line therapy in virologically suppressed adolescents. Because adolescents living with HIV may be heavily treatment experienced, have suboptimal treatment adherence, or may be on second or even third-line therapy, viral load testing would allow clinicians to make informed decisions about increased counselling and support for adolescents together with the need to maintain or switch therapeutic regimens. CONCLUSIONS: Given scarce resources, prioritization of viral load testing among groups with a high risk of virological failure may be required. Adolescents have disproportionately high rates of virological failure, and targeting this age group for viral load monitoring may provide valuable lessons to inform broader scale-up.

The value of point-of-care CD4+ and laboratory viral load in tailoring antiretroviral therapy monitoring strategies to resource limitations.

OBJECTIVE: To examine the clinical and economic value of point-of-care CD4 (POC-CD4) or viral load monitoring compared with current practices in Mozambique, a country representative of the diverse resource limitations encountered by HIV treatment programs in sub-Saharan Africa. DESIGN/METHODS: We use the Cost-Effectiveness of Preventing AIDS Complications-International model to examine the clinical impact, cost (2014 US$), and incremental cost-effectiveness ratio [$/year of life saved (YLS)] of ART monitoring strategies in Mozambique. We compare: monitoring for clinical disease progression [clinical ART monitoring strategy (CLIN)] vs. annual POC-CD4 in rural settings without laboratory services and biannual laboratory CD4 (LAB-CD4), biannual POC-CD4, and annual viral load in urban settings with laboratory services. We examine the impact of a range of values in sensitivity analyses, using Mozambique's 2014 per capita gross domestic product ($620) as a benchmark cost-effectiveness threshold. RESULTS: In rural settings, annual POC-CD4 compared to CLIN improves life expectancy by 2.8 years, reduces time on failed ART by 0.6 years, and yields an incremental cost-effectiveness ratio of $480/YLS. In urban settings, biannual POC-CD4 is more expensive and less effective than viral load. Compared to biannual LAB-CD4, viral load improves life expectancy by 0.6 years, reduces time on failed ART by 1.0 year, and is cost-effective ($440/YLS). CONCLUSION: In rural settings, annual POC-CD4 improves clinical outcomes and is cost-effective compared to CLIN. In urban settings, viral load has the greatest clinical benefit and is cost-effective compared to biannual POC-CD4 or LAB-CD4. Tailoring ART monitoring strategies to specific settings with different available resources can improve clinical outcomes while remaining economically efficient.

Differentiated Human Immunodeficiency Virus RNA Monitoring in Resource-Limited Settings: An Economic Analysis.

BACKGROUND.: Viral load (VL) monitoring for patients receiving antiretroviral therapy (ART) is recommended worldwide. However, the costs of frequent monitoring are a barrier to implementation in resource-limited settings. The extent to which personalized monitoring frequencies may be cost-effective is unknown. METHODS.: We created a simulation model parameterized using person-level longitudinal data to assess the benefits of flexible monitoring frequencies. Our data-driven model tracked human immunodeficiency virus (HIV)-infected individuals for 10 years following ART initiation. We optimized the interval between viral load tests as a function of patients' age, gender, education, duration since ART initiation, adherence behavior, and the cost-effectiveness threshold. We compared the cost-effectiveness of the personalized monitoring strategies to fixed monitoring intervals every 1, 3, 6, 12, and 24 months. RESULTS.: Shorter fixed VL monitoring intervals yielded increasing benefits (6.034 to 6.221 discounted quality-adjusted life-years [QALYs] per patient with monitoring every 24 to 1 month over 10 years, respectively, standard error = 0.005 QALY), at increasing average costs: US$3445 (annual monitoring) to US$5393 (monthly monitoring) per patient, respectively (standard error = US$3.7). The adaptive policy optimized for low-income contexts achieved 6.142 average QALYs at a cost of US$3524, similar to the fixed 12-month policy (6.135 QALYs, US$3518). The adaptive policy optimized for middle-income resource settings yields 0.008 fewer QALYs per person, but saves US$204 compared to monitoring every 3 months. CONCLUSIONS.: The benefits from implementing adaptive vs fixed VL monitoring policies increase with the availability of resources. In low- and middle-income countries, adaptive policies achieve similar outcomes to simpler, fixed-interval policies.

Co-financing for viral load monitoring during the course of antiretroviral therapy among patients with HIV/AIDS in Vietnam: A contingent valuation survey.

BACKGROUND: Viral load testing is considered the gold standard for monitoring HIV treatment; however, given its high cost, some patients cannot afford viral load testing if this testing is not subsidized. Since foreign aid for HIV/AIDS in Vietnam is rapidly decreasing, we sought to assess willingness to pay (WTP) for viral load and CD4 cell count tests among HIV-positive patients, and identified factors that might inform future co-payment schemes. METHODS: A multi-site cross-sectional survey was conducted with 1133 HIV-positive patients on antiretroviral therapy (ART) in Hanoi and Nam Dinh. Patients' health insurance coverage, quality of life, and history of illicit drug use were assessed. A contingent valuation approach was employed to measure patients' WTP for CD4 cell count and viral load testing. RESULTS: HIV-positive patients receiving ART at provincial sites reported more difficulty obtaining health insurance (HI) and had the overall the poorest quality of life. Most patients (90.9%) were willing to pay for CD4 cell count testing; here, the mean WTP was valued at US$8.2 (95%CI = 7.6-8.8 US$) per test. Most patients (87.3%) were also willing to pay for viral load testing; here, mean WTP was valued at US$18.6 (95%CI = 16.3-20.9 US$) per test. High income, high education level, and hospitalization were positively associated with WTP, while co-morbidity with psychiatric symptoms and trouble paying for health insurance were both negatively related to WTP. CONCLUSIONS: These findings raise concerns that HIV-positive patients in Vietnam might have low WTP for CD4 cell count and viral load testing. This means that without foreign financial subsidies, many of these patients would likely go without these important tests. Treating psychiatric co-morbidities, promoting healthcare services utilization, and removing barriers to accessing health insurance may increase WTP for monitoring of HIV/AIDS treatment among HIV+-positive Vietnamese patients.

[Optimizing resources to reduce costs to determine HIV viral load in limited resources settings].

INTRODUCTION: HIV viral load testing is a key factor to evaluate the accomplishment of the UNAIDS target of 90% of viral suppression among people receiving antiretroviral therapy. Pooled samples are a potentially accurate and economic approach in resource-constrained settings, but efficiency can be negatively affected by high prevalence rates of virological failure. OBJECTIVE: Strategies were assessed to increase the relative efficiency of pooled HIV viral load testing in resource-constrained settings. MATERIALS AND METHODS: We evaluated two strategies: a) plasma samples were not included in pools if patients had <12 months on antiretroviral therapy, patients had previous viral load >1,000 copies/ml, or were antiretroviral therapy naïve patients, and b) plasma pools were organized separately for first and second-line antiretroviral therapy regimens. Individual viral load tests were used to compare pooled results. RESULTS: Negative predictive values were similar for patients on first (100.0%; 95% CI 99.5 to 100.0) and second-line antiretroviral therapy regimens (99.4%; 95% CI 96.9 to 99.9). However, the incidence of virological failure among individuals on first-line antiretroviral therapy was lower than second-line antiretroviral therapy patients (p <0.01), resulting in greater savings in laboratory tests in patients on first-line antiretroviral therapy (74.0%; 95% CI 71.0 to 76.7) compared with the group of patients on second-line antiretroviral therapy (50.9%; 95% CI 44.4 to 57.3) (p<0.01). CONCLUSION: Selecting the samples to be included in the pools and selecting the pools according to ART regimens are criteria that could lead to decreased spending on laboratory tests for HIV viral load determination in resource-constrained settings.

Projecting the epidemiological effect, cost-effectiveness and transmission of HIV drug resistance in Vietnam associated with viral load monitoring strategies.

OBJECTIVES: The objective of this study was to investigate the potential epidemiological impact of viral load (VL) monitoring and its cost-effectiveness in Vietnam, where transmitted HIV drug resistance (TDR) prevalence has increased from <5% to 5%-15% in the past decade. METHODS: Using a population-based mathematical model driven by data from Vietnam, we simulated scenarios of various combinations of VL testing coverage, VL thresholds for second-line ART initiation and availability of HIV drug-resistance tests. We assessed the cost per disability-adjusted life year (DALY) averted for each scenario. RESULTS: Projecting expected ART scale-up levels, to approximately double the number of people on ART by 2030, will lead to an estimated 18 510 cases (95% CI: 9120-34 600 cases) of TDR and 55 180 cases (95% CI: 40 540-65 900 cases) of acquired drug resistance (ADR) in the absence of VL monitoring. This projection corresponds to a TDR prevalence of 16% (95% CI: 11%-24%) and ADR of 18% (95% CI: 15%-20%). Annual or biennial VL monitoring with 30% coverage is expected to relieve 12%-31% of TDR (2260-5860 cases), 25%-59% of ADR (9620-22 650 cases), 2%-6% of HIV-related deaths (360-880 cases) and 19 270-51 400 DALYs during 2015-30. The 30% coverage of VL monitoring is estimated to cost US$4848-5154 per DALY averted. The projected additional cost for implementing this strategy is US$105-268 million over 2015-30. CONCLUSIONS: Our study suggests that a programmatically achievable 30% coverage of VL monitoring can have considerable benefits for individuals and leads to population health benefits by reducing the overall national burden of HIV drug resistance. It is marginally cost-effective according to common willingness-to-pay thresholds.

Clinical Evaluation of an Affordable Qualitative Viral Failure Assay for HIV Using Dried Blood Spots in Uganda.

BACKGROUND: WHO recommends regular viral load (VL) monitoring of patients on antiretroviral therapy (ART) for timely detection of virological failure, prevention of acquired HIV drug resistance (HIVDR) and avoiding unnecessary switching to second-line ART. However, the cost and complexity of routine VL testing remains prohibitive in most resource limited settings (RLS). We evaluated a simple, low-cost, qualitative viral-failure assay (VFA) on dried blood spots (DBS) in three clinical settings in Uganda. METHODS: We conducted a cross-sectional diagnostic accuracy study in three HIV/AIDS treatment centres at the Joint Clinical Research Centre in Uganda. The VFA employs semi-quantitative detection of HIV-1 RNA amplified from the LTR gene. We used paired dry blood spot (DBS) and plasma with the COBASAmpliPrep/COBASTaqMan, Roche version 2 (VLref) as the reference assay. We used the VFA at two thresholds of viral load, (>5,000 or >1,000 copies/ml). RESULTS: 496 paired VFA and VLref results were available for comparative analysis. Overall, VFA demonstrated 78.4% sensitivity, (95% CI: 69.7%-87.1%), 93% specificity (95% CI: 89.7%-96.4%), 89.3% accuracy (95% CI: 85%-92%) and an agreement kappa = 0.72 as compared to the VLref. The predictive values of positivity and negativity among patients on ART for >12 months were 72.7% and 99.3%, respectively. CONCLUSIONS: VFA allowed 89% of correct classification of VF. Only 11% of the patients were misclassified with the potential of unnecessary or late switch to second-line ART. Our findings present an opportunity to roll out simple and affordable VL monitoring for HIV-1 treatment in RLS.

Scale-up of Routine Viral Load Testing in Resource-Poor Settings: Current and Future Implementation Challenges.

Despite immense progress in antiretroviral therapy (ART) scale-up, many people still lack access to basic standards of care, with our ability to meet the Joint United Nations Programme on HIV/AIDS 90-90-90 treatment targets for HIV/AIDS dependent on dramatic improvements in diagnostics. The World Health Organization recommends routine monitoring of ART effectiveness using viral load (VL) testing at 6 months and every 12 months, to monitor treatment adherence and minimize failure, and will publish its VL toolkit later this year. However, the cost and complexity of VL is preventing scale-up beyond developed countries and there is a lack of awareness among clinicians as to the long-term patient benefits and its role in prolonging the longevity of treatment programs. With developments in this diagnostic field rapidly evolving-including the recent improvements for accurately using dried blood spots and the imminent appearance to the market of point-of-care technologies offering decentralized diagnosis-we describe current barriers to VL testing in resource-limited settings. Effective scale-up can be achieved through health system and laboratory system strengthening and test price reductions, as well as tackling multiple programmatic and funding challenges.