An integrated tiered service delivery model (ITSDM) based on local CD4 testing demands can improve turn-around times and save costs whilst ensuring accessible and scalable CD4 services across a national programme

Optimizing diagnostic networks to increase patient access to TB diagnostic services: Development of the diagnostic network optimization (DNO) approach and learnings from its application in Kenya, India and the Philippines

Diagnostic network optimization (DNO) is an analytical approach that enables use of available country data to inform evidence-based decision-making to optimize access to diagnostic services. A DNO methodology was developed using available data sources and a commercial supply chain optimization software. In collaboration with Ministries of Health and partners, the approach was applied in Kenya, India and the Philippines to map TB diagnostic networks, identify misalignments, and determine optimal network design to increase patient access to TB diagnostic services and improve device utilization. The DNO analysis was successfully applied to evaluate and inform TB diagnostic services in Kenya, India and the Philippines as part of national strategic planning for TB. The analysis was tailored to each country's specific objectives and allowed evaluation of factors such as the number and placement of different TB diagnostics, design of sample referral networks and integration of early infant diagnosis for HIV at national and sub-national levels and across public and private sectors. Our work demonstrates the value of DNO as an innovative approach to analysing and modelling diagnostic networks, particularly suited for use in low-resource settings, as an open-access approach that can be applied to optimize networks for any disease.

Modelling CD4 reagent usage across a national hierarchal network of laboratories in South Africa

Background

The National Health Laboratory Service is mandated to deliver cost-effective and efficient diagnostic services across South Africa. Their mandate is achieved by a network of laboratories ranging from centralised national laboratories to distant rural facilities.

Objective

This study aimed to establish a model of CD4 reagent utilisation as an independent measure of laboratory efficiency.

Methods

The efficiency percentage was defined as finished goods (number of reportable results) over raw materials (number of reagents supplied) for 47 laboratories in nine provinces (both anonymised) for 2019. The efficiency percentage at national and provincial levels was calculated and compared to the optimal efficiency percentage derived using pre-set assumptions. Comparative laboratory analysis was conducted for the provinces with the best and worst efficiency percentages. The possible linear relationship between the efficiency percentage and call-outs, days lost, referrals, and turn-around time was assessed.

Results

Data are reported for 2 806 799 CD4 tests, with an overall efficiency percentage of 84.5% (optimal of 84.98%). The efficiency percentage varied between 75.7% and 87.7% between provinces, while within the laboratory it ranged from 66.1% to 111.5%. Four laboratories reported an efficiency percentage ranging from 67.8% to 85.7%. No linear correlation was noted between the efficiency percentage, call-outs, days lost, and turn-around time performance.

Conclusion

Reagent efficiency percentage distinguished laboratories into different utilisation levels irrespective of their CD4 service level. This parameter is an additional independent indicator of laboratory performance, with no relationship with any contributing factors tested, that can be implemented across pathology disciplines for monitoring reagent utilisation.

What this study adds

This study provides an objective methodology to assess reagent utilisation as an independent measure of laboratory efficiency. This model could be applied to all routine pathology services.

Optimising courier specimen collection time improves patient access to HIV viral load testing in South Africa

BACKGROUND

South Africa uses a courier network for transporting specimens to public laboratories. After the daily collection of specimens from the facility by the courier, patients not yet attended to are unlikely to receive same-day blood draws, potentially inhibiting access to viral load (VL) testing for HIV patients.

OBJECTIVE

We aimed to design an optimised courier network and assess whether this improves VL testing access.

METHODS

We optimised the specimen transport network in South Africa for 4046 facilities (November 2019). For facilities with current specimen transport times (n = 356), we assessed the relationship between specimen transport time and VL testing access (number of annual VL tests per antiretroviral treatment patient) using regression analysis. We compared our optimised transport times with courier collection times to determine the change in access to same-day blood draws.

RESULTS

The number of annual VL tests per antiretroviral treatment patient (1.14, standard deviation: 0.02) was higher at facilities that had courier collection after 13:36 (the average latest collection time) than those that had their last collection before 13:36 (1.06, standard deviation: 0.03), even when adjusted for facility size. Through network optimisation, the average time for specimen transport was delayed to 14:35, resulting in a 6% - 13% increase in patient access to blood draws.

CONCLUSION

Viral load testing access depends on the time of courier collection at healthcare facilities. Simple solutions are frequently overlooked in the quest to improve healthcare. We demonstrate how simply changing specimen transportation timing could markedly improve access to VL testing.

Evaluation of fixed-panel, multicolour ClearLLab 10C at an academic flow cytometry laboratory in Johannesburg, South Africa

Background

Flow cytometric immunophenotyping is well established for the diagnosis of haematological neoplasms. New commercially available systems offer fixed, pre-aliquoted multi-parameter analysis to simplify sample preparation and standardise data analysis.

Objective

The Beckman Coulter (BC) ClearLLab™ 10C (4-tube) system was evaluated against an existing laboratory developed test (LDT).

Methods

Peripheral blood and bone marrow aspirates (n = 101), tested between August 2019 and November 2019 at an academic pathology laboratory in Johannesburg, South Africa, were analysed. Following daily instrument quality control, samples were prepared for LDT (using > 20 2–4-colour in-house panels and an extensive liquid monoclonal reagent repertoire) or ClearLLab 10C, and respectively analysed using in-house protocols on a Becton Dickinson FACSCalibur, or manufacturer-directed protocols on a BC Navios. Becton Dickinson Paint-a-Gate or BC Kaluza C software facilitated data interpretation. Diagnostic accuracy (concordance) was established by calculating sensitivity and specificity outcomes.

Results

Excellent agreement (clinical diagnostic concordance) with 100% specificity and sensitivity was established between LDT and ClearLLab 10C in 67 patients with a haematological neoplasm and 34 participants with no haematological disease. Similar acceptable diagnostic concordance (97%) was noted when comparing ClearLLab 10C to clinicopathological outcomes. Additionally, the ClearLLab 10C panels, analysed with Kaluza C software, enabled simultaneous discrimination of disease and concurrent background myeloid and lymphoid haematological populations, including assessing stages of maturation or sub-populations.

Conclusion

ClearLLab 10C panels provide excellent agreement to existing LDTs and may reliably be used for immunophenotyping of haematological neoplasms, simplifying and standardising sample preparation and data acquisition.

Newly implemented community CD4 service in Tshwaragano, Northern Cape province, South Africa, positively impacts result turn-around time

Background

The Northern Cape is South Africa’s largest province with an HIV prevalence of 7.1% versus a 13.5% national prevalence. CD4 testing is provided at three of five National Health Laboratory Service district laboratories, each covering a 250 km precinct radius. Districts without a local service report prolonged CD4 turn-around times (TAT).

Objective

This study documented the impact of a new CD4 laboratory in Tshwaragano in the remote John Taolo Gaetsewe district of the Northern Cape, South Africa.

Methods

CD4 test volumes and TAT (total, pre-analytical, analytical, and post-analytical) data for the Northern Cape province were extracted for June 2018 to October 2019. The percentage of CD4 results within the stipulated 40-h TAT cut-off and the median and 75th percentiles of all TAT parameters were calculated. Pre-implementation, samples collected at Tshwaragano were referred to Kimberley or Upington, Northern Cape, South Africa.

Results

Pre-implementation, 95.4% of samples at Tshwaragano were referred to Kimberley for CD4 testing (36.3% of Kimberley’s test volumes). Only 7.5% of Tshwaragano’s total samples were referred post-implementation. The Tshwaragano laboratory’s CD4 median total TAT decreased from 24.7 h pre-implementation to 12 h post-implementation (p = 0.003), with > 95.0% of results reported within 40 h. The Kimberley laboratory workload decreased by 29.0%, and testing time significantly decreased from 10 h to 4.3 h.

Conclusion

The new Tshwaragano CD4 service significantly decreased local TAT. Upgrading existing community laboratories to include CD4 testing can alleviate provincial service load and improve local access, TAT and efficiency in the centralised reference laboratory.

Use of Physical Accessibility Modelling in Diagnostic Network Optimization: A Review

Diagnostic networks are complex systems that include both laboratory-tested and community-based diagnostics, as well as a specimen referral system that links health tiers. Since diagnostics are the first step before accessing appropriate care, diagnostic network optimization (DNO) is crucial to improving the overall healthcare system. The aim of our review was to understand whether the field of DNO, and especially route optimization, has benefited from the recent advances in geospatial modeling, and notably physical accessibility modeling, that have been used in numerous health systems assessment and strengthening studies. All publications published in English between the journal’s inception and 12 August 2021 that dealt with DNO, geographical accessibility and optimization, were systematically searched for in Web of Science and PubMed, this search was complemented by a snowball search. Studies from any country were considered. Seven relevant publications were selected and charted, with a variety of geospatial approaches used for optimization. This paucity of publications calls for exploring the linkage of DNO procedures with realistic accessibility modeling framework. The potential benefits could be notably better-informed travel times of either the specimens or population, better estimates of the demand for diagnostics through realistic population catchments, and innovative ways of considering disease epidemiology to inform DNO.

Establishing the cost of Xpert MTB/RIF mobile testing in high-burden peri-mining communities in South Africa

Background

Globally, tuberculosis remains a major cause of mortality, with an estimated 1.3 million deaths per annum. The Xpert MTB/RIF assay is used as the initial diagnostic test in the tuberculosis diagnostic algorithm. To extend the national tuberculosis testing programme in South Africa, mobile units fitted with the GeneXpert equipment were introduced to high-burden peri-mining communities.

Objective

This study sought to assess the cost of mobile testing compared to traditional laboratory-based testing in a peri-mining community setting.

Methods

Actual cost data for mobile and laboratory-based Xpert MTB/RIF testing from 2018 were analysed using a bottom-up ingredients-based approach to establish the annual equivalent cost and the cost per result. Historical cost data were obtained from supplier quotations and the local enterprise resource planning system. Costs were obtained in rand and reported in United States dollars (USD).

Results

The mobile units performed 4866 tests with an overall cost per result of $49.16. Staffing accounted for 30.7% of this cost, while reagents and laboratory equipment accounted for 20.7% and 20.8%. The cost per result of traditional laboratory-based testing was $15.44 US dollars (USD). The cost for identifying a tuberculosis-positive result using mobile testing was $439.58 USD per case, compared to $164.95 USD with laboratory-based testing.

Conclusion

Mobile testing is substantially more expensive than traditional laboratory services but offers benefits for rapid tuberculosis case detection and same-day antiretroviral therapy initiation. Mobile tuberculosis testing should however be reserved for high-burden communities with limited access to laboratory testing where immediate intervention can benefit patient outcomes.

Developing Strategies for Onchocerciasis Elimination Mapping and Surveillance Through The Diagnostic Network Optimization Approach

Background

Onchocerciasis (river blindness) is a filarial disease targeted for elimination of transmission. However, challenges exist to the implementation of effective diagnostic and surveillance strategies at various stages of elimination programs. To address these challenges, we used a network data analytics approach to identify optimal diagnostic scenarios for onchocerciasis elimination mapping (OEM).

Methods

The diagnostic network optimization (DNO) method was used to model the implementation of the old Ov16 rapid diagnostic test (RDT) and of new RDTs in development for OEM under different testing strategy scenarios with varying testing locations, test performance and disease prevalence. Environmental suitability scores (ESS) based on machine learning algorithms were developed to identify areas at risk of transmission and used to select sites for OEM in Bandundu region in the Democratic Republic of Congo (DRC) and Uige province in Angola. Test sensitivity and specificity ranges were obtained from the literature for the existing RDT, and from characteristics defined in the target product profile for the new RDTs. Sourcing and transportation policies were defined, and costing information was obtained from onchocerciasis programs. Various scenarios were created to test various state configurations. The actual demand scenarios represented the disease prevalence at IUs according to the ESS, while the counterfactual scenarios (conducted only in the DRC) are based on adapted prevalence estimates to generate prevalence close to the statistical decision thresholds (5% and 2%), to account for variability in field observations. The number of correctly classified implementation units (IUs) per scenario were estimated and key cost drivers were identified.

Results

In both Bandundu and Uige, the sites selected based on ESS had high predicted onchocerciasis prevalence >10%. Thus, in the actual demand scenarios in both Bandundu and Uige, the old Ov16 RDT correctly classified all 13 and 11 IUs, respectively, as requiring CDTi. In the counterfactual scenarios in Bandundu, the new RDTs with higher specificity correctly classified IUs more cost effectively. The new RDT with highest specificity (99.8%) correctly classified all 13 IUs. However, very high specificity (e.g., 99.8%) when coupled with imperfect sensitivity, can result in many false negative results (missing decisions to start MDA) at the 5% statistical decision threshold (the decision rule to start MDA). This effect can be negated by reducing the statistical decision threshold to 2%. Across all scenarios, the need for second stage sampling significantly drove program costs upwards. The best performing testing strategies with new RDTs were more expensive than testing with existing tests due to need for second stage sampling, but this was offset by the cost of incorrect classification of IUs.

Conclusion

The new RDTs modelled added most value in areas with variable disease prevalence, with most benefit in IUs that are near the statistical decision thresholds. Based on the evaluations in this study, DNO could be used to guide the development of new RDTs based on defined sensitivities and specificities. While test sensitivity is a minor driver of whether an IU is identified as positive, higher specificities are essential. Further, these models could be used to explore the development and optimization of new tools for other neglected tropical diseases.

Implementing 'universal' access to antiretroviral treatment in South Africa: a scoping review on research priorities

‘Universal’ access to antiretroviral treatment (ART) has become the global standard for treating people living with HIV and achieving epidemic control; yet, findings from numerous ‘test and treat’ trials and implementation studies in sub-Saharan Africa suggest that bringing ‘universal' access to ART to scale is more complex than anticipated. Using South Africa as a case example, we describe the research priorities and foci in the literature on expanded ART access. To do so, we adapted Arksey and O’Malley’s six-stage scoping review framework to describe the peer-reviewed literature and opinion pieces on expanding access to ART in South Africa between 2000 and 2017. Data collection included systematic searches of two databases and hand-searching of a sub-sample of reference lists. We used an adapted socio-ecological thematic framework to categorize data according to where it located the challenges and opportunities of expanded ART eligibility: individual/client, health worker–client relationship, clinic/community context, health systems infrastructure and/or policy context. We included 194 research articles and 23 opinion pieces, of 1512 identified, addressing expanded ART access in South Africa. The peer-reviewed literature focused on the individual and health systems infrastructure; opinion pieces focused on changing roles of individuals, communities and health services implementers. We contextualized our findings through a consultative process with a group of researchers, HIV clinicians and programme managers to consider critical knowledge gaps. Unlike the published literature, the consultative process offered particular insights into the importance of researching and intervening in the relational aspects of HIV service delivery as South Africa’s HIV programme expands. An overwhelming focus on individual and health systems infrastructure factors in the published literature on expanded ART access in South Africa may skew understanding of HIV programme shortfalls away from the relational aspects of HIV services delivery and delay progress with finding ways to leverage non-medical modalities for achieving HIV epidemic control.

The Development of a Standardized Quality Assessment Material to Support Xpert® HIV-1 Viral Load Testing for ART Monitoring in South Africa

The tiered laboratory framework for human immunodeficiency virus (HIV) viral load monitoring accommodates a range of HIV viral load testing platforms, with quality assessment critical to ensure quality patient testing. HIV plasma viral load testing is challenged by the instability of viral RNA. An approach using an RNA stabilizing buffer is described for the Xpert^® HIV-1 Viral Load (Cepheid) assay and was tested in remote laboratories in South Africa. Plasma panels with known HIV viral titres were prepared in PrimeStore molecular transport medium for per-module verification and per-instrument external quality assessment. The panels were transported at ambient temperatures to 13 testing laboratories during 2017 and 2018, tested according to standard procedures and uploaded to a web portal for analysis. A total of 275 quality assessment specimens (57 verification panels and two EQA cycles) were tested. All participating laboratories met study verification criteria (n = 171 specimens) with an overall concordance correlation coefficient (ρ_c) of 0.997 (95% confidence interval (CI): 0.996 to 0.998) and a mean bias of −0.019 log copies per milliliter (cp/mL) (95% CI: −0.044 to 0.063). The overall EQA ρ_c (n = 104 specimens) was 0.999 (95% CI: 0.998 to 0.999), with a mean bias of 0.03 log cp/mL (95% CI: 0.02 to 0.05). These panels are suitable for use in quality monitoring of Xpert^® HIV-1 VL and are applicable to laboratories in remote settings.

Categorising specimen referral delays for CD4 testing: How inter-laboratory distances and travel times impact turn-around time across a national laboratory service in South Africa

Background

The South African National Health Laboratory Service provides laboratory services for public sector health facilities, utilising a tiered laboratory model to refer samples for CD4 testing from 255 source laboratories into 43 testing laboratories.

Objective

The aim of this study was to determine the impact of distance on inter-laboratory referral time for public sector testing in South Africa in 2018.

Methods

A retrospective cross-sectional study design analysed CD4 testing inter-laboratory turn-around time (TAT) data for 2018, that is laboratory-to-laboratory TAT from registration at the source to referral receipt at the testing laboratory. Google Maps was used to calculate inter-laboratory distances and travel times. Distances were categorised into four buckets, with the median and 75th percentile reported. Wilcoxon scores were used to assess significant differences in laboratory-to-laboratory TAT across the four distance categories.

Results

CD4 referrals from off-site source laboratories comprised 49% (n = 1 390 510) of national reporting. A positively skewed distribution of laboratory-to-laboratory TAT was noted, with a median travel time of 11 h (interquartile range: 7–17), within the stipulated 12 h target. Inter-laboratory distance categories of less than 100 km, 101–200 km, 201–300 km and more than 300 km (p < 0.0001) had 75th percentiles of 8 h, 17 h, 14 h and 27 h.

Conclusion

Variability in inter-laboratory TAT was noted for all inter-laboratory distances, especially those exceeding 300 km. The correlation between distance and laboratory-to-laboratory TAT suggests that interventions are required for distant laboratories.

Weekly laboratory turn-around time identifies poor performance masked by aggregated reporting

Background

High-level monthly, quarterly and annual turn-around time (TAT) reports are used to assess laboratory performance across the National Health Laboratory Service in South Africa. Individual laboratory performances are masked by aggregate TAT reporting across network of testing facilities.

Objective

This study investigated weekly TAT reporting to identify laboratory inefficiencies for intervention.

Methods

CD4 TAT data were extracted for 46 laboratories from the corporate data warehouse for the 2016/2017 financial period. The total TAT median, 75th percentile and percentage of samples meeting organisational TAT cut-off (90% within 40 hours) were calculated. Total TAT was reported at national, provincial and laboratory levels. Provincial TAT performance was classified as markedly or moderately poor, satisfactory and good based on the percentage of samples that met the cut-off. The pre-analytical, testing and result review TAT component times were calculated.

Results

Median annual TAT was 18.8 h, 75th percentile was 25 h and percentage within cut-off was 92% (n = 3 332 599). Corresponding 75th percentiles of component TAT were 10 h (pre-analytical), 22 h testing and 1.6 h review. Provincial 75th percentile TAT varied from 17.6 h to 34.1 h, with three good (n = 13 laboratories), four satisfactory (n = 24 laboratories) and two poor performers (n = 9 laboratories) provinces. Weekly TAT analysis showed 12/46 laboratories (28.6%) without outlier weeks, 31/46 (73.8%) with 1-10 outlier weeks and 3/46 (6.5%) with more than 10 (highest of 20/52 weeks) outlier weeks.

Conclusion

Masked TAT under-performances were revealed by weekly TAT analyses, identifying poorly performing laboratories needing immediate intervention; TAT component analyses identified specific areas for improvement.

Bringing Data Analytics to the Design of Optimized Diagnostic Networks in Low- and Middle-Income Countries: Process, Terms and Definitions

Diagnostics services are an essential component of healthcare systems, advancing universal health coverage and ensuring global health security, but are often unavailable or under-resourced in low- and middle-income (LMIC) countries. Typically, diagnostics are delivered at various tiers of the laboratory network based on population needs, and resource and infrastructure constraints. A diagnostic network additionally incorporates screening and includes point-of-care testing that may occur outside of a laboratory in the community and clinic settings; it also emphasizes the importance of supportive network elements, including specimen referral systems, as being critical for the functioning of the diagnostic network. To date, design and planning of diagnostic networks in LMICs has largely been driven by infectious diseases such as TB and HIV, relying on manual methods and expert consensus, with a limited application of data analytics. Recently, there have been efforts to improve diagnostic network planning, including diagnostic network optimization (DNO). The DNO process involves the collection, mapping, and spatial analysis of baseline data; selection and development of scenarios to model and optimize; and lastly, implementing changes and measuring impact. This review outlines the goals of DNO and steps in the process, and provides clarity on commonly used terms.

Cryptococcal meningitis: a review of cryptococcal antigen screening programs in Africa

INTRODUCTION

Cryptococcal meningitis remains a significant contributor to AIDS-related mortality despite widened access to antiretroviral therapy. Cryptococcal antigen (CrAg) can be detected in the blood prior to development of meningitis. Development of highly sensitive and specific rapid diagnostic CrAg tests has helped facilitate the adoption of CrAg screening programs in 19 African countries.

AREAS COVERED

The biological rationale for CrAg screening and the programmatic strategies for its implementation are reviewed. We describe the approach to the investigation of patients with cryptococcal antigenemia and the importance of lumbar puncture to identify individuals who may have cryptococcal meningitis in the absence of symptoms. The limitations of current treatment recommendations and the potential role of newly defined combination antifungal therapies are discussed. A literature review was conducted using a broad database search for cryptococcal antigen screening and related terms in published journal articles dating up to December 2019. Conference abstracts, publicly available guidelines, and project descriptions were also incorporated.

EXPERT OPINION

As we learn more about the risks of cryptococcal antigenemia, it has become clear that the current management paradigm is inadequate. More intensive investigation and management are required to prevent the development of cryptococcal meningitis and reduce mortality associated with cryptococcal antigenemia.

Assessment of two POC technologies for CD4 count in Morocco

Background

In the era of “test and treat strategy”, CD4 testing remains an important tool for monitoring HIV-infected individuals. Since conventional methods of CD4 count measurement are costly and cumbersome, POC CD4 counting technique are more affordable and practical for countries with limited resources. Before introducing such methods in Morocco, we decided to assess their reliability.

Methods

In this study 92 blood samples from HIV-infected patients, were tested by PIMA and FACSPresto to derive CD4 count. Flow cytometry using FacsCalibur, was used as reference method for CD4 count comparison. Linear regression, Bland–Altman analysis were performed to assess correlation and agreement between these POC methods and the reference method. In addition, sensitivity and specificity, positive predictive value (PPV), negative predictive value (NPV) and misclassification percentage at 350 and 200 CD4 count thresholds; were also determined. Finally, because FACSPresto can also measure hemoglobin (Hb) concentration, 52 samples were used to compare FACSPresto against an automated hematology analyzer.

Results

The coefficient of determination R² was 0.93 for both methods. Bland–Altman analysis displayed a mean bias of − 32.3 and − 8.1 cells/µl for PIMA and FACSPresto, respectively. Moreover, with a threshold of 350 CD4 count, PIMA displayed a sensitivity, specificity, PPV, NPV, were 88.57%, 94.12%, 91.18%, 92.31%; respectively. FACSPresto showed 88.23%, 96.23%, 93.75% and 92.73%; respectively. Furthermore, the upward misclassification percentage was 8.57 and 5.88%, for PIMA and FACSPresto, respectively; whereas the downward misclassification percentage was 7.84% and 7.54%; respectively. With 200 cells/µl threshold, PIMA had a sensitivity, specificity, PPV and NPV of 83.33%, 98.53%, 93.75% and 95.71%, respectively. Regarding FACSPresto, sensitivity, specificity, PPV and NPV was 82.35%, 98.57%, 88.57% and 95.83%; respectively. Upward misclassification percentage was 5.56% and 5.88%, for PIMA and FACSPresto, respectively; whereas downward misclassification percentage was 4.41% and 4.29%; respectively. Finally, the hemoglobin measurement evaluation displayed an R² of 0.80 and a mean bias of − 0.12 with a LOA between − 1.75 and 1.51.

Conclusion

When compared to the reference method, PIMA and FACSPresto have shown good performance, for CD4 counting. The introduction of such POC technology will speed up the uptake of patients in the continuum of HIV care, in our country.

Designing an optimized diagnostic network to improve access to TB diagnosis and treatment in Lesotho

Background

To reach WHO End tuberculosis (TB) targets, countries need a quality-assured laboratory network equipped with rapid diagnostics for tuberculosis diagnosis and drug susceptibility testing. Diagnostic network analysis aims to inform instrument placement, sample referral, staffing, geographical prioritization, integration of testing enabling targeted investments and programming to meet priority needs.

Methods

Supply chain modelling and optimization software was used to map Lesotho’s TB diagnostic network using available data sources, including laboratory and programme reports and health and demographic surveys. Various scenarios were analysed, including current network configuration and inclusion of additional GeneXpert and/or point of care instruments. Different levels of estimated demand for testing services were modelled (current [30,000 tests/year], intermediate [41,000 tests/year] and total demand needed to find all TB cases [88,000 tests/year]).

Results

Lesotho’s GeneXpert capacity is largely well-located but under-utilized (19/24 sites use under 50% capacity). The network has sufficient capacity to meet current and near-future demand and 70% of estimated total demand. Relocation of 13 existing instruments would deliver equivalent access to services, maintain turnaround time and reduce costs compared with planned procurement of 7 more instruments. Gaps exist in linking people with positive symptom screens to testing; closing this gap would require extra 11,000 tests per year and result in 1000 additional TB patients being treated. Closing the gap in linking diagnosed patients to treatment would result in a further 629 patients being treated. Scale up of capacity to meet total demand will be best achieved using a point-of-care platform in addition to the existing GeneXpert footprint.

Conclusions

Analysis of TB diagnostic networks highlighted key gaps and opportunities to optimize services. Network mapping and optimization should be considered an integral part of strategic planning. By building efficient and patient-centred diagnostic networks, countries will be better equipped to meet End TB targets.

Assessment of the AQUIOS flow cytometer - An automated sample preparation system for CD4 lymphocyte PanLeucogating enumeration

Background

Flow cytometry has been the approach of choice for enumerating and documenting CD4-cell decline in HIV monitoring. Beckman Coulter has developed a single platform test for CD4+ T-cell lymphocyte count and percentage using PanLeucogating (PLG) technology on the automated AQUIOS flow cytometer (AQUIOS PLG).

Objectives

This study compared the performance of AQUIOS PLG with the Flowcare PLG method and performed a reference interval for comparison with those previously published.

Methods

The study was conducted between November 2014 and March 2015 at 5 different centres located in Canada; Paris, France; Lyon, France; the United States; and South Africa. Two-hundred and forty samples from HIV-positive adult and paediatric patients were used to compare the performances of AQUIOS PLG and Flowcare PLG on a FC500 flow cytometer (Flowcare PLG) in determining CD4+ absolute count and percentage. A reference interval was determined using 155 samples from healthy, non-HIV adults. Workflow was investigated testing 440 samples over 5 days.

Results

Mean absolute and relative count bias between AQUIOS PLG and Flowcare PLG was −41 cells/µL and −7.8%. Upward and downward misclassification at various CD4 thresholds was ≤ 2.4% and ≤ 11.1%. The 95% reference interval (2.5th – 97.5th) for the CD4+ count was 453–1534 cells/µL and the percentage was 30.5% – 63.4%. The workflow showed an average number of HIV samples tested as 17.5 per hour or 122.5 per 8-hour shift for one technician, including passing quality controls.

Conclusion

The AQUIOS PLG merges desirable aspects from conventional flow cytometer systems (high throughput, precision and accuracy, external quality assessment compatibility) with low technical operating skill requirements for automated, single platform systems.

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.

Categorizing and Establishing CD4 Service Equivalency: Testing of Residual, Archived External Quality Assessment Scheme Sample Panels Enables Accelerated Virtual Peer Laboratory Review

BACKGROUND

Testing of collated, curated residual archived external quality assessment (EQA) trial material, with pre-established true (consensus) values collated into 25-sample panels enables virtual peer review of a laboratory's proficiency. In this study, we introduce how archived EQAS samples/panels can establish equivalency of CD4 reporting across multiple laboratories in a national program.

METHODS

Curated unused trial material from archived EQAS CD4 trials were collated into 25-sample panels comprising three sets of five-sample replicates and at least three duplicate samples. Panel-samples were tested using predicate methods of participating laboratories and proficiency determined by calculating a Standard Deviation Index (SDI) for each panel-sample reported according to retrospective consensus pooled trial outcomes. All data were plotted using MS Excel and Graphpad-Prism with SDI limits between -2 and +2 SDI to define acceptable performance. Percentage similarity analysis determined agreement. Bead-count-rate data was used to determine pipetting error.

RESULTS

Tight clustering of SDI outcomes predicted acceptable laboratory proficiency with acceptable accuracy and precision as evidenced by mean SDI < 0.5 and SD of SDI < 0.5. Random pipetting error was identified with aberrant BCR. Systematic under-reading of results was noted in one lab with excellent precision but mean SDI > 1.6. Additional training requirements were evident where a respective laboratory's SD of SDI exceeded 0.7.

CONCLUSIONS

Archival panel testing undertaken across a network of CD4 laboratories using the same CD4 method to simultaneously test the same panel prior to national implementation highlighted proficient laboratories and was useful for identifying sites with service deficiencies and immediate additional training needs. © 2019 International Clinical Cytometry Society.

Addressing antiretroviral therapy-related diagnostic coverage gaps across South Africa using a programmatic approach

Background

A major challenge facing South Africa is the concomitant HIV and tuberculosis epidemics. The National Health Laboratory Service provides testing for staging HIV-positive patients, monitoring patients on antiretroviral therapy (ART) and diagnosing tuberculosis. Not all health districts have equivalent ART-related coverage in particular for CD4 and HIV viral load testing.

Objectives

The Integrated Tiered Service Delivery Model coverage precinct approach was used to address ART-related testing service coverage gaps in a manner that balances cost, quality and equity.

Methods

An algorithm was developed to identify and address ART-related diagnostic coverage gaps. Data was extracted from the corporate data warehouse and Oracle systems for the period of April 2015 to March 2016. Daily test volumes were based on 21.73 working days per month. Data were analysed using MS Excel and mapped using ArcCatalog and ArcMap. Capacity analysis was informed by the available testing-platforms.

Results

Health district daily HIV viral load volumes ranged from 2 to 1308 samples. Nineteen candidate laboratories were identified to address the coverage gaps. Following the proximity analysis, testing was consolidated at four candidate laboratories, resulting in 13 revised candidate laboratories. The revised candidate laboratory daily HIV viral load referrals ranged between 5 and 205 samples, with CD4 volumes between 6 and 85 samples. Remaining coverage gaps were identified in seven municipalities.

Conclusions

The study demonstrated that the service coverage precinct approach could be used to identify coverage gaps for a defined ART-related testing repertoire.

Using laboratory data to categorise CD4 laboratory turn-around-time performance across a national programme

Background and objective

The National Health Laboratory Service provides CD4 testing through an integrated tiered service delivery model with a target laboratory turn-around time (TAT) of 48 h. Mean TAT provides insight into national CD4 laboratory performance. However, it is not sensitive enough to identify inefficiencies of outlying laboratories or predict the percentage of samples meeting the TAT target. The aim of this study was to describe the use of the median, 75th percentile and percentage within target of laboratory TAT data to categorise laboratory performance.

Methods

Retrospective CD4 laboratory data for 2015–2016 fiscal year were extracted from the corporate data warehouse. The laboratory TAT distribution and percentage of samples within the 48 h target were assessed. A scatter plot was used to categorise laboratory performance into four quadrants using both the percentage within target and 75th percentile TAT. The laboratory performance was labelled good, satisfactory or poor.

Results

TAT data reported a positive skew with a mode of 13 h and a median of 17 h and 75th percentile of 25 h. Overall, 93.2% of CD4 samples had a laboratory TAT of less than 48 h. 48 out of 52 laboratories reported good TAT performance, i.e. percentage within target > 85% and 75th percentile ≤ 48 h, with two categorised as satisfactory (one parameter met), and two as poor performing laboratories (failed both parameters).

Conclusion

This study demonstrated the feasibility of utilising laboratory data to categorise laboratory performance. Using the quadrant approach for TAT data, laboratories that need interventions can be highlighted for root cause analysis assessment.

CD4 cell count variability with repeat testing in South Africa: Should reporting include both absolute counts and ranges of plausible values?

Although eligibility for antiretroviral treatment is no longer based on CD4 thresholds, CD4 testing remains important. Variation in CD4 cell count complicates initiation of antibiotic prophylaxis, differential diagnoses and assessments of immunological recovery. Five hundred and fifty-three HIV-positive antiretroviral-naïve adults, recruited from inner-city clinics, had three serial CD4 cell count tests. Test 1 was mostly done in a laboratory network supporting primary care clinics, while Tests 2 and 3 were performed in a tertiary-level laboratory. Reproducibility was assessed through Bland-Altman limits of agreement and coefficients of variation. Participants, a mean age of 34 years and mostly female (57%), had a median 203 CD4 cells/μL (Test 1). Seventeen per cent classified as having advanced HIV disease (CD4 cell count  < 200 cells/µL) on Test 1 had a CD4 cell count > 200 cells/µL on Tests 2 and 3. Mean differences between tests were <10 cells/µL for all comparisons. Limits of agreement for Tests 1 and 2 were -106.9 to 112.7 and coefficient of variation 15. Corresponding figures for Tests 2 and 3 were -88.2 to 103.4, and 13. Means of tests were similar, suggesting no systematic measurement differences, despite testing being done at different times. Variations were, however, considerable in many instances, though smaller in testing done in the same laboratory. CD4 cut-offs must not be applied rigidly, but rather constitute one amongst many factors used to guide patient care. Moreover, given the difficulties in determining whether CD4 changes are due to HIV disease, or other biological and laboratory factors, CD4 laboratory reports should include a range of plausible values, not only the absolute count.

The impact of digital technologies on point-of-care diagnostics in resource-limited settings

INTRODUCTION

Simple, rapid tests that can be used at the point-of-care (POC) can improve access to diagnostic services and overall patient management in resource-limited settings where laboratory infrastructure is limited. Implementation of POC tests places tremendous strain on already fragile health systems as the demand for training, supply management and quality assurance are amplified. Digital health has a major role to play in ensuring effective delivery and management of POC testing services. Area covered: The ability to digitise laboratory and POC platforms, including lateral flow rapid diagnostic test results, can standardize the interpretation of results and allows data to be linked to proficiency testing to ensure testing quality, reducing interpretation and transcription errors. Remote monitoring of POC instrument functionality and utilization through connectivity, allows programs to optimize instrument placement, algorithm adoption and supply management. Alerts can be built into the system to raise alarm at unusual trends such as outbreaks. Expert commentary: Digital technology has had a powerful impact on POC testing in resource limited settings. Technology, markets, and medical devices have matured to enable connected diagnostics to become a useful tool for epidemiology, patient care and tracking, research, and antimicrobial resistance and outbreak surveillance. However, to unlock this potential, digital tools must first add value at the point of patient care. The global health community need to propose models for protecting intellectual property to foster innovation and for safeguarding data confidentiality.

Improving Laboratory Efficiency in the Caribbean to Attain the World Health Organization HIV Treat All Recommendations

Scientific evidence showing the benefits of early initiation of antiretroviral therapy (ART) prompted World Health organization (WHO) to recommend that all persons diagnosed as HIV positive should commence ART irrespective of CD4 count and disease progression. Based on this recommendation, countries should adopt and implement the HIV "Treat All" policy to achieve the UNAIDS 90-90-90 targets and ultimately reach epidemic control. Attaining this goal along the HIV treatment cascade depends on the laboratory to monitor progress and measure impact. The laboratory plays an important role in HIV diagnosis to attain the first 90 and in viral load (VL) and HIV drug resistance testing to reinforce adherence, improve viral suppression, and measure the third 90. Countries in the Caribbean region have endorsed the WHO HIV "Treat all" recommendation; however, they are faced with diminishing financial resources to support laboratory testing, seen as a rate-limiting factor to achieving this goal. To improve laboratory coverage with fewer resources in the Caribbean there is the need to optimize laboratory operations to ensure the implementation of high quality, less expensive evidence-based approaches that will result in more efficient and effective service delivery. Suggested practical and innovative approaches to achieve this include: (1) targeted testing within HIV hotspots; (2) strengthening sample referral systems for VL; (3) better laboratory data collection systems; and (4) use of treatment cascade data for programmatic decision-making. Furthermore, strengthening quality improvement and procurement systems will minimize diagnostic errors and guarantee a continuum of uninterrupted testing which is critical for routine monitoring of patients to meet the stated goal.

Performance verification of the new fully automated Aquios flow cytometer PanLeucogate (PLG) platform for CD4-T-lymphocyte enumeration in South Africa

BACKGROUND

The National Health Laboratory Service (NHLS) offers wide-scale CD4 testing through a network of laboratories in South Africa. A new "load and go" cytometer (Aquios CL, Beckman Coulter), developed with a PLG protocol, was validated against the predicate PLG method on the Beckman Coulter FC500 MPL/CellMek platform.

METHODS

Remnant routine EDTA blood CD4 reference results were compared to results from two Aquios/PLG instruments (n = 205) and a further n = 1885 samples tested to assess daily testing capacity. Reproducibility was assessed using ImmunotrolTM and patient samples with low, medium, high CD4 counts. Data was analyzed using GraphPad software for general statistics and Bland-Altman (BA) analyses. The percentage similarity (%Sim) was used to measure the level of agreement (accuracy) of the new platform versus the predicate and variance (%SimCV) reported to indicate precision of difference to predicate.

RESULTS

205 samples were tested with a CD4 count range of 2-1228 cells/μl (median 365cells/μl). BA analysis revealed an overall -40.5±44.0cells/μl bias (LOA of 126.8 to 45.8cells/μl) and %Sim showing good agreement and tight precision to predicate results (94.83±5.39% with %SimCV = 5.69%). Workflow analysis (n = 1885) showed similar outcomes 94.9±8.9% (CV of 9.4%) and 120 samples/day capacity. Excellent intra-instrument reproducibility was noted (%Sim 98.7±2.8% and %SimCV of 2.8%). 5-day reproducibility using internal quality control material (Immunotrol™) showed tight precision (reported %CV of 4.69 and 7.62 for Normal and Low material respectively) and instrument stability.

CONCLUSION

The Aquios/PLG CD4 testing platform showed clinically acceptable result reporting to existing predicate results, with good system stability and reproducibility with a slight negative but precise bias. This system can replace the faded XL cytometers in low- to medium volume CD4 testing laboratories, using the standardized testing protocol, with better staff utilization especially where technical skills are lacking. Central monitoring of on-board quality assessment data facilitates proactive maintenance and networked instrument performance monitoring.

Programmatic implications of implementing the relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory sites, test volumes, platform distribution and space requirements

INTRODUCTION

CD4 testing in South Africa is based on an integrated tiered service delivery model that matches testing demand with capacity. The National Health Laboratory Service has predominantly implemented laboratory-based CD4 testing. Coverage gaps, over-/under-capacitation and optimal placement of point-of-care (POC) testing sites need investigation.

OBJECTIVES

We assessed the impact of relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory and POC testing sites.

METHODS

The RACL algorithm was developed to allocate laboratories and POC sites to ensure coverage using a set coverage approach for a defined travel time (T). The algorithm was repeated for three scenarios (A: T = 4; B: T = 3; C: T = 2 hours). Drive times for a representative sample of health facility clusters were used to approximate T. Outcomes included allocation of testing sites, Euclidian distances and test volumes. Additional analysis included platform distribution and space requirement assessment. Scenarios were reported as fusion table maps.

RESULTS

Scenario A would offer a fully-centralised approach with 15 CD4 laboratories without any POC testing. A significant increase in volumes would result in a four-fold increase at busier laboratories. CD4 laboratories would increase to 41 in scenario B and 61 in scenario C. POC testing would be offered at two sites in scenario B and 20 sites in scenario C.

CONCLUSION

The RACL algorithm provides an objective methodology to address coverage gaps through the allocation of CD4 laboratories and POC sites for a given T. The algorithm outcomes need to be assessed in the context of local conditions.

Estimating the cost-per-result of a national reflexed Cryptococcal antigenaemia screening program: Forecasting the impact of potential HIV guideline changes and treatment goals

Introduction

During 2016, the National Health Laboratory Service (NHLS) introduced laboratory-based reflexed Cryptococcal antigen (CrAg) screening to detect early Cryptococcal disease in immunosuppressed HIV+ patients with a confirmed CD4 count of 100 cells/μl or less.

Objective

The aim of this study was to assess cost-per-result of a national screening program across different tiers of laboratory service, with variable daily CrAg test volumes. The impact of potential ART treatment guideline and treatment target changes on CrAg volumes, platform choice and laboratory workflow are considered.

Methods

CD4 data (with counts < = 100 cells/μl) from the fiscal year 2015/16 were extracted from the NHLS Corporate Date Warehouse and used to project anticipated daily CrAg testing volumes with appropriately-matched CrAg testing platforms allocated at each of 52 NHLS CD4 laboratories. A cost-per-result was calculated for four scenarios, including the existing service status quo (Scenario-I), and three other settings (as Scenarios II-IV) which were based on information from recent antiretroviral (ART) guidelines, District Health Information System (DHIS) data and UNAIDS 90/90/90 HIV/AIDS treatment targets. Scenario-II forecast CD4 testing offered only to new ART initiates recorded at DHIS. Scenario-III projected all patients notified as HIV+, but not yet on ART (recorded at DHIS) and Scenario-IV forecast CrAg screening in 90% of estimated HIV+ patients across South Africa (also DHIS). Stata was used to assess daily CrAg volumes at the 5^th, 10^th, 25^th, 50^th, 75^th, 90^th and 95^th percentiles across 52 CD4-laboratories. Daily volumes were used to determine technical effort/ operator staff costs (% full time equivalent) and cost-per-result for all scenarios.

Results

Daily volumes ranged between 3 and 64 samples for Scenario-I at the 5th and 95th percentile. Similarly, daily volumes ranges of 1–12, 2–45 and 5–100 CrAg-directed samples were noted for Scenario’s II, III and IV respectively. A cut-off of 30 CrAg tests per day defined use of either LFA or EIA platform. LFA cost-per-result ranged from $8.24 to $5.44 and EIA cost-per-result between $5.58 and $4.88 across the range of test volumes. The technical effort across scenarios ranged from 3.2–27.6% depending on test volumes and platform used.

Conclusion

The study reported the impact of programmatic testing requirements on varying CrAg test volumes that subsequently influenced choice of testing platform, laboratory workflow and cost-per-result. A novel percentiles approach is described that enables an overview of the cost-per-result across a national program. This approach facilitates cross-subsidisation of more expensive lower volume sites with cost-efficient, more centralized higher volume laboratories, mitigating against the risk of costing tests at a single site.

HIV viral load scale-up: multiple interventions to meet the HIV treatment cascade

PURPOSE OF REVIEW

In 2015, the WHO urged countries to provide ART to all people living with HIV, irrespective of their CD4 cell count, this new recommendation supports the Joint United Nations Programme on HIV/AIDS elimination targets. However, to meet these aims, urgent scale-up of viral load testing is critical. The multiple interventions in the healthcare system required to support scale-up of viral load testing are reviewed here.

RECENT FINDINGS

It is estimated that 18.2 million individuals are accessing antiretroviral therapy, consequently this will cause significant demand for viral load monitoring; however, at the current rate of implementation, demand will not meet the required target by 2020. To change this trajectory, multiple stakeholders must be involved, communities and key populations need increased treatment literacy to create demand and greater numbers of healthcare workers will require training. In addition, laboratories and point-of-care testing sites will need to be expanded, and adequate monitoring and evaluation tools will need to be put in place to identify gaps in the system, to institute prompt corrective actions and to direct resources where needed.

SUMMARY

Sufficient scale-up of viral load may well be possible if innovations in mHealth are used to support healthcare workers and patients with regard to the scale-up and effective use of viral load monitoring; new laboratory technologies are implemented, both at a centralized level and point-of-care, to manage higher volumes and improve coverage; and there is careful coordination between implementing partners and funders.

Establishing a cost-per-result of laboratory-based, reflex Cryptococcal antigenaemia screening (CrAg) in HIV+ patients with CD4 counts less than 100 cells/μl using a Lateral Flow Assay (LFA) at a typical busy CD4 laboratory in South Africa

INTRODUCTION

Cryptococcal meningitis is a major cause of mortality and morbidity in countries with high HIV prevalence, primarily affecting patients whose CD4 are < = 100 cells/μl. Routine Cryptococcal Antigen (CrAg) screening is thus recommended in the South African HIV treatment guidelines for all patients with CD4 counts < = 100 cells/μl, followed by pre-emptive anti-fungal therapy where CrAg results are positive. A laboratory-based reflexed CrAg screening approach, using a Lateral Flow Assay (LFA) on remnant EDTA CD4 blood samples, was piloted at three CD4 laboratories.

OBJECTIVES

This study aimed to assess the cost-per-result of laboratory-based reflexed CrAg screening at one pilot CD4 referral laboratory.

METHODS

CD4 test volumes from 2014 were extracted to estimate percentage of CD4 < = 100 cells/μl. Daily average volumes were derived, assuming 12 months per/year and 21.73 working days per/month. Costing analyses were undertaken using Microsoft Excel and Stata with a provider prospective. The cost-per-result was estimated using a bottom-up method, inclusive of test kits and consumables (reagents), laboratory equipment and technical effort costs. The ZAR/$ exchange of 14.696/$1 was used, where applicable. One-way sensitivity analyses on the cost-per-result were conducted for possible error rates (3%- 8%, reductions or increases in reagent costs as well as test volumes (ranging from -60% to +60%).

RESULTS

The pilot CD4 laboratory performed 267000 CD4 tests in 2014; ~ 9.3% (27500) reported CD4< = 100 cells/μl, equivalent to 106 CrAg tests performed daily. A batch of 30-tests could be performed in 1.6 hours, including preparation and analysis time. A cost-per-result of $4.28 was reported, with reagents contributing $3.11 (72.8%), while technical effort and laboratory equipment overheads contributed $1.17 (27.2%) and $0.03 (<1%) respectively. One-way sensitivity analyses including increasing or decreasing test volumes by 60% revealed a cost-per-result range of $3.84 to $6.03.

CONCLUSION

A cost-per-result of $4.28 was established in a typical CD4 service laboratory to enable local budgetary cost projections and programmatic cost-effectiveness modelling. Varying reagent costs linked to currency exchange and varying test volumes in different levels of service can lead to varying cost-per-test and technical effort to manage workload, with an inverse relationship of higher costs expected at lower volumes of tests.

Options to Expand HIV Viral Load Testing in South Africa: Evaluation of the GeneXpert® HIV-1 Viral Load Assay

BACKGROUND

Expansion of HIV viral load (VL) testing services are required to meet increased targets for monitoring patients on antiretroviral treatment. South Africa currently tests >4million VLs per annum in 16 highly centralised, automated high-throughput laboratories. The Xpert HIV-1 VL assay (Cepheid) was evaluated against in-country predicates, the Roche Cobas Taqmanv2 and Abbott HIV-1RT, to investigate options for expanding VL testing using GeneXpert's random access, polyvalent capabilities and already established footprint in South Africa with the Xpert MTB/RIF assay (207 sites). Additionally, the performance of Xpert HIV-1VL on alternative, off-label specimen types, Dried Blood Spots (DBS) and whole blood, was investigated.

METHOD

Precision, accuracy (agreement) and clinical misclassification (1000cp/ml) of Xpert HIV-1VL plasma was compared to Taqmanv2 (n = 155) and Abbott HIV-1 RT (n = 145). Misclassification of Xpert HIV-1VL was further tested on DBS (n = 145) and whole blood (n = 147).

RESULTS

Xpert HIV-1VL demonstrated 100% concordance with predicate platforms on a standardised frozen, plasma panel (n = 42) and low overall percentage similarity CV of 1.5% and 0.9% compared to Taqmanv2 and Abbott HIV-1 RT, respectively. On paired plasma clinical specimens, Xpert HIV-1VL had low bias (SD 0.32-0.37logcp/ml) and 3% misclassification at the 1000cp/ml threshold compared to Taqmanv2 (fresh) and Abbott HIV-1 RT (frozen), respectively. Xpert HIV-1VL on whole blood and DBS increased misclassification (upward) by up to 14% with increased invalid rate. All specimen testing was easy to perform and compatible with concurrent Xpert MTB/RIF Tuberculosis testing on the same instrument.

CONCLUSION

The Xpert HIV-1VL on plasma can be used interchangeably with existing predicate platforms in South Africa. Whole blood and DBS testing requires further investigation, but polyvalency of the GeneXpert offers a solution to extending VL testing services.

South Africa's experience with provision of quality HIV diagnostic services

No abstract available.

Progress in Harmonizing Tiered HIV Laboratory Systems: Challenges and Opportunities in 8 African Countries

Countries have had mixed results in adhering to laboratory instrument procurement lists, with some limiting instrument brand expansion and others experiencing substantial growth in instrument counts and brand diversity. Important challenges to advancing laboratory harmonization strategies include:

Lack of adherence to procurement policies

Lack of an effective coordinating body

Misalignment of laboratory policies, treatment guidelines, and minimum service packages

In 2014, the Joint United Nations Programme on HIV/AIDS released its 90-90-90 targets, which make laboratory diagnostics a cornerstone for measuring efforts toward the epidemic control of HIV. A data-driven laboratory harmonization and standardization approach is one way to create efficiencies and ensure optimal laboratory procurements. Following the 2008 “Maputo Declaration on Strengthening of Laboratory Systems”—a call for government leadership in harmonizing tiered laboratory networks and standardizing testing services—several national ministries of health requested that the United States Government and in-country partners help implement the recommendations by facilitating laboratory harmonization and standardization workshops, with a primary focus on improving HIV laboratory service delivery. Between 2007 and 2015, harmonization and standardization workshops were held in 8 African countries. This article reviews progress in the harmonization of laboratory systems in these 8 countries. We examined agreed-upon instrument lists established at the workshops and compared them against instrument data from laboratory quantification exercises over time. We used this measure as an indicator of adherence to national procurement policies. We found high levels of diversity across laboratories’ diagnostic instruments, equipment, and services. This diversity contributes to different levels of compliance with expected service delivery standards. We believe the following challenges to be the most important to address: (1) lack of adherence to procurement policies, (2) absence or limited influence of a coordinating body to fully implement harmonization proposals, and (3) misalignment of laboratory policies with minimum packages of care and with national HIV care and treatment guidelines. Overall, the effort to implement the recommendations from the Maputo Declaration has had mixed success and is a work in progress. Program managers should continue efforts to advance the principles outlined in the Maputo Declaration. Quantification exercises are an important method of identifying instrument diversity, and provide an opportunity to measure efforts toward standardization.

Screening HIV-Infected Patients with Low CD4 Counts for Cryptococcal Antigenemia prior to Initiation of Antiretroviral Therapy: Cost Effectiveness of Alternative Screening Strategies in South Africa

Background

In 2015 South Africa established a national cryptococcal antigenemia (CrAg) screening policy targeted at HIV-infected patients with CD4+ T-lymphocyte (CD4) counts <100 cells/ μl who are not yet on antiretroviral treatment (ART). Two screening strategies are included in national guidelines: reflex screening, where a CrAg test is performed on remnant blood samples from CD4 testing; and provider-initiated screening, where providers order a CrAg test after a patient returns for CD4 test results. The objective of this study was to compare costs and effectiveness of these two screening strategies.

Methods

We developed a decision analytic model to compare reflex and provider-initiated screening in terms of programmatic and health outcomes (number screened, number identified for preemptive treatment, lives saved, and discounted years of life saved) and screening and treatment costs (2015 USD). We estimated a base case with prevalence and other parameters based on data collected during CrAg screening pilot projects integrated into routine HIV care in Gauteng, Free State, and Western Cape Provinces. We conducted sensitivity analyses to explore how results change with underlying parameter assumptions.

Results

In the base case, for each 100,000 CD4 tests, the reflex strategy compared to the provider-initiated strategy has higher screening costs ($37,536 higher) but lower treatment costs ($55,165 lower), so overall costs of screening and treatment are $17,629 less with the reflex strategy. The reflex strategy saves more lives (30 lives, 647 additional years of life saved). Sensitivity analyses suggest that reflex screening dominates provider-initiated screening (lower total costs and more lives saved) or saves additional lives for small additional costs (< $125 per life year) across a wide range of conditions (CrAg prevalence, patient and provider behavior, patient survival without treatment, and effectiveness of preemptive fluconazole treatment).

Conclusions

In countries with substantial numbers of people with untreated, advanced HIV disease such as South Africa, CrAg screening before initiation of ART has the potential to reduce cryptococcal meningitis and save lives. Reflex screening compared to provider-initiated screening saves more lives and is likely to be cost saving or have low additional costs per additional year of life saved.

Impact and Cost-Effectiveness of Point-Of-Care CD4 Testing on the HIV Epidemic in South Africa

Rapid diagnostic tools have been shown to improve linkage of patients to care. In the context of infectious diseases, assessing the impact and cost-effectiveness of such tools at the population level, accounting for both direct and indirect effects, is key to informing adoption of these tools. Point-of-care (POC) CD4 testing has been shown to be highly effective in increasing the proportion of HIV positive patients who initiate ART. We assess the impact and cost-effectiveness of introducing POC CD4 testing at the population level in South Africa in a range of care contexts, using a dynamic compartmental model of HIV transmission, calibrated to the South African HIV epidemic. We performed a meta-analysis to quantify the differences between POC and laboratory CD4 testing on the proportion linking to care following CD4 testing. Cumulative infections averted and incremental cost-effectiveness ratios (ICERs) were estimated over one and three years. We estimated that POC CD4 testing introduced in the current South African care context can prevent 1.7% (95% CI: 0.4% - 4.3%) of new HIV infections over 1 year. In that context, POC CD4 testing was cost-effective 99.8% of the time after 1 year with a median estimated ICER of US$4,468/DALY averted. In healthcare contexts with expanded HIV testing and improved retention in care, POC CD4 testing only became cost-effective after 3 years. The results were similar when, in addition, ART was offered irrespective of CD4 count, and CD4 testing was used for clinical assessment. Our findings suggest that even if ART is expanded to all HIV positive individuals and HIV testing efforts are increased in the near future, POC CD4 testing is a cost-effective tool, even within a short time horizon. Our study also illustrates the importance of evaluating the potential impact of such diagnostic technologies at the population level, so that indirect benefits and costs can be incorporated into estimations of cost-effectiveness.

PIMA™ point-of-care testing for CD4 counts in predicting antiretroviral initiation in HIV-infected individuals in KwaZulu-Natal, Durban, South Africa

Introduction

Limited information is available on the usefulness of the PIMA™ analyser in predicting antiretroviral treatment eligibility and outcome in a primary healthcare clinic setting in disadvantaged communities in KwaZulu-Natal, South Africa.

Materials and methods

The study was conducted under the eThekwini Health Unit, Durban, KwaZulu-Natal. Comparison of the enumeration of CD4+ T-cells in 268 patients using the PIMA™ analyser and the predicate National Health Laboratory Services (NHLS) was undertaken during January to July 2013. Bland-Altman analysis to calculate bias and limits of agreement, precision and levels of clinical misclassification at various CD4+ T-cell count thresholds was performed.

Results

There was high precision of the PIMA™ control bead cartridges with low and normal CD4+ T-cell counts using three different PIMA™ analysers (%CV < 5). Under World Health Organization (WHO) guidelines (≤ 500 cells/mm³), the sensitivity of the PIMA™ analyser was 94%, specificity 78% and positive predictive value (PPV) 95%. There were 24 (9%) misclassifications, of which 13 were false-negative in whom the mean bias was 149 CD4+ T-cells/mm³. Most (87%) patients returned for their CD4 test result but only 67% (110/164) of those eligible (≤ 350 cells/mm³) were initiated on antiretroviral therapy (ART) with a time to treatment of 49 days (interquartile range [IQR], 42–64 days).

Conclusion

There was adequate agreement between PIMA™ analyser and predicate NHLS CD4+ T-cell count enumeration (≤ 500 cells/mm³) in adult HIV-positive individuals. The high PPV, sensitivity and acceptable specificity of the PIMA™ analyser technology lend it as a reliable tool in predicting eligibility and rapid linkage to care in ART programmes.

Performance Evaluation of the Becton Dickinson FACSPresto™ Near-Patient CD4 Instrument in a Laboratory and Typical Field Clinic Setting in South Africa

Background

The BD-FACSPresto^™ CD4 is a new, point-of-care (POC) instrument utilising finger-stick capillary blood sampling. This study evaluated its performance against predicate CD4 testing in South Africa.

Methods

Phase-I testing: HIV+ patient samples (n = 214) were analysed on the Presto^™ under ideal laboratory conditions using venous blood. During Phase-II, 135 patients were capillary-bled for CD4 testing on FACSPresto^™, performed according to manufacturer instruction. Comparative statistical analyses against predicate PLG/CD4 method and industry standards were done using GraphPad Prism 6. It included Bland-Altman with 95% limits of agreement (LOA) and percentage similarity with coefficient of variation (%CV) analyses for absolute CD4 count (cells/μl) and CD4 percentage of lymphocytes (CD4%).

Results

In Phase-I, 179/217 samples yielded reportable results with Presto^™ using venous blood filled cartridges. Compared to predicate, a mean bias of 40.4±45.8 (LOA of -49.2 to 130.2) and %similarity (%CV) of 106.1%±7.75 (7.3%) was noted for CD4 absolute counts. In Phase-2 field study, 118/135 capillary-bled Presto^™ samples resulted CD4 parameters. Compared to predicate, a mean bias of 50.2±92.8 (LOA of -131.7 to 232) with %similarity (%CV) 105%±10.8 (10.3%), and 2.87±2.7 (LOA of -8.2 to 2.5) with similarity of 94.7±6.5% (6.83%) noted for absolute CD4 and CD4% respectively. No significant clinical differences were indicated for either parameter using two sampling methods.

Conclusion

The Presto^™ produced remarkable precision to predicate methods, irrespective of venous or capillary blood sampling. A consistent, clinically insignificant over-estimation (5–7%) of counts against PLG/CD4 and equivalency to FACSCount^™ was noted. Further field studies are awaited to confirm longer-term use.

Estimating implementation and operational costs of an integrated tiered CD4 service including laboratory and point of care testing in a remote health district in South Africa

BACKGROUND

An integrated tiered service delivery model (ITSDM) has been proposed to provide 'full-coverage' of CD4 services throughout South Africa. Five tiers are described, defined by testing volumes and number of referring health-facilities. These include: (1) Tier-1/decentralized point-of-care service (POC) in a single site; Tier-2/POC-hub servicing processing < 30-40 samples from 8-10 health-clinics; Tier-3/Community laboratories servicing ∼ 50 health-clinics, processing < 150 samples/day; high-volume centralized laboratories (Tier-4 and Tier-5) processing < 300 or > 600 samples/day and serving > 100 or > 200 health-clinics, respectively. The objective of this study was to establish costs of existing and ITSDM-tiers 1, 2 and 3 in a remote, under-serviced district in South Africa.

METHODS

Historical health-facility workload volumes from the Pixley-ka-Seme district, and the total volumes of CD4 tests performed by the adjacent district referral CD4 laboratories, linked to locations of all referring clinics and related laboratory-to-result turn-around time (LTR-TAT) data, were extracted from the NHLS Corporate-Data-Warehouse for the period April-2012 to March-2013. Tiers were costed separately (as a cost-per-result) including equipment, staffing, reagents and test consumable costs. A one-way sensitivity analyses provided for changes in reagent price, test volumes and personnel time.

RESULTS

The lowest cost-per-result was noted for the existing laboratory-based Tiers- 4 and 5 ($6.24 and $5.37 respectively), but with related increased LTR-TAT of > 24-48 hours. Full service coverage with TAT < 6-hours could be achieved with placement of twenty-seven Tier-1/POC or eight Tier-2/POC-hubs, at a cost-per-result of $32.32 and $15.88 respectively. A single district Tier-3 laboratory also ensured 'full service coverage' and < 24 hour LTR-TAT for the district at $7.42 per-test.

CONCLUSION

Implementing a single Tier-3/community laboratory to extend and improve delivery of services in Pixley-ka-Seme, with an estimated local ∼ 12-24-hour LTR-TAT, is ∼ $2 more than existing referred services per-test, but 2-4 fold cheaper than implementing eight Tier-2/POC-hubs or providing twenty-seven Tier-1/POCT CD4 services.