Socioeconomic inequalities in cervical precancer screening among women in Ethiopia, Malawi, Rwanda, Tanzania, Zambia and Zimbabwe: analysis of Population-Based HIV Impact Assessment surveys.

OBJECTIVES: We examined age, residence, education and wealth inequalities and their combinations on cervical precancer screening probabilities for women. We hypothesised that inequalities in screening favoured women who were older, lived in urban areas, were more educated and wealthier. DESIGN: Cross-sectional study using Population-Based HIV Impact Assessment data. SETTING: Ethiopia, Malawi, Rwanda, Tanzania, Zambia and Zimbabwe. Differences in screening rates were analysed using multivariable logistic regressions, controlling for age, residence, education and wealth. Inequalities in screening probability were estimated using marginal effects models. PARTICIPANTS: Women aged 25-49 years, reporting screening. OUTCOME MEASURES: Self-reported screening rates, and their inequalities in percentage points, with differences of 20%+ defined as high inequality, 5%-20% as medium, 0%-5% as low. RESULTS: The sample size of participants ranged from 5882 in Ethiopia to 9186 in Tanzania. The screening rates were low in the surveyed countries, ranging from 3.5% (95% CI 3.1% to 4.0%) in Rwanda to 17.1% (95% CI 15.8% to 18.5%) and 17.4% (95% CI 16.1% to 18.8%) in Zambia and Zimbabwe. Inequalities in screening rates were low based on covariates. Combining the inequalities led to significant inequalities in screening probabilities between women living in rural areas aged 25-34 years, with a primary education level, from the lowest wealth quintile, and women living in urban areas aged 35-49 years, with the highest education level, from the highest wealth quintile, ranging from 4.4% in Rwanda to 44.6% in Zimbabwe. CONCLUSIONS: Cervical precancer screening rates were inequitable and low. No country surveyed achieved one-third of the WHO's target of screening 70% of eligible women by 2030. Combining inequalities led to high inequalities, preventing women who were younger, lived in rural areas, were uneducated, and from the lowest wealth quintile from screening. Governments should include and monitor equity in their cervical precancer screening programmes.

Socioeconomic inequalities in the 90-90-90 target, among people living with HIV in 12 sub-Saharan African countries - Implications for achieving the 95-95-95 target - Analysis of population-based surveys.

Background: Inequalities undermine efforts to end AIDS by 2030. We examined socioeconomic inequalities in the 90-90-90 target among people living with HIV (PLHIV) -men (MLHIV), women (WLHIV) and adolescents (ALHIV). Methods: We analysed the available Population HIV Impact Assessment (PHIA) survey data for each of the 12 sub-Saharan African countries, collected between 2015 and 2018 to estimate the attainment of each step of the 90-90-90 target by wealth quintiles. We constructed concentration curves, computed concentration indices (CIX) -a negative (positive) CIX indicated pro-poor (pro-rich) inequalities- and identified factors associated with, and contributing to inequality. Findings: Socioeconomic inequalities in achieving the 90-90-90 target components among PLHIV were noted in 11 of the 12 countries surveyed: not in Rwanda. Awareness of HIV positive status was pro-rich in 5/12 countries (Côte d'Ivoire, Tanzania, Uganda, Malawi, and Zambia) ranging from CIX=0·085 (p< 0·05) in Tanzania for PLHIV, to CIX = 0·378 (p<0·1) in Côte d'Ivoire for ALHIV. It was pro-poor in 5/12 countries (Côte d'Ivoire, Ethiopia, Malawi, Namibia and Eswatini), ranging from CIX = -0·076 (p<0·05) for PLHIV in Eswatini, and CIX = -0·192 (p<0·05) for WLHIV in Ethiopia. Inequalities in accessing ART were pro-rich in 5/12 countries (Cameroun, Tanzania, Uganda, Malawi and Zambia) ranging from CIX=0·101 (p<0·05) among PLHIV in Zambia to CIX=0·774 (p<0·1) among ALHIV in Cameroun and pro-poor in 4/12 countries (Tanzania, Zimbabwe, Lesotho and Eswatini), ranging from CIX = -0·072 (p<0·1) among PLHIV in Zimbabwe to CIX = -0·203 (p<0·05) among WLHIV in Tanzania. Inequalities in HIV viral load suppression were pro-rich in 3/12 countries (Ethiopia, Uganda, and Lesotho), ranging from CIX = 0·089 (p< 0·1) among PLHIV in Uganda to CIX = 0·275 (p<0·01) among WLHIV in Ethiopia. Three countries (Tanzania CIX = 0·069 (p< 0·5), Uganda CIX = 0·077 (p< 0·1), and Zambia CIX = 0·116 (p< 0·1)) reported pro-rich and three countries (Côte d'Ivoire CIX = -0·125 (p< 0·1), Namibia CIX = -0·076 (p< 0·05), and Eswatini CIX = -0·050 (p< 0·05) pro-poor inequalities for the cumulative CIX for HIV viral load suppression. The decomposition analysis showed that age, rural-urban residence, education, and wealth were associated with and contributed the most to inequalities observed in achieving the 90-90-90 target. Interpretation: Some PLHIV in 11 of 12 countries were not receiving life-saving HIV testing, treatment, or achieving HIV viral load suppression due to socioeconomic inequalities. Socioeconomic factors were associated with and explained the inequalities observed in the 90-90-90 target among PLHIV. Governments should scale up equitable 95-95-95 target interventions, prioritizing the reduction of age, rural-urban, education and wealth-related inequalities. Research is needed to understand interventions to reduce socioeconomic inequities in achieving the 95-95-95 target. Funding: This study was supported by the Swiss National Science Foundation (grant 202660).

Associations of Sustainable Development Goals Accelerators With Adolescents' Well-Being According to Head-of-Household's Disability Status-A Cross-Sectional Study From Zambia.

Objectives: We examined associations between accelerators (interventions impacting ≥2 SDG targets) and SDG-aligned well-being indicators among adolescents 16-24 years old in Zambia. Methods: We surveyed adults from 1,800 randomly sampled households receiving social cash transfers. We examined associations between accelerators (social cash transfers, life-long learning, mobile phone access) and seven well-being indicators among adolescents using multivariate logistic regressions. Results: The sample comprised 1,725 adolescents, 881 (51.1%) girls. Mobile phone access was associated with no poverty (adjusted Odds Ratio [aOR] 2.08, p < 0.001), informal cash transfers (aOR 1.82, p = 0.004), and seeking mental health support (aOR 1.61, p = 0.020). Social cash transfers were associated with no disability-related health restrictions (aOR 2.56, p = 0.004) and lesser odds of seeking mental health support (aOR 0.53, p = 0.029). Life-long learning was associated with informal cash transfers (aOR 3.49, p < 0.001) and lower school enrollment (aOR 0.70, p = 0.004). Adolescents with disabled head-of-household reported worse poverty, good health but less suicidal ideation. Conclusions: Social cash transfers, life-long learning, and mobile phone access were positively associated with well-being indicators. Adolescents living with disabled head-of-household benefited less. Governments should implement policies to correct disability-related inequalities.

Hepatitis C core antigen test as an alternative for diagnosing HCV infection: mathematical model and cost-effectiveness analysis.

BACKGROUND: The cost and complexity of the polymerase chain reaction (PCR) test are barriers to diagnosis and treatment of hepatitis C virus (HCV) infection. We investigated the cost-effectiveness of testing strategies using antigen instead of PCR testing. METHODS: We developed a mathematical model for HCV to estimate the number of diagnoses and cases of liver disease. We compared the following testing strategies: antibody test followed by PCR in case of positive antibody (baseline strategy); antibody test followed by HCV-antigen test (antibody-antigen); antigen test alone; PCR test alone. We conducted cost-effectiveness analyses considering either the costs of HCV testing of infected and uninfected individuals alone (A1), HCV testing and liver-related complications (A2), or all costs including HCV treatment (A3). The model was parameterized for the country of Georgia. We conducted several sensitivity analyses. RESULTS: The baseline scenario could detect 89% of infected individuals. Antibody-antigen detected 86% and antigen alone 88% of infected individuals. PCR testing alone detected 91% of the infected individuals: the remaining 9% either died or spontaneously recovered before testing. In analysis A1, the baseline strategy was not essentially more expensive than antibody-antigen. In analysis A2, strategies using PCR became cheaper than antigen-based strategies. In analysis A3, antibody-antigen was again the cheapest strategy, followed by the baseline strategy, and PCR testing alone. CONCLUSIONS: Antigen testing, either following a positive antibody test or alone, performed almost as well as the current practice of HCV testing. The cost-effectiveness of these strategies depends on the inclusion of treatment costs.

Developing evidenced-based quality assessment checklist for real practice in primary health care using standardized patients: a systematic review.

BACKGROUND: The aim of this review was to explore the quality assessment checklists development methods in previous researches using standardized patients (SPs), as well as to propose an evidence-based checklist development procedure for quality assessment of common conditions in primary health care (PHC) settings. METHODS: We conducted a systematic review of studies that described checklist development method and extracted the methodology in terms of the developer, the basis and processes. Based on that, we formulated the development procedure according to the recommendations of the WHO Handbook for Guideline Development. RESULTS: We identified a total of 13 articles, and proposed the following five key steps: (I) forming a multidisciplinary team; (II) selecting and evaluating relevant references; (III) extracting medical information and forming the basic items; (IV) clinical expert consensus on the items; and (V) pre-testing the item pool and determining final items. DISCUSSION: SP has been proven to be an effective method to assess performance in practice. There are still some deficiencies in the developing of case-specific checklists using SPs. To ensure the validity and reliability of checklists, the development processes need to be more standardized and procedural.

Cost-per-diagnosis as a metric for monitoring cost-effectiveness of HIV testing programmes in low-income settings in southern Africa: health economic and modelling analysis.

INTRODUCTION: As prevalence of undiagnosed HIV declines, it is unclear whether testing programmes will be cost-effective. To guide their HIV testing programmes, countries require appropriate metrics that can be measured. The cost-per-diagnosis is potentially a useful metric. METHODS: We simulated a series of setting-scenarios for adult HIV epidemics and ART programmes typical of settings in southern Africa using an individual-based model and projected forward from 2018 under two policies: (i) a minimum package of "core" testing (i.e. testing in pregnant women, for diagnosis of symptoms, in sex workers, and in men coming forward for circumcision) is conducted, and (ii) core-testing as above plus additional testing beyond this ("additional-testing"), for which we specify different rates of testing and various degrees to which those with HIV are more likely to test than those without HIV. We also considered a plausible range of unit test costs. The aim was to assess the relationship between cost-per-diagnosis and the incremental cost-effectiveness ratio (ICER) of the additional-testing policy. The discount rate used in the base case was 3% per annum (costs in 2018 U.S. dollars). RESULTS: There was a strong graded relationship between the cost-per-diagnosis and the ICER. Overall, the ICER was below $500 per-DALY-averted (the cost-effectiveness threshold used in primary analysis) so long as the cost-per-diagnosis was below $315. This threshold cost-per-diagnosis was similar according to epidemic and programmatic features including the prevalence of undiagnosed HIV, the HIV incidence and a measure of HIV programme quality (the proportion of HIV diagnosed people having a viral load <1000 copies/mL). However, restricting to women, additional-testing did not appear cost-effective even at a cost-per-diagnosis of below $50, while restricting to men additional-testing was cost-effective up to a cost-per-diagnosis of $585. The threshold cost per diagnosis for testing in men to be cost-effective fell to $256 when the cost-effectiveness threshold was $300 instead of $500, and to $81 when considering a discount rate of 10% per annum. CONCLUSIONS: For testing programmes in low-income settings in southern African there is an extremely strong relationship between the cost-per-diagnosis and the cost-per-DALY averted, indicating that the cost-per-diagnosis can be used to monitor the cost-effectiveness of testing programmes.

How should HIV resources be allocated? Lessons learnt from applying Optima HIV in 23 countries.

INTRODUCTION: With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS: Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION: The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS: Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

The global Optima HIV allocative efficiency model: targeting resources in efforts to end AIDS.

BACKGROUND: To move towards ending AIDS by 2030, HIV resources should be allocated cost-effectively. We used the Optima HIV model to estimate how global HIV resources could be retargeted for greatest epidemiological effect and how many additional new infections could be averted by 2030. METHODS: We collated standard data used in country modelling exercises (including demographic, epidemiological, behavioural, programmatic, and expenditure data) from Jan 1, 2000, to Dec 31, 2015 for 44 countries, capturing 80% of people living with HIV worldwide. These data were used to parameterise separate subnational and national models within the Optima HIV framework. To estimate optimal resource allocation at subnational, national, regional, and global levels, we used an adaptive stochastic descent optimisation algorithm in combination with the epidemic models and cost functions for each programme in each country. Optimal allocation analyses were done with international HIV funds remaining the same to each country and by redistributing these funds between countries. FINDINGS: Without additional funding, if countries were to optimally allocate their HIV resources from 2016 to 2030, we estimate that an additional 7·4 million (uncertainty range 3·9 million-14·0 million) new infections could be averted, representing a 26% (uncertainty range 13-50%) incidence reduction. Redistribution of international funds between countries could avert a further 1·9 million infections, which represents a 33% (uncertainty range 20-58%) incidence reduction overall. To reduce HIV incidence by 90% relative to 2010, we estimate that more than a three-fold increase of current annual funds will be necessary until 2030. The most common priorities for optimal resource reallocation are to scale up treatment and prevention programmes targeting key populations at greatest risk in each setting. Prioritisation of other HIV programmes depends on the epidemiology and cost-effectiveness of service delivery in each setting as well as resource availability. INTERPRETATION: Further reductions in global HIV incidence are possible through improved targeting of international and national HIV resources. FUNDING: World Bank and Australian NHMRC.

Reporting of declarations and conflicts of interest in WHO guidelines can be further improved.

OBJECTIVES: We aimed to examine the declaration of interests (DOIs), management of conflict of interest (COI), and the funders for World Health Organization (WHO) guidelines. STUDY DESIGN AND SETTING: We examined all Guidelines Review Committee (GRC)-approved WHO guidelines published in English from January 2007 (inception of the GRC) to November 2016. We obtained a list of all such guidelines from the GRC Secretariat. Characteristics of guidelines including funders and individual contributors' DOI were independently extracted by two researchers. Binary logistic regression was used to assess the association between declarations and the number of organizations involved in development. RESULTS: A total of 176 guidelines fulfilled inclusion criteria, encompassing 14 clinical or public health fields. Funders were reported in 128 (73%) of the guidelines: the most common were governments. DOI for external contributors were reported in 157 (89%) of the guidelines: 75 (48%) indicated no contributors with COI, 57 (36%) reported contributors with COI, and 25 (16%) reported collecting DOI but not whether COI existed. Financial COI were reported more frequently than nonfinancial COI. Of 57 guidelines that reported COI, 45 (79%) indicated how the COI were managed. CONCLUSION: The majority of WHO guidelines reported their funding sources and the DOI and COI of external contributors in their guideline documents. However, there is a need for improvement, in particular for reporting of funders and their role, declaration processes, and management of COI.

Getting it right when budgets are tight: Using optimal expansion pathways to prioritize responses to concentrated and mixed HIV epidemics.

BACKGROUND: Prioritizing investments across health interventions is complicated by the nonlinear relationship between intervention coverage and epidemiological outcomes. It can be difficult for countries to know which interventions to prioritize for greatest epidemiological impact, particularly when budgets are uncertain. METHODS: We examined four case studies of HIV epidemics in diverse settings, each with different characteristics. These case studies were based on public data available for Belarus, Peru, Togo, and Myanmar. The Optima HIV model and software package was used to estimate the optimal distribution of resources across interventions associated with a range of budget envelopes. We constructed "investment staircases", a useful tool for understanding investment priorities. These were used to estimate the best attainable cost-effectiveness of the response at each investment level. FINDINGS: We find that when budgets are very limited, the optimal HIV response consists of a smaller number of 'core' interventions. As budgets increase, those core interventions should first be scaled up, and then new interventions introduced. We estimate that the cost-effectiveness of HIV programming decreases as investment levels increase, but that the overall cost-effectiveness remains below GDP per capita. SIGNIFICANCE: It is important for HIV programming to respond effectively to the overall level of funding availability. The analytic tools presented here can help to guide program planners understand the most cost-effective HIV responses and plan for an uncertain future.

Comparative cost-effectiveness of Option B+ for prevention of mother-to-child transmission of HIV in Malawi.

OBJECTIVE: To estimate the cost-effectiveness of prevention of mother-to-child transmission (MTCT) of HIV with lifelong antiretroviral therapy (ART) for pregnant and breastfeeding women ('Option B+') compared with ART during pregnancy or breastfeeding only unless clinically indicated ('Option B'). DESIGN: Mathematical modelling study of first and second pregnancy, informed by data from the Malawi Option B+ programme. METHODS: Individual-based simulation model. We simulated cohorts of 10 000 women and their infants during two subsequent pregnancies, including the breastfeeding period, with either Option B+ or B. We parameterized the model with data from the literature and by analysing programmatic data. We compared total costs of antenatal and postnatal care, and lifetime costs and disability-adjusted life-years of the infected infants between Option B+ and Option B. RESULTS: During the first pregnancy, 15% of the infants born to HIV-infected mothers acquired the infection. With Option B+, 39% of the women were on ART at the beginning of the second pregnancy, compared with 18% with Option B. For second pregnancies, the rates MTCT were 11.3% with Option B+ and 12.3% with Option B. The incremental cost-effectiveness ratio comparing the two options ranged between about US$ 500 and US$ 1300 per DALY averted. CONCLUSION: Option B+ prevents more vertical transmissions of HIV than Option B, mainly because more women are already on ART at the beginning of the next pregnancy. Option B+ is a cost-effective strategy for PMTCT if the total future costs and lost lifetime of the infected infants are taken into account.

The cost-effectiveness of monitoring strategies for antiretroviral therapy of HIV infected patients in resource-limited settings: software tool.

BACKGROUND: The cost-effectiveness of routine viral load (VL) monitoring of HIV-infected patients on antiretroviral therapy (ART) depends on various factors that differ between settings and across time. Low-cost point-of-care (POC) tests for VL are in development and may make routine VL monitoring affordable in resource-limited settings. We developed a software tool to study the cost-effectiveness of switching to second-line ART with different monitoring strategies, and focused on POC-VL monitoring. METHODS: We used a mathematical model to simulate cohorts of patients from start of ART until death. We modeled 13 strategies (no 2nd-line, clinical, CD4 (with or without targeted VL), POC-VL, and laboratory-based VL monitoring, with different frequencies). We included a scenario with identical failure rates across strategies, and one in which routine VL monitoring reduces the risk of failure. We compared lifetime costs and averted disability-adjusted life-years (DALYs). We calculated incremental cost-effectiveness ratios (ICER). We developed an Excel tool to update the results of the model for varying unit costs and cohort characteristics, and conducted several sensitivity analyses varying the input costs. RESULTS: Introducing 2nd-line ART had an ICER of US$1651-1766/DALY averted. Compared with clinical monitoring, the ICER of CD4 monitoring was US$1896-US$5488/DALY averted and VL monitoring US$951-US$5813/DALY averted. We found no difference between POC- and laboratory-based VL monitoring, except for the highest measurement frequency (every 6 months), where laboratory-based testing was more effective. Targeted VL monitoring was on the cost-effectiveness frontier only if the difference between 1st- and 2nd-line costs remained large, and if we assumed that routine VL monitoring does not prevent failure. CONCLUSION: Compared with the less expensive strategies, the cost-effectiveness of routine VL monitoring essentially depends on the cost of 2nd-line ART. Our Excel tool is useful for determining optimal monitoring strategies for specific settings, with specific sex-and age-distributions and unit costs.

Active surveillance for rheumatic heart disease in endemic regions: a systematic review and meta-analysis of prevalence among children and adolescents.

BACKGROUND: Rheumatic heart disease accounts for up to 250 000 premature deaths every year worldwide and can be regarded as a physical manifestation of poverty and social inequality. We aimed to estimate the prevalence of rheumatic heart disease in endemic countries as assessed by different screening modalities and as a function of age. METHODS: We searched Medline, Embase, the Latin American and Caribbean System on Health Sciences Information, African Journals Online, and the Cochrane Database of Systematic Reviews for population-based studies published between Jan 1, 1993, and June 30, 2014, that reported on prevalence of rheumatic heart disease among children and adolescents (≥ 5 years to <18 years). We assessed prevalence of clinically silent and clinically manifest rheumatic heart disease in random effects meta-analyses according to screening modality and geographical region. We assessed the association between social inequality and rheumatic heart disease with the Gini coefficient. We used Poisson regression to analyse the effect of age on prevalence of rheumatic heart disease and estimated the incidence of rheumatic heart disease from prevalence data. FINDINGS: We included 37 populations in the systematic review and meta-analysis. The pooled prevalence of rheumatic heart disease detected by cardiac auscultation was 2·9 per 1000 people (95% CI 1·7-5·0) and by echocardiography it was 12·9 per 1000 people (8·9-18·6), with substantial heterogeneity between individual reports for both screening modalities (I² = 99·0% and 94·9%, respectively). We noted an association between social inequality expressed by the Gini coefficient and prevalence of rheumatic heart disease (p = 0·0002). The prevalence of clinically silent rheumatic heart disease (21·1 per 1000 people, 95% CI 14·1-31·4) was about seven to eight times higher than that of clinically manifest disease (2·7 per 1000 people, 1·6-4·4). Prevalence progressively increased with advancing age, from 4·7 per 1000 people (95% CI 0·0-11·2) at age 5 years to 21·0 per 1000 people (6·8-35·1) at 16 years. The estimated incidence was 1·6 per 1000 people (0·8-2·3) and remained constant across age categories (range 2·5, 95% CI 1·3-3·7 in 5-year-old children to 1·7, 0·0-5·1 in 15-year-old adolescents). We noted no sex-related differences in prevalence (p = 0·829).

Cost-effectiveness of different strategies to monitor adults on antiretroviral treatment: a combined analysis of three mathematical models.

BACKGROUND: WHO's 2013 revisions to its Consolidated Guidelines on antiretroviral drugs recommend routine viral load monitoring, rather than clinical or immunological monitoring, as the preferred monitoring approach on the basis of clinical evidence. However, HIV programmes in resource-limited settings require guidance on the most cost-effective use of resources in view of other competing priorities such as expansion of antiretroviral therapy coverage. We assessed the cost-effectiveness of alternative patient monitoring strategies. METHODS: We evaluated a range of monitoring strategies, including clinical, CD4 cell count, and viral load monitoring, alone and together, at different frequencies and with different criteria for switching to second-line therapies. We used three independently constructed and validated models simultaneously. We estimated costs on the basis of resource use projected in the models and associated unit costs; we quantified impact as disability-adjusted life years (DALYs) averted. We compared alternatives using incremental cost-effectiveness analysis. FINDINGS: All models show that clinical monitoring delivers significant benefit compared with a hypothetical baseline scenario with no monitoring or switching. Regular CD4 cell count monitoring confers a benefit over clinical monitoring alone, at an incremental cost that makes it affordable in more settings than viral load monitoring, which is currently more expensive. Viral load monitoring without CD4 cell count every 6-12 months provides the greatest reductions in morbidity and mortality, but incurs a high cost per DALY averted, resulting in lost opportunities to generate health gains if implemented instead of increasing antiretroviral therapy coverage or expanding antiretroviral therapy eligibility. INTERPRETATION: The priority for HIV programmes should be to expand antiretroviral therapy coverage, firstly at CD4 cell count lower than 350 cells per µL, and then at a CD4 cell count lower than 500 cells per µL, using lower-cost clinical or CD4 monitoring. At current costs, viral load monitoring should be considered only after high antiretroviral therapy coverage has been achieved. Point-of-care technologies and other factors reducing costs might make viral load monitoring more affordable in future. FUNDING: Bill & Melinda Gates Foundation, WHO.

Cost-effectiveness of point-of-care viral load monitoring of antiretroviral therapy in resource-limited settings: mathematical modelling study.

BACKGROUND: Monitoring of HIV viral load in patients on combination antiretroviral therapy (ART) is not generally available in resource-limited settings. We examined the cost-effectiveness of qualitative point-of-care viral load tests (POC-VL) in sub-Saharan Africa. DESIGN: Mathematical model based on longitudinal data from the Gugulethu and Khayelitsha township ART programmes in Cape Town, South Africa. METHODS: Cohorts of patients on ART monitored by POC-VL, CD4 cell count or clinically were simulated. Scenario A considered the more accurate detection of treatment failure with POC-VL only, and scenario B also considered the effect on HIV transmission. Scenario C further assumed that the risk of virologic failure is halved with POC-VL due to improved adherence. We estimated the change in costs per quality-adjusted life-year gained (incremental cost-effectiveness ratios, ICERs) of POC-VL compared with CD4 and clinical monitoring. RESULTS: POC-VL tests with detection limits less than 1000 copies/ml increased costs due to unnecessary switches to second-line ART, without improving survival. Assuming POC-VL unit costs between US$5 and US$20 and detection limits between 1000 and 10,000 copies/ml, the ICER of POC-VL was US$4010-US$9230 compared with clinical and US$5960-US$25540 compared with CD4 cell count monitoring. In Scenario B, the corresponding ICERs were US$2450-US$5830 and US$2230-US$10380. In Scenario C, the ICER ranged between US$960 and US$2500 compared with clinical monitoring and between cost-saving and US$2460 compared with CD4 monitoring. CONCLUSION: The cost-effectiveness of POC-VL for monitoring ART is improved by a higher detection limit, by taking the reduction in new HIV infections into account and assuming that failure of first-line ART is reduced due to targeted adherence counselling.

Retention in care of HIV-infected children from HIV test to start of antiretroviral therapy: systematic review.

BACKGROUND: In adults it is well documented that there are substantial losses to the programme between HIV testing and start of antiretroviral therapy (ART). The magnitude and reasons for loss to follow-up and death between HIV diagnosis and start of ART in children are not well defined. METHODS: We searched the PubMed and EMBASE databases for studies on children followed between HIV diagnosis and start of ART in low-income settings. We examined the proportion of children with a CD4 cell count/percentage after after being diagnosed with HIV infection, the number of treatment-eligible children starting ART and predictors of loss to programme. Data were extracted in duplicate. RESULTS: Eight studies from sub-Saharan Africa and two studies from Asia with a total of 10,741 children were included. Median age ranged from 2.2 to 6.5 years. Between 78.0 and 97.0% of HIV-infected children subsequently had a CD4 cell count/percentage measured, 63.2 to 90.7% of children with an eligibility assessment met the eligibility criteria for the particular setting and time and 39.5 to 99.4% of the eligible children started ART. Three studies reported an association between low CD4 count/percentage and ART initiation while no association was reported for gender. Only two studies reported on pre-ART mortality and found rates of 13 and 6 per 100 person-years. CONCLUSION: Most children who presented for HIV care met eligibility criteria for ART. There is an urgent need for strategies to improve the access to and retention to care of HIV-infected children in resource-limited settings.

Loss to programme between HIV diagnosis and initiation of antiretroviral therapy in sub-Saharan Africa: systematic review and meta-analysis.

OBJECTIVES: To assess the proportion of patients lost to programme (died, lost to follow-up, transferred out) between HIV diagnosis and start of antiretroviral therapy (ART) in sub-Saharan Africa, and determine factors associated with loss to programme. METHODS: Systematic review and meta-analysis. We searched PubMed and EMBASE databases for studies in adults. Outcomes were the percentage of patients dying before starting ART, the percentage lost to follow-up, the percentage with a CD4 cell count, the distribution of first CD4 counts and the percentage of eligible patients starting ART. Data were combined using random-effects meta-analysis. RESULTS: Twenty-nine studies from sub-Saharan Africa including 148,912 patients were analysed. Six studies covered the whole period from HIV diagnosis to ART start. Meta-analysis of these studies showed that of the 100 patients with a positive HIV test, 72 (95% CI 60-84) had a CD4 cell count measured, 40 (95% CI 26-55) were eligible for ART and 25 (95% CI 13-37) started ART. There was substantial heterogeneity between studies (P < 0.0001). Median CD4 cell count at presentation ranged from 154 to 274 cells/µl. Patients eligible for ART were less likely to become lost to programme (25%vs. 54%, P < 0.0001), but eligible patients were more likely to die (11%vs. 5%, P < 0.0001) than ineligible patients. Loss to programme was higher in men, in patients with low CD4 cell counts and low socio-economic status and in recent time periods. CONCLUSIONS: Monitoring and care in the pre-ART time period need improvement, with greater emphasis on patients not yet eligible for ART.

Mortality and loss to follow-up in the first year of ART: Malawi national ART programme.

OBJECTIVES: To analyse mortality, loss to follow-up (LTFU) and retention on antiretroviral treatment (ART) in the first year of ART across all age groups in the Malawi national ART programme. DESIGN: Cohort study including all patients who started ART in Malawi's public sector clinics between 2004 and 2007. METHODS: ART registers were photographed, information entered into a database and merged with data from clinics with electronic records. Rates per 100 patient-years and cumulative incidence of retention were calculated. Subhazard ratios (sHRs) of outcomes adjusted for patient and clinic-level characteristics were calculated in multivariable analysis, applying competing risk models. RESULTS: A total of 117,945 patients contributed 85,246 person-years: 1.0% were infants below 2 years, 7.4% children 2-14, 7.5% young people 15-24, and 84.2% adults 25 years and above. Sixty percent of patients were female: women outnumbered men from age 14 to 35 years. Mortality and LTFU were higher in men from age 20 years. Infants and young people had the highest rates per 100 person-years for mortality (23.0 and 19.4) and LTFU (24.7 and 19.3), and the highest adjusted relative risks compared to age group 25-34 years: sHRs were 1.37 [95% confidence interval (CI) 1.17-1.60] and 1.17 (95% CI 1.10-1.25) for death and 1.37 (95% CI 1.18-1.59) and 1.27 (95% CI 1.19-1.35) for LTFU, respectively. CONCLUSION: In this country-wide study patients aged 0-1 and 15-24 years had the highest risk of death and LTFU, and from age 20 men were at higher risk than women. Interventions to improve outcomes in these patient groups are required.