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Cost-effectiveness of laboratory monitoring in sub Saharan Africa: a review of the current literature
Global Health Sciences Literature Digest
Published December 13, 2010
Journal Article

Walensky RP, Ciaranello AL, Park JE, et al. Cost-effectiveness of laboratory monitoring in sub Saharan Africa: a review of the current literature. Clin Infect Dis. 2010 Jul 1;51(1):85-92.

Study Design

An evaluation of five published studies of cost-effectiveness analyses examining the value of CD4 cell count and viral load monitoring.(1, 2, 3, 4, 5)

In Context

There is controversy regarding the value of CD4 cell count and viral load monitoring in managing HIV disease in resource-limited countries; national treatment guidelines differ from WHO guidelines to reflect locally available resources. The World Health Organization (WHO) is now relying more on cost-effectiveness analyses to inform guidelines. (6, 7) The multi-site African DART trial found that quarterly CD4 cell count monitoring with other basic lab tests provided only modest survival benefits compared to clinical monitoring alone(8) although a preliminary CEA from this study suggests that CD4 cell count alone (without other lab tests) may be cost effective. (9, 10)


To describe the use of cost-effectiveness analysis (CEA); to review the cost-effectiveness literature regarding monitoring of CD4 cells counts and HIV RNA levels to inform antiretroviral therapy (ART) initiation and regimen switching in Africa.


Data from CEA performed in Côte d'Ivoire, Kenya, Zimbabwe, Botswana, South Africa, and other lower income countries in sub-Saharan Africa (not specified in the article).


HIV-infected persons eligible for, or on ART.


The authors define cost-effectiveness analysis, a formal methodology that includes costs (current and future), and effectiveness (short and long-term), either per person or as a total amount for a defined population. Effectiveness is quantified as years of life saved (YLS), or as quality-adjusted life-years saved (QALY). Quality of life 'weights' are assigned to health conditions so that each year of imperfect health is worth less than one year of perfect health. Incremental cost-effectiveness ratios (ICER) (difference in costs divided by differences in effectiveness) are calculated to compare different strategies. Strategies that cost more but produce fewer YLS or QALYs are economically irrational and were not considered; strategies that have higher cost-effectiveness ratios than less expensive and less effective interventions were considered economically inefficient and eliminated from comparisons. WHO suggests that a country's per capita Gross Domestic Product (GDP) should guide whether an intervention is affordable;(6) interventions are considered highly cost effective if their ratios are less than the per capita GDP, and cost effective if their ratios are less than three times the GDP.

Five published (2006-2008) model-based CEA were evaluated, and only included strategies relevant to the question of laboratory monitoring for the purpose of ART initiation and switching. Calculations made in each study were repeated using conventional cost-effectiveness strategies. To enable comparison across studies, all cost-effectiveness results were expressed in per-person costs and benefits, with ratios updated to 2007 US dollars.


Across studies, standardized costs of CD4 cell count tests varied from $5 to $31 (all dollar amounts given in USD); costs per HIV RNA test ranged between $26 to $92; annual first-line ART costs ranged from $130 to $429; second line ART ranged from $640 to $1432, annually. Across studies, the extended life expectancy resulting from using HIV RNA monitoring compared to CD4 cell monitoring was only a few months, although the differences in per person lifetime costs for CD4 versus viral load monitoring varied between $500 and $1000. Laboratory monitoring generally resulted in an expedited switch to a more expensive second-line ART regimen; ART regimen costs, rather than the laboratory tests costs themselves being the primary determinants of total costs. In a study from Côte d'Ivoire(1) the incremental cost effectiveness ratio of CD4 cell monitoring compared to clinical monitoring was $1140 per YLS, or cost effective for this country (GDP=1000). In another study from 3 countries,(2) CD4 cell monitoring compared to clinical monitoring had a ICER of $640 per QALY for first line ART and $5960 per QALY when second line ART is available (cost effective for Botswana, but exceeding GDP thresholds for Kenya and Zimbabwe). Compared with CD4 cell monitoring, the ICER for viral load monitoring was $16,860 per QALY (first line ART only), and $15,250 per QALY (when second line ART available). In a study from South Africa,(3) a 'developed world strategy' of initiating ART at CD4<350 cells/µl with CD4 and HIV RNA monitoring every 3 months, compared to ART initiation at CD4< 200 cells/µl with CD4 cell monitoring every 6 months, resulted in an ICER of $5780 per LYS, very cost effective for SA (GDP=5900). In a study by Phillips et al(4), laboratory monitoring was considered for switching only, and not for ART initiation. Switching based on HIV RNA monitoring compared to switching based on a new WHO stage 3 or 4 event (no CD4 cell count strategy), had a CER of $3610 per QALY (cost effective for Zambia and Côte d'Ivoire, and highly cost effective for South Africa and Botswana). In a study from southern Africa,(5) compared to initiation at CD4 count <200 cells/µl and biannual CD4 monitoring: the ICER of ART initiation at CD4 count <350 cells/µl was $90 per YLS; the ICER for biannual CD4 cell and HIV RNA monitoring was $4140 per YLS; and the ICER for using quarterly CD4 and HIV RNA monitoring was $124,000 per YLS.


The authors conclude that cost effectiveness analysis can be a critical tool in understanding the value of various laboratory monitoring strategies in resource poor settings. The published studies evaluated here suggest that CD4 cell count monitoring is likely to be cost-effective in many settings, while viral load monitoring might be cost-effective, depending on ART and laboratory costs, and available resources.

Quality Rating

This study attempted to standardize comparisons across studies but was limited by the fact that different monitoring strategies were evaluated in each study. Not all studies reported how their costs were derived. Costs of the initial investment in laboratory infrastructure, maintenance and health information systems were not included.

Programmatic Implications

These results are somewhat difficult to interpret because of the wide variation in the relative costs and cost-effectiveness of strategies between countries and studies. In these studies, however, it appears that using viral load monitoring does not add significant months of life compared to CD4 cell count monitoring, and is not cost effective in resource poor settings. Only in more comparatively resource rich countries such as Botswana and South Africa, and by comparison to per capita GDP, does the use of RNA monitoring appear to be cost effective. CD4 cell monitoring compared to clinical monitoring is likely to be cost effective even in the poorest countries. These results should be interpreted with caution, however, as the number of studies were few, they were not performed similarly across sites, and input costs varied significantly.


  1. Goldie SJ, Yazdanpanah Y, Losina E, et al. Cost-effectiveness of HIV treatment in resource-poor settings-the case of Côte d'Ivoire. N Engl J Med 2006; 355:1141-1153.
  2. Bishai D, Colchero A, Durack DT. The cost effectiveness of antiretroviral treatment strategies in resource-limited settings. AIDS 2007; 21:1333-1140.
  3. Vijayaraghavan A, Efrusy MB, Mazonson PD, Ebrahim O, Sanne IM, Santas CC. Cost-effectiveness of alternative strategies for initiating and monitoring highly active antiretroviral therapy in the developing world. J Acquir Immune Defic Syndr 2007; 46:91-100.
  4. Phillips AN, Pillay D, Miners AH, Bennett DE, Gilks CF, Lundgren JD. Outcomes from monitoring of patients on antiretroviral therapy in resource-limited settings with viral load, CD4 cell count, or clinical observation alone: a computer simulation model. Lancet 2008; 371:1443-1451.
  5. Bendavid E, Young SD, Katzenstein DA, Bayoumi AM, Sanders GD, Owens DK. Cost-effectiveness of HIV monitoring strategies in resource-limited settings: a southern African analysis. Arch Intern Med 2008; 168:1910-1918.
  6. World Health Organization. Choosing interventions that are cost effective: cost-effectiveness thresholds. 2005. Accessed 18 November 2009.
  7. World Health Organization. Rapid advice: antiretroviral therapy for HIV infection in adults and adolescents. 2009. Accessed 3 December 2009.
  8. Mugyenyi P, Walker AS, Hakim J, et al. Routine versus clinically driven laboratory monitoring of HIV antiretroviral therapy in Africa (DART): a randomised non-inferiority trial. Lancet 2010; 375:123-131.
  9. Medina Lara A, Kigozi J, Amurwon J, et al. Cost effectiveness analysis of routine laboratory or clinically driven strategies for monitoring antiretroviral therapy in Uganda and Zimbabwe (DART Trial) In: Program and abstracts of the 5th International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention (Cape Town, South Africa). Geneva: International AIDS Society, 2009. Abstract TUSS103.
  10. Gilks CF. Cost effectiveness analysis of routine laboratory or clinically driven strategies for monitoring anti-retroviral therapy in Uganda and Zimbabwe. In: Program and abstracts of the 5th International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention (Cape Town, South Africa). Geneva: International AIDS Society, 2009.