Individuals become infected with HIV at the given incidence rate but remain undiagnosed until testing. HIV disease progression is modeled by changes in CD4 counts with associated changes in quality-of-life values and mortality rates over time. The base case scenario assumes a median time from seroconversion to AIDS of 10.3 years and a 10-year cumulative mortality of 39%.44-49
Testing frequencies range from retesting every 3 months to one test after 30 years (Table 1). To avoid biases resulting from different lengths of follow-up after the last test, testing frequencies were chosen such that the last test for all strategies takes place 30 years after the start of the model. To compare the relative cost-effectiveness of each strategy, all individuals tested according to the given frequencies (see Appendix, Supplemental Digital Content 1, http://links.lww.com/QAI/A144). HIV tests were assumed to be rapid, point-of-care tests and have 100% sensitivity and specificity. Individuals testing seronegative continue to test at the specified frequency; individuals testing seropositive do not retest but are linked to care and then started on first-line highly active antiretroviral therapy (HAART) if the CD4 count is 350 cells/mm3 or less.50 After initiating HAART, a person may be lost to follow-up at a rate of 10% per year (range, 5-20% yearly in sensitivity analysis).51 Following HAART initiation and virologic suppression, a patient's CD4 count gradually increases as a function of the CD4 count at the start of HAART.29,52,53 Failure rates and mortality on first- and second-line HAART were assumed to be greatest immediately after initiation of HAART.54-58 It was assumed to take 6 months for virologic failure to be detected and patients to be switched to second-line HAART. To avoid unrealistic increases of CD4, CD4 counts were assumed to remain constant during effective second-line therapy in the base case; the effect of this assumption was explored in sensitivity analysis (see Appendix, Supplemental Digital Content 1, http://links.lww.com/QAI/A144). During nonsuppressive therapy, CD4 counts were assumed to drop again. Patients failing second-line therapy are kept on nonsuppressive therapy, consistent with guidelines.50,59,60
With the most substantial increase in persons on HAART likely to occur in South Africa,21 costs for HAART therapy were derived for the drug regimens indicated by the South Africa 2010 guidelines for patients newly starting therapy, tenofovir + emtracitabine/lamivudine + efavirenz/nevirapine, and averaging the costs for the four possible regimens.61 Costs were similarly modeled for a second-line therapy of zidovudine + lamivudine + ritonavir-boosted lopinavir, consistent with the same guidelines. HCT cost per tester, laboratory costs, cost of prophylaxis for opportunistic infections, and cost per person for treatment of opportunistic infections were derived from studies in sub-Saharan Africa.62,63 Costs for healthcare facilities overhead, salaries of healthcare workers, and costs to the patient for time spent obtaining care are not explicitly included in the model, although significantly higher costs for HAART-where overhead costs can be implicit-were explored in the sensitivity analysis.
The quality-of-life value for HIV-uninfected persons was assumed to be 1. Quality-of-life values (Table 1) for an HIV-infected individual were assumed to be dependent on CD4 counts: CD4 <200, 200-349, and ≥350 cells/mm3 with values of 0.70, 0.82, and 0.94, respectively.64 Table 1 shows the base-case and sensitivity analysis values used.
Differential transmission rates were modeled for the acute, subacute (2-9 months following infection), chronic, and AIDS phases. Because it was assumed that a test for HIV is 100% sensitive and specific, it was also assumed that any diagnosis of HIV occurs after the acute phase. Combined with the mortality estimates for untreated and undiagnosed HIV disease, the base-case transmission rates, shown in Table 1, result in an undiscounted lifetime average of 0.94 infections per HIV-infected person per lifetime.8,65 Rates of HIV transmission were assumed to decline by 20% in the base-case scenario (range, 0-50% in sensitivity analysis) if an individual is aware of his or her HIV-infected status, a conservative estimate based on several studies in sub-Saharan Africa and the United States.66-70
Comprehensive sensitivity analyses for each of the three incidence scenarios evaluated the effect of alternative assumptions for the model input parameters. For each variation of a single input parameter, the most cost-effective testing strategy was identified and compared with that of the base-case scenario. The sensitivity of the primary outcome of cost per QALY to a 1% change in each input parameter was also evaluated. The sensitivity of the results to downstream infections prevented due to testing and treatment in the primary cohort was studied by taking into account tertiary in addition to secondary infections averted.
In low-risk environments, the most cost-effective testing frequency was testing every 7.5 years (Table 2). The total cost per QALY gained from this testing frequency was $998. When cost savings and QALYs gained from preventing secondary HIV infections were taken into account, the overall cost per QALY gained was $701. For testing every 7.5 years, the total cost per HIV-infected case identified was $2030. Of the total cost, 4.5%, 68.1%, and 27.3% were from HCT costs, HAART costs, and laboratory costs, respectively.
In a medium-risk environment, the most cost-effective testing frequency was every 6 years with a total cost per QALY gained of $977. Factoring in benefits derived from transmission reductions resulted in testing every 5 years being most cost-effective with a total cost per QALY gained of $681 (Table 2). The cost per HIV-infected case identified for this testing frequency was $2123. Of the intervention cost, 4.0%, 68.5%, and 27.4% were from HCT costs, HAART costs, and laboratory costs, respectively.
In a high-risk environment, testing every 5 years was most cost-effective with a cost per QALY of $942. Including secondary infections averted into the analysis resulted in testing ever 2 years being the most cost-effective strategy with a total cost per QALY gained of $635. For this frequency, cost per HIV-infected case identified was $2325 with 3.2%, 69.2%, and 27.6% of the total cost from HCT costs, HAART costs, and laboratory costs, respectively. Annual testing and testing every 6 months resulted in incremental cost-effectiveness ratios of $833/QALY and $1899/QALY gained, respectively, when compared with the next least effective strategy and when benefits from secondary infections averted are accounted for.
Without testing, counseling, diagnosis, or treatment, the average number of undiscounted secondary infections per HIV-infected individual is 0.94 for the base-case scenarios. Values for reproductive numbers greater than 1.0 were assessed in the sensitivity analysis. Reductions in rates of HIV transmission resulting from testing, counseling, and treatment ranged from 5.4% (testing once after 30 years, 4.0% incidence) to 26.3% (testing every 3 months, 0.8% incidence). The percent reduction in transmission of HIV for each testing scenario is shown in Table 2.
Using a mathematical model, we compared alternative retesting strategies for HIV with best estimates for input parameters from sub-Saharan Africa. Expectedly, the most cost-effective testing frequency depended on the risk environment, with higher risk indicating more frequent testing.
Our sensitivity analysis shows that the most cost-effective strategy can vary substantially with changes in the input parameters. HCT cost, assumptions about the effect of a seropositive diagnosis on HIV transmission, and the cost of first-line HAART had the greatest effects across risk settings; rates of linkage to care, rates of CD4 count decline for untreated HIV, assumptions about quality-of-life values, rates of HIV transmission for untreated HIV, and cost of second-line HAART altered the optimal testing strategy for some risk scenarios.
The results for the high-risk scenario approximate the recommendation for annual testing for high-risk individuals recently released from the World Health Organization,29 particularly if the cost of HCT per tester can be minimized and certainly in settings where the epidemic is rapidly growing, where including tertiary infections averted into the analysis is reasonable. The World Health Organization guidelines also discourage retesting for individuals who have no new exposure after a seronegative HIV test. However, knowing that no new exposure occurred may be difficult in the setting of a generalized epidemic, particularly for married women.13-16 In such circumstances, our results suggest that even populations of lower risk would benefit from continuing to retest for HIV.
Aside from uncertainties introduced by the input parameters, our model has several structural limitations and could be extended in several ways. Behavior change associated with HCT for seronegative testers, for which there is mixed evidence,3,71 would alter our cost-effectiveness estimates. Including a background of ongoing symptom-based case identification or exposure-related self-initiated testing at interim time points would affect the cost-effectiveness of the strategies as would allowing a mechanism for those who are lost to follow-up to later return to care. Treatment side effects and development of resistant strains that alter the effectiveness of available HAART options are not currently modeled. False-positive and false-negative test results are not taken into account, which would gain importance at more frequent testing intervals. Although studies have shown that CD4 counts at seroconversion vary with age, sex, and exposure group,44,45 and that rates of CD4 decline vary significantly with HIV-1 subtype,45 these factors were not included in the model and would be pertinent for certain subpopulations of testers. Although costs for healthcare personnel and overhead were not built into the model, these costs can be absorbed into the treatment costs, higher costs of which are studied in the sensitivity analysis. An extension of the model to incorporate these factors as well as modeling of disease progression and cost at the individual rather than cohort level is required for a comprehensive cost-effectiveness analysis of retesting strategies. Given the large number of assumptions and the structural limitations of the model, the specific results presented here and the precise values of estimates should be interpreted with caution. However, the broad trends observed in these data relating to higher risk populations meriting more frequent testing and the benefits of retesting even in lower risk populations are likely to be robust.
For our findings to provide guidance, policymakers need to understand variations in local HIV incidence rates and resource availability to select optimal testing strategies. This includes differential rates of HIV infection in population subgroups and an understanding of the cost and uptake of alternative HCT options such as provider-initiated testing, mobile HCT, fixed-venue HCT, and home-based testing. Selection biases associated with seeking HIV testing and variation in the cost per test have the potential to greatly influence the relative cost-effectiveness of each strategy in different venues. With limited resources, there is also a need to balance retesting against the more pressing need to detect as yet undiagnosed prevalent cases. Although guidelines on retesting can assist clients already presenting for HIV testing, significant obstacles remain in decreasing stigma and promoting uptake of HIV testing by those who have yet to ever test.13 Care also needs to be taken to ensure that HIV retesting recommendations do not present testing barriers for individuals who merit more frequent testing.
Although our model is theoretical, it has direct implications for HIV testing and treatment policy and practice. The results suggest substantial benefits from periodic retesting for HIV even for groups other than high-risk populations. These findings also show substantial savings in cost and QALYs from reduced HIV transmission as a result of periodic retesting and linkage to care, consistent with the paradigm of treatment as prevention.10-12 Recognizing the need for most sexually active adults, as opposed to only certain risk groups, to retest for HIV at regular intervals may help to decrease stigma and normalize HIV testing if testing is no longer viewed as “acknowledgement of bad behavior,” a reason that keeps some individuals from ever testing.72,73 Further work in this area and the convergence of several models on similar outcomes as presented here would provide more robust evidence in support of the adoption of guidelines for HIV retesting for lower-risk populations to complement those currently in place for higher-risk populations.
We gratefully acknowledge the Hubert-Yeargan Center for Global Health for critical infrastructure support for the Kilimanjaro Christian Medical Centre-Duke University collaboration.
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