What Will It Take to Reduce HIV Incidence in the United States: A Mathematical Modeling Analysis

What Will It Take to Reduce HIV Incidence in the United States: A Mathematical Modeling Analysis Open Forum Infectious Diseases MAJOR ARTICLE What Will It Take to Reduce HIV Incidence in the United States: A Mathematical Modeling Analysis 1 1 1 2 Allison Perry, Parastu Kasaie, David W. Dowdy, and Maunank Shah 1 2 Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Johns Hopkins University School of Medicine, Baltimore, Maryland Background. e N Th ational HIV/AIDS Strategy has set ambitious goals to improve the epidemic in the United States. However, there is a paucity of usable program-level benchmarks tied to population-level epidemiologic goals. Our objective was to define tangible benchmarks for annual rates along the care continuum that are likely to translate to meaningful reductions in incidence. Methods. We used a validated mathematical model of HIV transmission and care engagement to characterize care continuum parameters that would translate into 50% reductions in incidence by 2025, compared with a base case scenario of the current US care continuum. We generated a large pool of simulations in which rates of screening, linkage, and retention in care were varied across wide ranges to evaluate permutations that halved incidence by 2025. Results. Among all simulations, 7% achieved a halving of incidence. It was impossible for our simulations to achieve this target if the annual rate of disengagement from care exceeded 20% per year, even at high rates of care reengagement. When retention in care was 95% per year and people living with HIV (PLWH) out of care reengaged within 1.5 years (on average), the probability of halving incidence by 2025 was approximately 90%. Conclusions. HIV programs should aim to retain at least 95% of PLWH in care annually and reengage people living with HIV into care within an average of 1.5 years to achieve the goal of halving HIV incidence by 2025. Keywords. HIV care-continuum; HIV/AIDS; linkage to care; retention in care; mathematical model; economics. Since the beginning of the epidemic, more than 1.2 million peo- for high-risk groups [9]. Nevertheless, research suggests that ple in the United States have received an AIDS diagnosis, and sustained engagement of PLWH in care is a critical factor for more than 700 000 people have died [1, 2]. There are currently both improved individual health and prevention of further HIV an estimated 1.1 million persons aged 13 years and older living transmission [9–12]. with HIV (PLWH) in the United States, with some estimates In response to the ongoing HIV epidemic, the National suggesting that less than 50% are retained in care [2–4]. Despite HIV/AIDS Strategy (NHAS) was recently updated in 2015 improvements in antiretroviral therapy (ART) and evidence [13]. Among the key components was enumeration of cross- for treatment as prevention with guidance for early ART initia- sectional population-level targets for care engagement and tion, incidence of HIV has declined at a slow rate and remains improvements in incidence [13]. Our group has previously uti-     between 36 000 and 39 000 new HIV infections per year [4–7]. lized a mathematical modeling approach to evaluate whether Among the challenges is an imperfect HIV care continuum, in achievement of these NHAS care continuum targets was likely which current national estimates suggest that suboptimal num- to achieve sustained reductions in transmission. The studies bers of PLWH are virologically suppressed, representing missed found that failure to improve engagement in HIV care leads to opportunities for averting ongoing HIV transmission [8]. excess infections, treatment costs, and deaths, and that interven- Each step along the HIV care cascade, from diagnosis to tions must improve not just HIV screening but also retention in engagement in HIV care and long-term ART adherence, must care to optimize epidemiologic impact and cost-effectiveness be strengthened [9]. There has been widespread focus on testing [9, 11]. Nonetheless, care continuum targets (ie, increasing the and initiation of treatment, with efforts to scale-up HIV testing percentage of persons with diagnosed HIV infection who are retained in HIV medical care to at least 90%) have not been quantitatively linked to stated epidemiological goals, and many Received 9 September 2017; editorial decision 23 December 2017; accepted 5 January 2018. continue to remain aspirational. Moreover, such cross-sectional Correspondence: A.  Perry, MHS, 71 Barnyard Lane, Roslyn Heights, NY 11577 (allison. goals are not easily translated into objective metrics that HIV perry23@gmail.com) program managers can utilize to assess success in their own Open Forum Infectious Diseases © The Author(s) 2018. Published by Oxford University Press on behalf of Infectious Diseases programs on an ongoing basis [9, 11]. Society of America. This is an Open Access article distributed under the terms of the Creative In this study, we aimed to define the standards of care engage- Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/ by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any ment along the full spectrum of the HIV care continuum that medium, provided the original work is not altered or transformed in any way, and that the work would be necessary to “bend the curve” of the HIV epidemic is properly cited. For commercial re-use, please contact journals.permissions@oup.com DOI: 10.1093/ofid/ofy008 in the United States. We sought to determine the annual rates Achieving NHAS Targets in the United States • OFID • 1 Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 of screening, retention, and reengagement in care, and the per- and during transitions between compartments, based on HIV centage of PLWH linking to care that are needed to achieve an status and place in the HIV care continuum (Supplementary ambitious goal of 50% reduction in HIV incidence by 2025. Our Section “Model Costs”). Future costs were discounted 3%. In aim was to define tangible metrics for care continuum engage- this study, we modeled outcomes over a 10-year period, from ment that are tied to population-level epidemiologic goals and 2016 to 2025. The model output of interest was relative reduc- can be used by program managers and public health officials. tion in incident cases of HIV, or the percentage point change in HIV incidence—with a primary target of 50% reduction by METHODS 2025, compared with the projected 2025 incidence assuming continuation of the current care continuum. We evaluated a The Johns Hopkins HIV economic-epidemic model (JHEEM) 50% reduction by 2025 as a further extension of epidemiologic is a compartmental model of the US HIV epidemic that incor- goals on the path to elimination, building on current NHAS porates transmission, disease progression, and health system goals of reducing new diagnoses by 25% by 2020. We addition- engagement (Supplementary Figure  1) [9, 11]. Briefly, this ally evaluated more modest (25% reduction) and more ambi- model partitions the adult population (age 18–78  years) of tious (75% reduction) reductions in incidence in secondary the United States based on sex, age, HIV infection, and trans- analyses. We modeled a continuation of the current care con- mission category (heterosexuals, men who have sex with men tinuum (Figure S4) to serve as the baseline comparator to esti- [MSM], and people who inject drugs [PWID]). Lower-risk mate the projected percentage point change in incidence under groups were defined as older heterosexuals, and higher-risk alternative care continuum scenarios (Table  1; Supplementary groups were defined to include younger individuals (age Figures 2 and 3)  [9, 11]. We used JHEEM to sample ~100 000 18–28  years), young and old MSM, and PWID. HIV infec- simulations in which we simultaneously varied, within wide tion, transition through the care continuum, and demographic ranges using a uniform distribution (ie, where all values within changes were modeled dynamically as a system of ordinary dif- the range are equally likely), the care continuum parameters of ferential equations [9, 11]. PLWH were further characterized by interest: (1) annual high-risk screening rates, (2) annual low- CD4 strata and stage of HIV care continuum, through which risk screening rates, (3) percentages of PLWH linking to care subpopulations can transition: unaware of HIV status, aware within 1  month of initial diagnosis, (4) annual rates of disen- but out of care, in care but not on ART, on ART but not virolog- gagement from care for those in care, and (5) annual rates of ically suppressed, and virologically suppressed. Those who are reengagement into care for those aware of their diagnosis and in care are initiated per current guidelines (at any CD4 count) out of care, while holding all other parameters within the model on suppressive ART regimens. We modeled retention in care as constant (Table  1; Supplementary Figure  1, Supplementary having sustained access to clinical care and eligibility for ART. Table 1). We did not incorporate specific care continuum inter- Suboptimal adherence was modeled in terms of risks for viro- vention costs to achieve specific rates of screening, linkage, and logic failure (but still retained in care); for those retained in care, retention. However, each model simulation incorporated unit the model assumed timely detection of viremia and initiation of costs per HIV test, linkage to care costs per individual linking alternative regimens capable of achieving virologic suppression. and establishing care (baseline genotype, viral load, CD4 count, It also assumed that those lost to follow-up or not retained in clinic visit), and incorporated an annual cost per individual care experienced viremia (and not on ART), but were eligible retained on a yearly basis (Supplementary Data); as such, we for care reengagement and initiation of suppressive ART regi- projected the incremental total health system costs of improv- mens at a later point in time. Total health system costs are calcu- ing the care continuum in each simulation, compared with the lated based on time spent per individual in each compartment Table 1. Key Model Parameters Simulation Range a a Model Parameters Baseline Value [min., max.] References 9,11 Annual rate of retention in care, %/y 86–89 [50, 99] 9,11 Annual rate of reengagement into care, %/y 20 [1, 100] c 9,11 Annual screening rate among high-risk group, %/y 7.5–25 [1, 100] c 9,11 Annual screening rate among low-risk groups, %/y 12.5–17.5 [1, 100] d 9,11 Percentage of PLWH linking to care 55–75 [1, 100] Abbreviation: PLWH, people living with HIV. Base-case values (stratified by risk group) were based on literature estimates and model calibration to current estimates of the care continuum (see the supplementary section on Additional Model Details, Supplementar y Table 1 [3]. Ranges represent ranges across which we varied the parameters for our simulation experiments. High-risk groups include heterosexual youths, people who inject drugs, men who have sex with men. Percentage of PLWH linking to care represents percent linking to care within 1 month; PLWH not linked to care can still engage in care at a later point in time. 2 • OFID • Perry et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 base-case scenario of continuation of current rates of care con- of care from 50% per year to 60% per year) increased the esti- tinuum engagement. mated probability of halving HIV incidence by 2025 by an aver- To assess the relationships between the care continuum age of approximately 2% (Figure 1B; Supplementary Table 2). parameters and the dichotomous outcome of halving incidence Using multivariable linear regression, all 5 elements of the by 2025 (yes/no), scatterplots with Locally Weighted Scatterplot care cascade were associated with the projected probability of Smoothing (Lowess) were created and evaluated for linearity. halving incidence by 2025, but the strength of the association A  linear regression model with a robust estimate of variance varied by care continuum element (Table  2). For every 10% was run to explore the additive association between a 10% in- absolute improvement in the rate of retention above 80% (eg, crease in each of the care continuum parameters, treated as from 85% to 95% per year), the estimated probability of halving continuous variables, and the projected probability of halving incidence by 2025 increased by approximately 25% (95% con- incidence by 2025. fidence interval [CI], 24.8%–25.6%), and for each 10% absolute Next, to explore the interaction between retention (ie, com- increase in the rate of reengagement (eg, from 40% per year plement of disengagement from care) and reengagement in [average 2.5-year duration of disengagement] to 50% per year care, a 10-by-10 color-coded grid was created, with each cell in [average 2.0-year duration]), the projected probability increased the grid corresponding to the estimated probability of halving by 2.0% (95% CI, 1.96%–2.05%). Annual screening rates among incidence by 2025 for different combinations of retention and high-risk groups and the percentage of PLWH linking to care reengagement strata. had significant, but weaker, associations with the estimated Finally, to explore potential interactions among all model probability of halving incidence—and annual screening rates parameters, we conducted a probabilistic sensitivity ana- among low-risk groups had very little association (Table 2). lysis where we ran ~100 000 simulations in which all model Figure  2 displays the projected probability of halving inci- parameters were varied simultaneously within their plausible dence by 2025 among different strata of rates of retention and ranges and repeated statistical analyses similar to the above reengagement and suggests that improved rates of both reten- (Supplementary Section 3). tion and reengagement are needed to maximize the estimated Data were analyzed using R, version 3.0.1 (R Foundation for probability of halving incidence within the next 10  years. At Statistical Computing), and Stata, version 14.1. poor rates of annual retention in care (ie, less than 95%), not- ably higher rates of yearly reengagement into care (ie, median RESULTS 71%) are needed to maintain a reasonable projected prob- ability of achieving this target (Figure 2, Table 2; Supplementary If current rates of engagement in the HIV care continuum con- Table 3). When retention rates are at least 95% and more than tinue (and without other behavioral or pharmacologic interven- 70% of people living with HIV out of care reengage into care tions), our model projects 374 000 (95% UR 152 000–606 000)     annually, there is nearly a 90% projected probability of halving new HIV infections and 225 000 deaths among PLWH (95% UR incidence by 2025 (Figure 2). 66 000–464 000) between 2016 and 2025[11]. Of the approxi-     We evaluated the estimated probability of halving incidence mately 100 000 experimental simulations in this analysis, 26% by 2025 according to level of suppression at the population level achieved at least a 25% projected reduction in incidence, 7% as the final step in the care continuum. Current NHAS targets achieved at least a 50% reduction in incidence, and no simula- suggest increasing the percentage of diagnosed individuals to tions achieved at least a 75% reduction in incidence by 2025, as 80% (with a goal of at least 90% awareness). We estimated a compared with projections with continuation of the current care probability of halving incidence of only 9% if population-level continuum. Compared with a baseline estimate of total health suppression among all PLWH is less than or equal to 80%, and system costs of $251 billion, we projected median incremental a 62% probability if this target were increased to 80%–85% costs of $77 billion (31% increase; IQR, $62 billion–$91 billion) viral suppression among all PLWH. By contrast, the estimated associated with achieving a 25% reduction and $93 billion (37% probability of achieving a halving of incidence was 98% if increase; IQR, $79 billion–$106 billion) to achieve a 50% reduc- more than 85% of all PLWH can be virally suppressed by 2025 tion in incidence by 2025, attributable to increased health care (Supplementary Figure 5). engagement (eg, increased antiretroviral drug (ARV) utilization We conducted extensive sensitivity analyses to explore the im- among simulations with higher rates of retention in care). pact and interactions with other non–care continuum param- e p Th rojected probability of halving incidence is most closely eters. Varying all model parameters simultaneously did not associated with retention and reengagement in care (Figure  1). impact our findings or inferences (Supplementary Section 3). With a baseline probability of disengagement from care greater than 20%, there was a projected 0% probability of halving inci- DISCUSSION dence within the next 10 years (Figure 1A; Supplementary Table 2, ie, sixth to tenth strata). Each absolute 10% increase in annual We found that high rates of both annual retention (for those rates of care reengagement (eg, reengagement of individuals out in care) and reengagement (for those out of care) are critical to Achieving NHAS Targets in the United States • OFID • 3 Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 AB Impact of annual retention in care on Impact of care reengagement on achieving achieving reductions in incidence reductions in incidence 60 18 16.93 54.66 14.45 12.03 9.27 24.45 7.31 22.79 4.97 20 6 2.87 1.07 2.14 0.15 0 0 00 00 0 0 ≤5 5–10 10–15 15–20 20–25 25–30 30–35 35–40 40–45 >45 ≤10 10–20 20–30 30–40 40–50 50–60 60–70 70–80 80–90 >90 Percent of PLWH disengaging from care annually (%)Percent of PLWH reengaging into care annually (%) CD Impact of high-risk screening on Impact of low-risk screening on achieving reductions in incidence achieving reductions in incidence 7.6 10.16 9.62 10 9.48 7.4 7.33 7.33 9.07 7.23 7.22 7.23 7.2 7.86 7.6 6.56 6.85 6.82 6.81 6.81 6.8 4.72 6.6 3.21 6.34 6.4 6.2 1.08 5.8 <once every 10 years Once every other year Approximately <once every 10 yearsOnce every other year Approximately once per year once per year Frequency of screening among high-risk groups (youths, IDU, MSM) Frequency of screening among low-risk groups Impact of % linking to care on achieving reductions in incidence 8.79 8.02 7.74 8 7.35 7.28 6.86 6.66 6.66 6.72 5.92 ≤40 40–45 45–50 50–55 55–60 60–65 65–70 70–75 75–80 >80 Percentage of PLWH linking to care within 1 month* *PLWH not linked can engage in care at later time (%) Figure 1. Projected probability of halving US HIV incidence by 2025 by rates of each care continuum parameter. Each care continuum parameter is divided into 10 even strata. Bars represent the percentage of simulations that achieved a 50% reduction in incidence by 2025, according to each stratum. Shown are the percentage of people living with HIV (PLWH) disengaging from care annually (A), percentage of PLWH reengaging into care annually (B), frequency of screening among high-risk groups (ie, youths, people who inject drugs, men who have sex with men) (C), frequency of screening among low-risk groups (D), and percentage of PLWH linking to care within 1 month (E). Abbreviations: IUD, injection drug users; MSM, men who have sex with men; PLWH, people living with HIV. Table 2. Impact of 10% Change in Annual Rates of Screening, Linkage, Retention, and Reengagement on Achieving Reductions in HIV Incidence Change in Projected Probability of Achieving Incidence Target Care Continuum Parameter Mean (95% CI), % Annual rate of retention above 80% 25.17 (24.77–25.57) Annual rate of reengagement 2.00 (1.96–2.05) Annual rate of high-risk screening 0.96 (0.92–1.01) Annual rate of low-risk screening 0.11 (0.06–0.15) Percentage of PLWH linking to care annually 0.37 (0.32–0.41) Abbreviations: CI, confidence interval; PLWH, people living with HIV. Multivariable linear regression with robust estimate of variance of achieving 50% reduction in incidence by 2025 on care continuum parameters. 50% reduction in incidence (95% CI) per 10% absolute increase in each care continuum parameter. High-risk groups include heterosexual youths, people who inject drugs, men who have sex with men. Percentage of PLWH linking to care represents percentage of PLWH linking to care within 1 month; those who are not linked to care can still engage in care at a later point in time. 4 • OFID • Perry et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 % of simulations meeting % of simulations meeting incidence target incidence target % of simulations meeting incidence target % of simulations meeting % of simulations meeting incidence target incidence target % of PLWH retained in care per year: <55% 0 0 0 0 0 0 0 0 0 0 55–60% 0 0 0 0 0 0 0 0 0 0 60–65% 0 0 0 0 0 0 0 0 0 0 65–70% 0 0 0 0 0 0 0 0 0 0 70–75% 0 0 0 0 0 0 0 0 0 0 75–80% 0 0 0 0 0 0 0 0 0 0 80–85% 0 0 0 0 0 0 0 0 0 0 0.55 4.86 15.46 85–90% 0 0 0 0 0 0 0 (6/1098) (49/1009) (164/1061) 2.89 11.72 25.97 46.10 61.55 73.83 90–95% 0 0 0 0 (30/1037) (115/981) (274/1055) (490/1063) (626/1017) (776/1051) 74.44 2.01 12.46 34.16 56.51 83.59 88.67 93.26 94.66 >95% 0 (16/795) (107/859) (289/846) (469/830) (626/841) (652/780) (712/803) (803/861) (798/843) Reengagement: <10% 10–20% 20–30% 30–40% 40–50% 50–60% 60–70% 70–80% 80–90% >90% % of PLWH out of care returning to care per year 1–20 20–50 50–70 70–90 >90 Figure 2. Projected probability of halving US HIV incidence by 2025 by annual rates of retention and reengagement in care. Chart displaying percentages of simulations achieving 50% reduction in incidence, in 2 × 2 fashion, by annual rates of retention and reengagement in care. The values in each box represent the total percentage (and fraction) of scenarios within each combination of annual rates of retention and reengagement in care that achieved a 50% reduction in incidence by 2025. Cells with 0s represent permutations where no simulations met this target; these cells represent 25 742 simulations of the approximately 100 000 total simulations. Abbreviation: PLWH,     people living with HIV. reducing HIV incidence. In our model, when rates of retention social networks in retention-focused interventions, and incor- are less than 80% per year, it is essentially impossible, without porating clinical staff with expertise to serve high-risk popu- other non–care continuum interventions, to achieve a 50% lations [22, 23]. Furthermore, integration of services, provider reduction in HIV incidence in the United States by 2025. Our notification systems, and, to a lesser extent, case management, modeling results suggest that, to maximize the projected prob- technology, and clinic-based interventions may be potentially ability of halving HIV incidence within the next decade, annual efficacious strategies [14]. rates of retention in care should be at least 90%, and preferably Coupled with high rates of retention in care, our modeling greater than 95%, coupled with annual rates of care reengage- suggests a need for relatively high rates of reengaging people ment (for those aware of their HIV serostatus but not in care) of out of care back into care within an average of 1.5  years, to at least 70% (ie, reengaging diagnosed PLWH into care within shorten the potential time of viremia and excess HIV trans- an average of 1.5 years). When retention in care was more than missions. Given the challenges of achieving such high rates of 95% per year and PLWH who were lost to care reengaged within retention and re-engagement, realistic approaches to achieving approximately 1.5 years (on average), the estimated probability a 50% reduction in incidence by 2025 will need to be compre- of halving incidence by 2025 was approximately 90%. hensive in nature—including not only retention and reengage- Our proposed quality metric for HIV programs of retain- ment in care, but also preventive strategies (eg, pre-exposure ing at least 95% of individuals in care on an annual basis will prophylaxis, behavioral interventions, and condom promotion) require dedicated effort in the United States. Current estimates and improved treatment options. Ultimately, we must prioritize of annual rates of retention in HIV care in the United States are patient-centered approaches that consider the diverse needs of heterogeneous and sparse, and defining retention in care has PLWH and seek to meet those needs in a holistic fashion [11]. been difficult, with no consensus definition [12, 14–16]. Current Not surprisingly, we found that in addition to retention and literature reviews estimate that current rates of retention in care reengagement, annual screening and the percentage of PLWH range from 45% to 70% per year, although retention has mostly linking to care were also associated with simulations achiev- been evaluated in cross-sectional analyses and has not yet been ing high reductions in HIV incidence, highlighting the fact fully studied longitudinally [3, 12, 14, 17–20]. Most existing that screening and diagnosis are essential entry steps toward research, however, suggests that retaining 95% of individuals care engagement and ART usage. Our findings support cur - in care per year will require new interventions [21]. Potential rent recommendations focusing on high-risk populations, opportunities for intervention strategies to improve retention which recommend screening groups at very high risk for new in HIV care include using community-based organizations to HIV infection at least annually, whereas we found that screen- emphasize the importance of regular care, involving patients’ ing rates in low-risk groups have very little association with Achieving NHAS Targets in the United States • OFID • 5 Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 the estimated probability of halving the incidence within the linkage, and adherence or care engagement will likely require a next 10  years [10, 22]. Nevertheless, the absolute incremental combination of health system, policy, and clinical innovations, improvements associated with more frequent screening and along with sustained financial commitments to providing com- percentage of PLWH linked to care within 1 month of diagnoses prehensive HIV care and ARV therapy [11]. Our model of the were modest as compared with achieving high rates of retention HIV care continuum does not address the potential effects and reengagement in care, suggesting that improving screen- of scale-up of pre-exposure prophylaxis (PrEP) or other pre- ing rates and linkage to care alone will not impact incidence. ventive interventions; thus, to the extent that these interven- A focus on other care continuum parameters, notably retention tions are effective at the population level and scaled up over and reengagement in care, is necessary. time, our care continuum targets may be overly ambitious. Our findings are consistent with prior studies, which have Our results should therefore be interpreted as the levels of re- found that continuous retention in care is critical and must be tention and reengagement that should be achieved in order to of high priority to achieve ambitious reductions in incidence maximize the estimated probability of halving incidence by [11, 12]. Research describes adverse impacts of poor reten- 2025, in the absence of large scale-up of additional preventive tion in care on patient outcomes, including decreased likeli- interventions. The high levels of retention and reengagement hood of receiving ART, higher rates of ART failure, increased necessary speak to the importance of scaling up prevention risky behaviors that promote HIV transmission, increased (in addition to strengthening the care continuum) in order to rates of hospitalization, and decreased survival [24, 25]. achieve NHAS goals. Identifying evidence-based interventions is critical to improv- In conclusion, our model suggests that sustained improve- ing long-term retention and closing the current gap in the ments in retention and reengagement in care, retaining at least HIV care continuum [24, 26, 27]. Currently, most HIV care 95% of PLWH in care annually and reengaging PLWH out of outcomes that are reported are limited by their cross-sectional care back into care within an average of 1.5 years, should be pri- nature and short time period for follow-up. However, given oritized if we are to halve HIV incidence in the United States by the temporally dynamic nature of the care continuum, it is 2025. Our results oer q ff uantitative guidance to inform policy important to report longitudinal measures of outcomes per recommendations and help programs evaluate success in care unit time to allow for a more comprehensive understanding by focusing on dynamic rates. These goals for retention and of intervention efficacy [14]. This study is among the first to reengagement rates are ambitious, and future research should quantify rates of care continuum engagement that are needed focus on their feasibility (ie, specific intervention efficacy and to maximize the projected probability of achieving popu- costs) and identifying evidence-based effective strategies to lation-level reductions in incidence. Our findings have sig- achieve such targets, while also emphasizing the need for a nificant value for policy makers, HIV clinics, and HIV care comprehensive approach including scale-up of prevention (eg, programs by quantifying programmatic benchmarks that cor- PrEP) and accounting for potential changes in transmission relate with population levels of reduced incidence. Moreover, over the next decade. As HIV care programs move forward, our our model provides interpretable probabilities of halving in- model suggests that efforts, resources, and priorities must be cidence within the next 10  years at different levels of annual focused on retaining almost all PLWH in care and frequently retention and reengagement. reengaging those out of care to reduce HIV incidence in the Our study is limited in that the model is calibrated to nation- United States over the next decade. al-level epidemiology; to the extent that there are regional Supplementary Data variations in HIV care engagement, our results may over- or Supplementary materials are available at Open Forum Infectious Diseases underestimate the relative impact of improvements in local online. Consisting of data provided by the authors to benefit the reader, care continua [11, 19]. Furthermore, given the relative paucity the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corre- of evidence-based data, our model did not evaluate feasibility, sponding author. nor did it evaluate specific interventions that would likely be needed to achieve such recommendations [14]. Nonetheless, Acknowledgments independent of specific intervention costs, we present the Financial support. This research was made possible with help from estimated overall incremental increases in total health system the Johns Hopkins University Center for AIDS Research, a National Institutes of Health (NIH)–funded program (1P30AI094189), which is costs associated with increased care engagement along the supported by the following NIH Co-Funding and Participating Institutes HIV care continuum required to achieve epidemiologic goals. and Centers: National Institute of Allergy and Infectious Diseases (NIAID), Needed increases in screening, linkage, and retention in care National Cancer Institute (NCI), National Institute of Child Health and Human Development (NICHD), National Heart, Lung, and Blood Institute (ie, with increased sustained ART usage) were estimated to (NHLBI), National Institute on Drug Abuse (NIDA), National Institute result in more than 30% higher total health system expendi- of Mental Health (NIMH), National Institute on Aging (NIA), Fogarty tures compared with continuing at current levels of care en- International Center (FIC), National Institute of General Medical Sciences gagement. Our results suggest that efforts to improve testing, (NIGMS), National Institute of Diabetes and Digestive and Kidney Diseases 6 • OFID • Perry et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 (NIDDK), and Office of AIDS Research (OAR). The content is solely the 12. Colasanti J, Kelly J, Pennisi E, et al. Continuous retention and viral suppression provide further insights into the HIV care continuum compared to the cross- responsibility of the authors and does not necessarily represent the official sectional HIV care cascade. Clin Infect Dis 2016; 62:648–54. views of the NIH. 13. National HIV/AIDS Strategy for the United States: Updated to 2020. https://files. Potential conifl cts of interest. All authors: no reported conflicts of hiv.gov/s3fs-public/nhas-update.pdf. 2015. Accessed 30 August 2017. interest. All authors have submitted the ICMJE Form for Disclosure of 14. 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The HIV treatment cascade and care continuum: 2. CDC. HIV in the United States: at a glance. 2017. Available at: https://www.cdc. updates, goals, and recommendations for the future. AIDS Res Ther 2016; 13:35. gov/hiv/statistics/overview/ataglance.html. Accessed 1 December 2017. 18. Gardner EM, McLees MP, Steiner JF, et al. The spectrum of engagement in HIV 3. CDC. Understanding the HIV care continuum. 2017. https://www.cdc.gov/ care and its relevance to test-and-treat strategies for prevention of HIV infection. hiv/pdf/library/factsheets/cdc-hiv-care-continuum.pdf. Accessed 1 December Clin Infect Dis 2011; 52:793–800. 19. Bradley H, Hall HI, Wolitski RJ, et al. Vital signs: HIV diagnosis, care, and treat- 4. Song R, Hall HI, Green TA, et  al. Using CD4 data to estimate HIV incidence, ment among persons living with HIV–United States, 2011. MMWR Morb Mortal prevalence, and percent of undiagnosed infections in the United States. J Acquir Wkly Rep 2014; 63:1113–7. Immune Defic Syndr 2017; 74:3–9. 20. Mugavero MJ, Amico KR, Horn T, Thompson MA. The state of engagement in 5. CDC. New HIV infections drop 18 percent in six years. 2017. Available at: HIV care in the United States: from cascade to continuum to control. Clin Infect https://www.cdc.gov/nchhstp/newsroom/2017/croi-hiv-incidence-press-re- Dis 2013; 57:1164–71. lease.html. Accessed 30 August 2017. 21. Fleishman JA, Yehia BR, Moore RD, et al; HIV Research Network. Establishment, 6. Hall H, Singh S, Song R, et al. CDC - HIV incidence, prevalence and undiagnosed retention, and loss to follow-up in outpatient HIV care. J Acquir Immune Defic infections in men who have sex with men - HIV incidence decreased among Syndr 2012; 60:249–59. all transmission categories except MSM. 2017. Available at: http://www.natap. 22. WHO HIV/AIDS Programme. Service delivery approaches to HIV testing and org/2017/CROI/croi_116.htm. Accessed 30 August 2017. counselling (HTC): a strategic HTC programme framework. 2012. Available at: 7. CDC. Monitoring selected national HIV prevention and care objectives by using http://apps.who.int/iris/bitstream/10665/75206/1/9789241593877_eng.pdf ?ua=1. HIV surveillance data - United States and 6 dependent areas, 2015. HIV sur- Accessed 20 February 2017. veillance supplemental report 2017. 2017. Available at: http://www.cdc.gov/hiv/ 23. Higa DH, Marks G, Crepaz N, et  al. Interventions to improve retention in HIV library/reports/hiv-surveillance.html. Accessed 30 August 2017. primary care: a systematic review of U.S.  studies. Curr HIV/AIDS Rep 2012; 8. HIV.gov. What is the HIV care continuum? 2016. Available at: https://www. 9:313–25. hiv.gov/federal-response/policies-issues/hiv-aids-care-continuum. Accessed 20 24. Saag M, Mugavero M. Retention and Re-Engagement in Care. http://www.hivma. February 2017. org/Templates/TwoColumn.aspx?pageid=32212264903&LangType=1033. 2013. 9. 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Achieving NHAS Targets in the United States • OFID • 7 Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Open Forum Infectious Diseases Oxford University Press

What Will It Take to Reduce HIV Incidence in the United States: A Mathematical Modeling Analysis

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Abstract

Open Forum Infectious Diseases MAJOR ARTICLE What Will It Take to Reduce HIV Incidence in the United States: A Mathematical Modeling Analysis 1 1 1 2 Allison Perry, Parastu Kasaie, David W. Dowdy, and Maunank Shah 1 2 Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Johns Hopkins University School of Medicine, Baltimore, Maryland Background. e N Th ational HIV/AIDS Strategy has set ambitious goals to improve the epidemic in the United States. However, there is a paucity of usable program-level benchmarks tied to population-level epidemiologic goals. Our objective was to define tangible benchmarks for annual rates along the care continuum that are likely to translate to meaningful reductions in incidence. Methods. We used a validated mathematical model of HIV transmission and care engagement to characterize care continuum parameters that would translate into 50% reductions in incidence by 2025, compared with a base case scenario of the current US care continuum. We generated a large pool of simulations in which rates of screening, linkage, and retention in care were varied across wide ranges to evaluate permutations that halved incidence by 2025. Results. Among all simulations, 7% achieved a halving of incidence. It was impossible for our simulations to achieve this target if the annual rate of disengagement from care exceeded 20% per year, even at high rates of care reengagement. When retention in care was 95% per year and people living with HIV (PLWH) out of care reengaged within 1.5 years (on average), the probability of halving incidence by 2025 was approximately 90%. Conclusions. HIV programs should aim to retain at least 95% of PLWH in care annually and reengage people living with HIV into care within an average of 1.5 years to achieve the goal of halving HIV incidence by 2025. Keywords. HIV care-continuum; HIV/AIDS; linkage to care; retention in care; mathematical model; economics. Since the beginning of the epidemic, more than 1.2 million peo- for high-risk groups [9]. Nevertheless, research suggests that ple in the United States have received an AIDS diagnosis, and sustained engagement of PLWH in care is a critical factor for more than 700 000 people have died [1, 2]. There are currently both improved individual health and prevention of further HIV an estimated 1.1 million persons aged 13 years and older living transmission [9–12]. with HIV (PLWH) in the United States, with some estimates In response to the ongoing HIV epidemic, the National suggesting that less than 50% are retained in care [2–4]. Despite HIV/AIDS Strategy (NHAS) was recently updated in 2015 improvements in antiretroviral therapy (ART) and evidence [13]. Among the key components was enumeration of cross- for treatment as prevention with guidance for early ART initia- sectional population-level targets for care engagement and tion, incidence of HIV has declined at a slow rate and remains improvements in incidence [13]. Our group has previously uti-     between 36 000 and 39 000 new HIV infections per year [4–7]. lized a mathematical modeling approach to evaluate whether Among the challenges is an imperfect HIV care continuum, in achievement of these NHAS care continuum targets was likely which current national estimates suggest that suboptimal num- to achieve sustained reductions in transmission. The studies bers of PLWH are virologically suppressed, representing missed found that failure to improve engagement in HIV care leads to opportunities for averting ongoing HIV transmission [8]. excess infections, treatment costs, and deaths, and that interven- Each step along the HIV care cascade, from diagnosis to tions must improve not just HIV screening but also retention in engagement in HIV care and long-term ART adherence, must care to optimize epidemiologic impact and cost-effectiveness be strengthened [9]. There has been widespread focus on testing [9, 11]. Nonetheless, care continuum targets (ie, increasing the and initiation of treatment, with efforts to scale-up HIV testing percentage of persons with diagnosed HIV infection who are retained in HIV medical care to at least 90%) have not been quantitatively linked to stated epidemiological goals, and many Received 9 September 2017; editorial decision 23 December 2017; accepted 5 January 2018. continue to remain aspirational. Moreover, such cross-sectional Correspondence: A.  Perry, MHS, 71 Barnyard Lane, Roslyn Heights, NY 11577 (allison. goals are not easily translated into objective metrics that HIV perry23@gmail.com) program managers can utilize to assess success in their own Open Forum Infectious Diseases © The Author(s) 2018. Published by Oxford University Press on behalf of Infectious Diseases programs on an ongoing basis [9, 11]. Society of America. This is an Open Access article distributed under the terms of the Creative In this study, we aimed to define the standards of care engage- Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/ by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any ment along the full spectrum of the HIV care continuum that medium, provided the original work is not altered or transformed in any way, and that the work would be necessary to “bend the curve” of the HIV epidemic is properly cited. For commercial re-use, please contact journals.permissions@oup.com DOI: 10.1093/ofid/ofy008 in the United States. We sought to determine the annual rates Achieving NHAS Targets in the United States • OFID • 1 Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 of screening, retention, and reengagement in care, and the per- and during transitions between compartments, based on HIV centage of PLWH linking to care that are needed to achieve an status and place in the HIV care continuum (Supplementary ambitious goal of 50% reduction in HIV incidence by 2025. Our Section “Model Costs”). Future costs were discounted 3%. In aim was to define tangible metrics for care continuum engage- this study, we modeled outcomes over a 10-year period, from ment that are tied to population-level epidemiologic goals and 2016 to 2025. The model output of interest was relative reduc- can be used by program managers and public health officials. tion in incident cases of HIV, or the percentage point change in HIV incidence—with a primary target of 50% reduction by METHODS 2025, compared with the projected 2025 incidence assuming continuation of the current care continuum. We evaluated a The Johns Hopkins HIV economic-epidemic model (JHEEM) 50% reduction by 2025 as a further extension of epidemiologic is a compartmental model of the US HIV epidemic that incor- goals on the path to elimination, building on current NHAS porates transmission, disease progression, and health system goals of reducing new diagnoses by 25% by 2020. We addition- engagement (Supplementary Figure  1) [9, 11]. Briefly, this ally evaluated more modest (25% reduction) and more ambi- model partitions the adult population (age 18–78  years) of tious (75% reduction) reductions in incidence in secondary the United States based on sex, age, HIV infection, and trans- analyses. We modeled a continuation of the current care con- mission category (heterosexuals, men who have sex with men tinuum (Figure S4) to serve as the baseline comparator to esti- [MSM], and people who inject drugs [PWID]). Lower-risk mate the projected percentage point change in incidence under groups were defined as older heterosexuals, and higher-risk alternative care continuum scenarios (Table  1; Supplementary groups were defined to include younger individuals (age Figures 2 and 3)  [9, 11]. We used JHEEM to sample ~100 000 18–28  years), young and old MSM, and PWID. HIV infec- simulations in which we simultaneously varied, within wide tion, transition through the care continuum, and demographic ranges using a uniform distribution (ie, where all values within changes were modeled dynamically as a system of ordinary dif- the range are equally likely), the care continuum parameters of ferential equations [9, 11]. PLWH were further characterized by interest: (1) annual high-risk screening rates, (2) annual low- CD4 strata and stage of HIV care continuum, through which risk screening rates, (3) percentages of PLWH linking to care subpopulations can transition: unaware of HIV status, aware within 1  month of initial diagnosis, (4) annual rates of disen- but out of care, in care but not on ART, on ART but not virolog- gagement from care for those in care, and (5) annual rates of ically suppressed, and virologically suppressed. Those who are reengagement into care for those aware of their diagnosis and in care are initiated per current guidelines (at any CD4 count) out of care, while holding all other parameters within the model on suppressive ART regimens. We modeled retention in care as constant (Table  1; Supplementary Figure  1, Supplementary having sustained access to clinical care and eligibility for ART. Table 1). We did not incorporate specific care continuum inter- Suboptimal adherence was modeled in terms of risks for viro- vention costs to achieve specific rates of screening, linkage, and logic failure (but still retained in care); for those retained in care, retention. However, each model simulation incorporated unit the model assumed timely detection of viremia and initiation of costs per HIV test, linkage to care costs per individual linking alternative regimens capable of achieving virologic suppression. and establishing care (baseline genotype, viral load, CD4 count, It also assumed that those lost to follow-up or not retained in clinic visit), and incorporated an annual cost per individual care experienced viremia (and not on ART), but were eligible retained on a yearly basis (Supplementary Data); as such, we for care reengagement and initiation of suppressive ART regi- projected the incremental total health system costs of improv- mens at a later point in time. Total health system costs are calcu- ing the care continuum in each simulation, compared with the lated based on time spent per individual in each compartment Table 1. Key Model Parameters Simulation Range a a Model Parameters Baseline Value [min., max.] References 9,11 Annual rate of retention in care, %/y 86–89 [50, 99] 9,11 Annual rate of reengagement into care, %/y 20 [1, 100] c 9,11 Annual screening rate among high-risk group, %/y 7.5–25 [1, 100] c 9,11 Annual screening rate among low-risk groups, %/y 12.5–17.5 [1, 100] d 9,11 Percentage of PLWH linking to care 55–75 [1, 100] Abbreviation: PLWH, people living with HIV. Base-case values (stratified by risk group) were based on literature estimates and model calibration to current estimates of the care continuum (see the supplementary section on Additional Model Details, Supplementar y Table 1 [3]. Ranges represent ranges across which we varied the parameters for our simulation experiments. High-risk groups include heterosexual youths, people who inject drugs, men who have sex with men. Percentage of PLWH linking to care represents percent linking to care within 1 month; PLWH not linked to care can still engage in care at a later point in time. 2 • OFID • Perry et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 base-case scenario of continuation of current rates of care con- of care from 50% per year to 60% per year) increased the esti- tinuum engagement. mated probability of halving HIV incidence by 2025 by an aver- To assess the relationships between the care continuum age of approximately 2% (Figure 1B; Supplementary Table 2). parameters and the dichotomous outcome of halving incidence Using multivariable linear regression, all 5 elements of the by 2025 (yes/no), scatterplots with Locally Weighted Scatterplot care cascade were associated with the projected probability of Smoothing (Lowess) were created and evaluated for linearity. halving incidence by 2025, but the strength of the association A  linear regression model with a robust estimate of variance varied by care continuum element (Table  2). For every 10% was run to explore the additive association between a 10% in- absolute improvement in the rate of retention above 80% (eg, crease in each of the care continuum parameters, treated as from 85% to 95% per year), the estimated probability of halving continuous variables, and the projected probability of halving incidence by 2025 increased by approximately 25% (95% con- incidence by 2025. fidence interval [CI], 24.8%–25.6%), and for each 10% absolute Next, to explore the interaction between retention (ie, com- increase in the rate of reengagement (eg, from 40% per year plement of disengagement from care) and reengagement in [average 2.5-year duration of disengagement] to 50% per year care, a 10-by-10 color-coded grid was created, with each cell in [average 2.0-year duration]), the projected probability increased the grid corresponding to the estimated probability of halving by 2.0% (95% CI, 1.96%–2.05%). Annual screening rates among incidence by 2025 for different combinations of retention and high-risk groups and the percentage of PLWH linking to care reengagement strata. had significant, but weaker, associations with the estimated Finally, to explore potential interactions among all model probability of halving incidence—and annual screening rates parameters, we conducted a probabilistic sensitivity ana- among low-risk groups had very little association (Table 2). lysis where we ran ~100 000 simulations in which all model Figure  2 displays the projected probability of halving inci- parameters were varied simultaneously within their plausible dence by 2025 among different strata of rates of retention and ranges and repeated statistical analyses similar to the above reengagement and suggests that improved rates of both reten- (Supplementary Section 3). tion and reengagement are needed to maximize the estimated Data were analyzed using R, version 3.0.1 (R Foundation for probability of halving incidence within the next 10  years. At Statistical Computing), and Stata, version 14.1. poor rates of annual retention in care (ie, less than 95%), not- ably higher rates of yearly reengagement into care (ie, median RESULTS 71%) are needed to maintain a reasonable projected prob- ability of achieving this target (Figure 2, Table 2; Supplementary If current rates of engagement in the HIV care continuum con- Table 3). When retention rates are at least 95% and more than tinue (and without other behavioral or pharmacologic interven- 70% of people living with HIV out of care reengage into care tions), our model projects 374 000 (95% UR 152 000–606 000)     annually, there is nearly a 90% projected probability of halving new HIV infections and 225 000 deaths among PLWH (95% UR incidence by 2025 (Figure 2). 66 000–464 000) between 2016 and 2025[11]. Of the approxi-     We evaluated the estimated probability of halving incidence mately 100 000 experimental simulations in this analysis, 26% by 2025 according to level of suppression at the population level achieved at least a 25% projected reduction in incidence, 7% as the final step in the care continuum. Current NHAS targets achieved at least a 50% reduction in incidence, and no simula- suggest increasing the percentage of diagnosed individuals to tions achieved at least a 75% reduction in incidence by 2025, as 80% (with a goal of at least 90% awareness). We estimated a compared with projections with continuation of the current care probability of halving incidence of only 9% if population-level continuum. Compared with a baseline estimate of total health suppression among all PLWH is less than or equal to 80%, and system costs of $251 billion, we projected median incremental a 62% probability if this target were increased to 80%–85% costs of $77 billion (31% increase; IQR, $62 billion–$91 billion) viral suppression among all PLWH. By contrast, the estimated associated with achieving a 25% reduction and $93 billion (37% probability of achieving a halving of incidence was 98% if increase; IQR, $79 billion–$106 billion) to achieve a 50% reduc- more than 85% of all PLWH can be virally suppressed by 2025 tion in incidence by 2025, attributable to increased health care (Supplementary Figure 5). engagement (eg, increased antiretroviral drug (ARV) utilization We conducted extensive sensitivity analyses to explore the im- among simulations with higher rates of retention in care). pact and interactions with other non–care continuum param- e p Th rojected probability of halving incidence is most closely eters. Varying all model parameters simultaneously did not associated with retention and reengagement in care (Figure  1). impact our findings or inferences (Supplementary Section 3). With a baseline probability of disengagement from care greater than 20%, there was a projected 0% probability of halving inci- DISCUSSION dence within the next 10 years (Figure 1A; Supplementary Table 2, ie, sixth to tenth strata). Each absolute 10% increase in annual We found that high rates of both annual retention (for those rates of care reengagement (eg, reengagement of individuals out in care) and reengagement (for those out of care) are critical to Achieving NHAS Targets in the United States • OFID • 3 Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 AB Impact of annual retention in care on Impact of care reengagement on achieving achieving reductions in incidence reductions in incidence 60 18 16.93 54.66 14.45 12.03 9.27 24.45 7.31 22.79 4.97 20 6 2.87 1.07 2.14 0.15 0 0 00 00 0 0 ≤5 5–10 10–15 15–20 20–25 25–30 30–35 35–40 40–45 >45 ≤10 10–20 20–30 30–40 40–50 50–60 60–70 70–80 80–90 >90 Percent of PLWH disengaging from care annually (%)Percent of PLWH reengaging into care annually (%) CD Impact of high-risk screening on Impact of low-risk screening on achieving reductions in incidence achieving reductions in incidence 7.6 10.16 9.62 10 9.48 7.4 7.33 7.33 9.07 7.23 7.22 7.23 7.2 7.86 7.6 6.56 6.85 6.82 6.81 6.81 6.8 4.72 6.6 3.21 6.34 6.4 6.2 1.08 5.8 <once every 10 years Once every other year Approximately <once every 10 yearsOnce every other year Approximately once per year once per year Frequency of screening among high-risk groups (youths, IDU, MSM) Frequency of screening among low-risk groups Impact of % linking to care on achieving reductions in incidence 8.79 8.02 7.74 8 7.35 7.28 6.86 6.66 6.66 6.72 5.92 ≤40 40–45 45–50 50–55 55–60 60–65 65–70 70–75 75–80 >80 Percentage of PLWH linking to care within 1 month* *PLWH not linked can engage in care at later time (%) Figure 1. Projected probability of halving US HIV incidence by 2025 by rates of each care continuum parameter. Each care continuum parameter is divided into 10 even strata. Bars represent the percentage of simulations that achieved a 50% reduction in incidence by 2025, according to each stratum. Shown are the percentage of people living with HIV (PLWH) disengaging from care annually (A), percentage of PLWH reengaging into care annually (B), frequency of screening among high-risk groups (ie, youths, people who inject drugs, men who have sex with men) (C), frequency of screening among low-risk groups (D), and percentage of PLWH linking to care within 1 month (E). Abbreviations: IUD, injection drug users; MSM, men who have sex with men; PLWH, people living with HIV. Table 2. Impact of 10% Change in Annual Rates of Screening, Linkage, Retention, and Reengagement on Achieving Reductions in HIV Incidence Change in Projected Probability of Achieving Incidence Target Care Continuum Parameter Mean (95% CI), % Annual rate of retention above 80% 25.17 (24.77–25.57) Annual rate of reengagement 2.00 (1.96–2.05) Annual rate of high-risk screening 0.96 (0.92–1.01) Annual rate of low-risk screening 0.11 (0.06–0.15) Percentage of PLWH linking to care annually 0.37 (0.32–0.41) Abbreviations: CI, confidence interval; PLWH, people living with HIV. Multivariable linear regression with robust estimate of variance of achieving 50% reduction in incidence by 2025 on care continuum parameters. 50% reduction in incidence (95% CI) per 10% absolute increase in each care continuum parameter. High-risk groups include heterosexual youths, people who inject drugs, men who have sex with men. Percentage of PLWH linking to care represents percentage of PLWH linking to care within 1 month; those who are not linked to care can still engage in care at a later point in time. 4 • OFID • Perry et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 % of simulations meeting % of simulations meeting incidence target incidence target % of simulations meeting incidence target % of simulations meeting % of simulations meeting incidence target incidence target % of PLWH retained in care per year: <55% 0 0 0 0 0 0 0 0 0 0 55–60% 0 0 0 0 0 0 0 0 0 0 60–65% 0 0 0 0 0 0 0 0 0 0 65–70% 0 0 0 0 0 0 0 0 0 0 70–75% 0 0 0 0 0 0 0 0 0 0 75–80% 0 0 0 0 0 0 0 0 0 0 80–85% 0 0 0 0 0 0 0 0 0 0 0.55 4.86 15.46 85–90% 0 0 0 0 0 0 0 (6/1098) (49/1009) (164/1061) 2.89 11.72 25.97 46.10 61.55 73.83 90–95% 0 0 0 0 (30/1037) (115/981) (274/1055) (490/1063) (626/1017) (776/1051) 74.44 2.01 12.46 34.16 56.51 83.59 88.67 93.26 94.66 >95% 0 (16/795) (107/859) (289/846) (469/830) (626/841) (652/780) (712/803) (803/861) (798/843) Reengagement: <10% 10–20% 20–30% 30–40% 40–50% 50–60% 60–70% 70–80% 80–90% >90% % of PLWH out of care returning to care per year 1–20 20–50 50–70 70–90 >90 Figure 2. Projected probability of halving US HIV incidence by 2025 by annual rates of retention and reengagement in care. Chart displaying percentages of simulations achieving 50% reduction in incidence, in 2 × 2 fashion, by annual rates of retention and reengagement in care. The values in each box represent the total percentage (and fraction) of scenarios within each combination of annual rates of retention and reengagement in care that achieved a 50% reduction in incidence by 2025. Cells with 0s represent permutations where no simulations met this target; these cells represent 25 742 simulations of the approximately 100 000 total simulations. Abbreviation: PLWH,     people living with HIV. reducing HIV incidence. In our model, when rates of retention social networks in retention-focused interventions, and incor- are less than 80% per year, it is essentially impossible, without porating clinical staff with expertise to serve high-risk popu- other non–care continuum interventions, to achieve a 50% lations [22, 23]. Furthermore, integration of services, provider reduction in HIV incidence in the United States by 2025. Our notification systems, and, to a lesser extent, case management, modeling results suggest that, to maximize the projected prob- technology, and clinic-based interventions may be potentially ability of halving HIV incidence within the next decade, annual efficacious strategies [14]. rates of retention in care should be at least 90%, and preferably Coupled with high rates of retention in care, our modeling greater than 95%, coupled with annual rates of care reengage- suggests a need for relatively high rates of reengaging people ment (for those aware of their HIV serostatus but not in care) of out of care back into care within an average of 1.5  years, to at least 70% (ie, reengaging diagnosed PLWH into care within shorten the potential time of viremia and excess HIV trans- an average of 1.5 years). When retention in care was more than missions. Given the challenges of achieving such high rates of 95% per year and PLWH who were lost to care reengaged within retention and re-engagement, realistic approaches to achieving approximately 1.5 years (on average), the estimated probability a 50% reduction in incidence by 2025 will need to be compre- of halving incidence by 2025 was approximately 90%. hensive in nature—including not only retention and reengage- Our proposed quality metric for HIV programs of retain- ment in care, but also preventive strategies (eg, pre-exposure ing at least 95% of individuals in care on an annual basis will prophylaxis, behavioral interventions, and condom promotion) require dedicated effort in the United States. Current estimates and improved treatment options. Ultimately, we must prioritize of annual rates of retention in HIV care in the United States are patient-centered approaches that consider the diverse needs of heterogeneous and sparse, and defining retention in care has PLWH and seek to meet those needs in a holistic fashion [11]. been difficult, with no consensus definition [12, 14–16]. Current Not surprisingly, we found that in addition to retention and literature reviews estimate that current rates of retention in care reengagement, annual screening and the percentage of PLWH range from 45% to 70% per year, although retention has mostly linking to care were also associated with simulations achiev- been evaluated in cross-sectional analyses and has not yet been ing high reductions in HIV incidence, highlighting the fact fully studied longitudinally [3, 12, 14, 17–20]. Most existing that screening and diagnosis are essential entry steps toward research, however, suggests that retaining 95% of individuals care engagement and ART usage. Our findings support cur - in care per year will require new interventions [21]. Potential rent recommendations focusing on high-risk populations, opportunities for intervention strategies to improve retention which recommend screening groups at very high risk for new in HIV care include using community-based organizations to HIV infection at least annually, whereas we found that screen- emphasize the importance of regular care, involving patients’ ing rates in low-risk groups have very little association with Achieving NHAS Targets in the United States • OFID • 5 Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 the estimated probability of halving the incidence within the linkage, and adherence or care engagement will likely require a next 10  years [10, 22]. Nevertheless, the absolute incremental combination of health system, policy, and clinical innovations, improvements associated with more frequent screening and along with sustained financial commitments to providing com- percentage of PLWH linked to care within 1 month of diagnoses prehensive HIV care and ARV therapy [11]. Our model of the were modest as compared with achieving high rates of retention HIV care continuum does not address the potential effects and reengagement in care, suggesting that improving screen- of scale-up of pre-exposure prophylaxis (PrEP) or other pre- ing rates and linkage to care alone will not impact incidence. ventive interventions; thus, to the extent that these interven- A focus on other care continuum parameters, notably retention tions are effective at the population level and scaled up over and reengagement in care, is necessary. time, our care continuum targets may be overly ambitious. Our findings are consistent with prior studies, which have Our results should therefore be interpreted as the levels of re- found that continuous retention in care is critical and must be tention and reengagement that should be achieved in order to of high priority to achieve ambitious reductions in incidence maximize the estimated probability of halving incidence by [11, 12]. Research describes adverse impacts of poor reten- 2025, in the absence of large scale-up of additional preventive tion in care on patient outcomes, including decreased likeli- interventions. The high levels of retention and reengagement hood of receiving ART, higher rates of ART failure, increased necessary speak to the importance of scaling up prevention risky behaviors that promote HIV transmission, increased (in addition to strengthening the care continuum) in order to rates of hospitalization, and decreased survival [24, 25]. achieve NHAS goals. Identifying evidence-based interventions is critical to improv- In conclusion, our model suggests that sustained improve- ing long-term retention and closing the current gap in the ments in retention and reengagement in care, retaining at least HIV care continuum [24, 26, 27]. Currently, most HIV care 95% of PLWH in care annually and reengaging PLWH out of outcomes that are reported are limited by their cross-sectional care back into care within an average of 1.5 years, should be pri- nature and short time period for follow-up. However, given oritized if we are to halve HIV incidence in the United States by the temporally dynamic nature of the care continuum, it is 2025. Our results oer q ff uantitative guidance to inform policy important to report longitudinal measures of outcomes per recommendations and help programs evaluate success in care unit time to allow for a more comprehensive understanding by focusing on dynamic rates. These goals for retention and of intervention efficacy [14]. This study is among the first to reengagement rates are ambitious, and future research should quantify rates of care continuum engagement that are needed focus on their feasibility (ie, specific intervention efficacy and to maximize the projected probability of achieving popu- costs) and identifying evidence-based effective strategies to lation-level reductions in incidence. Our findings have sig- achieve such targets, while also emphasizing the need for a nificant value for policy makers, HIV clinics, and HIV care comprehensive approach including scale-up of prevention (eg, programs by quantifying programmatic benchmarks that cor- PrEP) and accounting for potential changes in transmission relate with population levels of reduced incidence. Moreover, over the next decade. As HIV care programs move forward, our our model provides interpretable probabilities of halving in- model suggests that efforts, resources, and priorities must be cidence within the next 10  years at different levels of annual focused on retaining almost all PLWH in care and frequently retention and reengagement. reengaging those out of care to reduce HIV incidence in the Our study is limited in that the model is calibrated to nation- United States over the next decade. al-level epidemiology; to the extent that there are regional Supplementary Data variations in HIV care engagement, our results may over- or Supplementary materials are available at Open Forum Infectious Diseases underestimate the relative impact of improvements in local online. Consisting of data provided by the authors to benefit the reader, care continua [11, 19]. Furthermore, given the relative paucity the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corre- of evidence-based data, our model did not evaluate feasibility, sponding author. nor did it evaluate specific interventions that would likely be needed to achieve such recommendations [14]. Nonetheless, Acknowledgments independent of specific intervention costs, we present the Financial support. This research was made possible with help from estimated overall incremental increases in total health system the Johns Hopkins University Center for AIDS Research, a National Institutes of Health (NIH)–funded program (1P30AI094189), which is costs associated with increased care engagement along the supported by the following NIH Co-Funding and Participating Institutes HIV care continuum required to achieve epidemiologic goals. and Centers: National Institute of Allergy and Infectious Diseases (NIAID), Needed increases in screening, linkage, and retention in care National Cancer Institute (NCI), National Institute of Child Health and Human Development (NICHD), National Heart, Lung, and Blood Institute (ie, with increased sustained ART usage) were estimated to (NHLBI), National Institute on Drug Abuse (NIDA), National Institute result in more than 30% higher total health system expendi- of Mental Health (NIMH), National Institute on Aging (NIA), Fogarty tures compared with continuing at current levels of care en- International Center (FIC), National Institute of General Medical Sciences gagement. Our results suggest that efforts to improve testing, (NIGMS), National Institute of Diabetes and Digestive and Kidney Diseases 6 • OFID • Perry et al Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018 (NIDDK), and Office of AIDS Research (OAR). The content is solely the 12. Colasanti J, Kelly J, Pennisi E, et al. Continuous retention and viral suppression provide further insights into the HIV care continuum compared to the cross- responsibility of the authors and does not necessarily represent the official sectional HIV care cascade. Clin Infect Dis 2016; 62:648–54. views of the NIH. 13. National HIV/AIDS Strategy for the United States: Updated to 2020. https://files. Potential conifl cts of interest. All authors: no reported conflicts of hiv.gov/s3fs-public/nhas-update.pdf. 2015. Accessed 30 August 2017. interest. All authors have submitted the ICMJE Form for Disclosure of 14. 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Achieving NHAS Targets in the United States • OFID • 7 Downloaded from https://academic.oup.com/ofid/article-abstract/5/2/ofy008/4792832 by Ed 'DeepDyve' Gillespie user on 16 March 2018

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