The Center for Medicare and Medicaid (CMS) services is the largest single provider of health insurance in the United States (U.S.), with 90 million Americans benefiting through its programs.¹ Under the Patient Protection and Affordable Care Act (ACA), Medicaid coverage was expanded to 138% of the federal poverty level in states that opted for expansion.² As of April 2021, Medicaid expansion was yet to be adopted by 11 states, including Texas; two others (OK, MO) had adopted but not yet implemented Medicaid expansion.³

The most populous city in the Southern U.S., Houston, Texas, is home to over 2.3 million people. A racially/ethnically diverse population with a growing influx of immigrants and younger cohorts,⁴ Houston is the principal city of Harris County, which includes 4.7 million residents,⁵ and is a microcosm of Texas, the state with the highest uninsured rate in the country: of Texas adults under 65 years of age, nearly 25% are uninsured and less than 7% are covered by Medicaid.⁶ Despite proposals to create a state-tailored expansion, legislative debate in 2021 was short-lived,⁷ leaving Texas and major cities such as Houston with no end in sight to massive coverage gaps that disproportionately burden people of color.⁸ This disparity in medical access intersects with existing health disparities in disease burden and health inequities, a potential driver for sustained transmission of conditions such as HIV among groups that have been marginalized.

As of a recent CDC report, the Houston metropolitan area ranked ninth nationally in rate of new HIV diagnoses⁹ and reports lower rates of retention in HIV care and viral suppression than the U.S. overall.¹⁰Of all new diagnoses in 2019, men who have sex with men (MSM) are believed to have constituted nearly 71% of diagnoses in Houston/Harris County. Among MSM 18-34 years of age, the highest burden was among young, Black MSM (YBMSM) who made up 19% of all new diagnoses per internal calculations from the Houston Health Department whereby missing risk group information was imputed.¹¹ Contributing factors to continued HIV transmission, especially in the South, may include intersectional stigma of race and sexual identity in geographic regions perceived as oppressive and the medical distrust that results from this and other forces.¹²Expectations around masculinity and religious ideals that are common among Black communities lead some YBMSM to experience “potentially irreconcilable beliefs surrounding race and its interplay with… sexual identity”.¹³ Social isolation resulting from such perceptions and experiences of homophobia dissuade engagement in HIV prevention and care services. A further barrier to services includes insurance coverage; MSM in non-expansion states are more likely to be uninsured and less likely to utilize preexposure prophylaxis (PrEP) than their counterparts residing in expansion states.²Furthermore, research demonstrates that lacking health insurance is associated with lengthy delays in the initiation of PrEP care among interested YBMSM¹⁴and may be related to lower PrEP care retention.^15-19Medicaid expansion has been shown to improve engagement in both the ART and PrEP continua.^20-22 A number of empirical and simulation studies have projected declines in downstream HIV incidence due to improved ART and PrEP continuum engagement.²³

However, little is known about how Medicaid expansion is likely to impact downstream HIV incidence, particularly in Houston, which remains among the urban epicenters of HIV in the southern US. Estimating the population health impacts of policy reforms is difficult because the effects of such policies may be realized over time periods that are longer than the duration of most empirical studies. Second, these impacts occur at a multitude of scales, starting from the micro-level individual, to the meso-level networks, and the macro-level population or community impacts. Computational modeling allows for the investigation of the impact of policy interventions prior to their real-world implementation and provides rigorous methods to quantify uncertainties given that data on relevant parameters are sometimes parse, uncertain, or unavailable.

This study takes a simulation approach to investigate the impact of Medicaid expansion strategies on HIV incidence among YBMSM in the context of Houston, TX. This simulation study is grounded on the modeling framework of a previously developed and calibrated agent-based network model (ABNM) and relies on empirically defined parameter estimates.²³ ABNMs are a complex systems modeling technique that provide the flexibility to model individual persons and members of their community networks as "agents" and the social network structures that connect them as "ties". The co-evolution of agents and networks provides practical insight into the impacts of health policy implementations.²⁴ The goal is to study the population-health impacts of Medicaid expansion strategies that have shown promise at the individual-level in improving engagement across the ART and PrEP continua.^20-22,25To our knowledge, the impact of the resulting population-level improvements in ART and PrEP continua engagement on downstream HIV incidence have not yet been estimated.

The ABNM is deployed here as a tool to estimate how Medicaid expansion might impact HIV incidence in Houston in the next decade. Quantifying any projected gaps between the estimated declines in HIV incidence and the levels required to achieve a “functional zero” incidence (i.e., a level at which the projected number of new HIV infections is below the threshold needed to sustain the epidemic) can help guide intervention planning tailored for the YBMSM population at this important juncture.²⁶

Table 3 provides the mean tenth year incidence rate (per 100 person years), the mean number of HIV infections in the tenth year, and the mean HIV prevalence at the end of the ten years of the simulation period. Figure 1 displays the average annual incidence rates, Figures 1 and 2 display simulated data for the HIV incidence rate (per 100 py) and the annual mean number of new HIV infections under all four scenarios, with color bands that demonstrate the bootstrap SIs. Table 4 provides the cumulative number of new infections averted in each year of ME 1, ME 2 and ME 3, relative to the control scenario.

A considerable decline in the HIV incidence rate and the projected mean number of new HIV infections is observed under all three Medicaid expansion scenarios. The ME1 scenario resulted in a 17.5% reduction in the HIV incidence rate and about a 14.9% decline in the number of infections in the tenth year of the intervention versus baseline. ME2 yielded tenth-year declines of 42.3% in the HIV incidence rate and 37.8% in mean number of new infections. ME3 yielded reductions of 48.7% in the HIV incidence rate and 44.0% in the number of new infections in the tenth year.

Cumulatively, the 30 simulation runs of the control scenario produced a mean of 3699 new infections across the 10^th year. In contrast, ME1, ME2 and ME3 respectively yielded 3358, 2837, and 2698 cumulative infections, corresponding to declines of 9.2%, 14.1%, and 27.1%, relative to the control scenario.

In this study, we explored the impact that Medicaid expansion might have on HIV incidence among YBMSM in Houston. We observe that Medicaid expansion can make a sizeable impact on HIV incidence. In addition, increasing PrEP and ART uptake beyond the projected increases under Medicaid expansion, can yield further decreases in the rate of new cases. An increase in ART and PrEP uptake, beyond the levels projected under Medicaid expansion, might be necessary to eliminate HIV transmission in the next decade. For example, drug assistance programs (DAP) in combination with Medicaid expansion, have been associated with 99% increase in PrEP use,³⁹ and may prove effective in increasing uptake. While Medicaid expansion alone may not get Houston to the goal of zero incidence, expanding PrEP and ART interventions in combination may help achieve this goal.

Previous work in Chicago, with a comparably sized HIV epidemic, has suggested that increasing ART and PrEP uptake to 30% above current levels would lower incidence to about 200 new infections per year among YBMSM, reaching a “functional zero” transmission rate.²⁶ Simulated data presented in this study indicate some similarity between the two cities, with comparably sized populations of YBMSM, where about a 30% increase in PrEP uptake and a 15% increase in ART use is projected to result in 205 new HIV infections per year among YBMSM in Houston.

With the Texas legislature’s decision not to expand Medicaid in April 2021,⁷ there is little evidence that widespread coverage gaps will soon be mitigated through this avenue. However, Houston has made substantial strides to increase PrEP and ART uptake that may bring the city closer to HIV Ending the Epidemic goals. In 2019, the Houston Health Department (HHD) initiated a locally-driven awareness campaign with residents from the LGBTQ community serving as ambassadors. Branded I am Life, the campaign focused on PrEP and treatment as prevention (TasP) messages among the populations most impacted in Houston—Black and Hispanic MSM and transgender individuals.⁴⁰ Complementing work to increase demand for PrEP, the HHD simultaneously increased availability by expanding hours/days of operation at PrEP-specific clinics.

In order to promptly disrupt onward transmission, Houston also continues to expand rapid initiation of ART. Just one of fifteen grantees, a Houston community-based organization was awarded new federal funding in 2020 to build capacity for rapid ART implementation.^41,42 The Houston jurisdiction’s Ryan White Grant Administration additionally scaled up rapid start as part of their Ending the HIV Epidemic initiative. Over the period of 2020 to 2021, they have provided over $3.7 million to initiate or enhance rapid start in five provider locations in the Houston area (personal communication, Carin Martin).

There are several limitations in this study. The external transmission from Black MSM older than 34 years, women, and non-Black MSM were not included in the model. This is due to limited evidence that supports infections among YBMSM originating from these populations and high levels of racial homophily among Black MSM,^43,44 although results are somewhat mixed.⁴⁵ Ongoing extensions to the model are expanding the representation of race/ethnicities, gender identities, and age groups included. Another limitation is that the target for a functional zero is not precisely defined yet. Research on a precise statistical definition of a functional zero is underway, and such a definition will help in planning better focused policy prescriptions. We also did not have data on the frequency of anal sex among YBMSM in Houston. We did, however, have comparable information for a similar population (younger Black MSM between 18-34 years of age) in Chicago. This frequency of anal sex produced calibration outcomes that were consistent with our Houston targets. Further research on estimating this parameter in Houston could help address this gap. Additionally, our model does not take into account expanded coverage that may exist from local safety-net programs, such as financial assistance or sliding scale medical care through Federally Qualified Health Centers (FQHC) or Harris Health System’s Financial Assistance Program.⁴⁶

Improved ART and PrEP engagement have shown promise in reducing HIV transmission in a number of U.S. populations that bear a disproportionate burden of the epidemic. Expanding Medicaid, as a number of states have already done, may help substantially reduce the burden of HIV among underserved populations in Houston and throughout Texas. Recently announced, the federal mandate that nearly all medical insurers must eliminate cost sharing for PrEP,⁴⁷ may prompt substantial acceleration toward the goal of HIV elimination; however, without concerted efforts to reach the uninsured, this change has the potential to increase rather than to decrease the disparities in HIV incidence that disproportionately affects Black MSM. Modeling studies can continue to provide insight as updates to policies are planned and implemented.