HIV cluster detection and response (CDR) provides a framework for identifying rapid HIV transmission and guiding implementation of proven HIV prevention and care strategies. Characterizing the relative benefits of CDR is important for guiding policy makers in resource allocation for HIV prevention. We sought to understand how many HIV infections would need to be averted by CDR activities to achieve various return-on-investment (ROI) thresholds. We conducted an ROI analysis of CDR in 2022, incorporating costs and benefits across US jurisdictions funded for HIV surveillance and prevention. Setting ROI thresholds between 1 and 5, we estimated the number of HIV infections that would need to be averted annually by CDR activities to reach ROI thresholds. A scenario was considered cost saving if the ROI > 1. Based on the number of people in national priority molecular clusters and estimated transmission in these clusters, we determined the percent reduction in transmission within these clusters that would be required to achieve the threshold number of HIV infections averted. The number of HIV infections needing to be averted annually ranged from 19 infections (ROI = 1) to 94 infections (ROI = 5). Among 657 HIV transmissions within national priority molecular clusters, the percent reduction in HIV transmission needed to meet ROI thresholds ranged from 2.9% (ROI = 1) to 14.3% (ROI = 5). In conclusion, CDR activities would need to avert a minimal number of HIV infections nationally to achieve cost savings.

OBJECTIVES: To determine the impact of increased long-acting injectable antiretroviral therapy (Cabotegravir-rilpivirine [CAB/RPV]) use among persons with diagnosed HIV (PWDH) with viral suppression (VLS), per 2021 US Food and Drug Administration (FDA) guidelines, on HIV incidence and levels of VLS in the US. METHODS: We used the HOPE compartmental model to simulate CAB/RPV use during 2023-2035. We first simulated a baseline scenario (no CAB/RPV), in which 69% of PWDH had VLS. We then introduced CAB/RPV in 2023 under two scenarios: (1) where CAB/RPV improved the duration of VLS post-cessation of ART use compared to oral ART; (2) where CAB/RPV additionally improved adherence. We compared cumulative 2023-35 incidence and percentage of PWDH with VLS at year-end 2035 to baseline. RESULTS: When CAB/RPV increased the duration of VLS only, cumulative incidence was reduced up to 9%, and VLS increased up to 4%. When CAB/RPV also improved ART adherence, incidence was reduced up to 19.5%, and VLS increased up to 9%. CONCLUSIONS: CAB/RPV, even if only used among PWDH with VLS, may reduce HIV incidence and increase VLS, due to longer-lasting VLS post-cessation of usage. If CAB/RPV also improves ART adherence, incidence is further reduced. Improved clinical efficacy of CAB/RPV may translate to improved population-level outcomes, even in limited use cases.

BACKGROUND: In 2019, there were an estimated 1.2 million persons with HIV (PWH) and 35,100 new infections in the United States. The HIV care continuum has a large influence on transmission dynamics. METHODS: We updated Progression and Transmission of HIV 3.0, an agent-based simulation model, to estimate 2019 HIV transmission rates and distribution of transmissions by the HIV care continuum, race/ethnicity, transmission group, and age group. RESULTS: In 2019, the estimated transmission rate in the United States was 2.94 new infections per 100 person-years (inf /100p-y). Transmission rates decreased along the HIV care continuum; the highest transmission rate was associated with persons with acute HIV infection and unaware of their HIV status at 16.35 inf /100p-y, followed by persons with HIV (non-acute) and unaware of their HIV status (9.52), persons aware of their HIV status and not in care (5.96), persons receiving HIV care (on antiretroviral therapy) but not virally suppressed (4.53), and persons virally suppressed (0). The highest transmission rate by transmission group was among men who have sex with men at 3.68 inf /100p-y. Transmission rates decreased as age increased and are similar by race/ethnicity, after accounting for the HIV care continuum. CONCLUSION: Our results support a continued emphasis on helping PWH move along the care continuum through early diagnosis, linkage to care, and adherence to ART, resulting in viral suppression to reduce HIV transmissions. Further, efforts should focus on reducing disparities in the provision of HIV prevention and care services, particularly for populations disproportionally affected by HIV.

BACKGROUND: The OraQuick In-Home HIV self-test represents a fast, inexpensive, and convenient method for users to assess their HIV status. If integrated thoughtfully into existing testing practices, accompanied by efficient pathways to formal diagnosis, self-testing could enhance both HIV awareness and reduce HIV incidence. However, currently available self-tests are less sensitive, particularly for recent infection, when compared to gold-standard laboratory tests. It is important to understand the impact if some portion of standard testing is replaced by self-tests. We used a compartmental model to evaluate the effects of self-testing in diverse scenarios among gay, bisexual and other men who have sex with men (MSM) in the United States for the period 2020-2030, and to understand which scenarios maximize the advantages of self-testing. METHODS: We introduced a novel 4-compartment model for HIV self-testing. We employed the model under different screening rates, self-test proportions, and delays to diagnosis for those identified through self-tests to determine the potential effects of self-testing on HIV incidence and awareness of status when applied to the US MSM population. We studied scenarios in which self-tests supplement laboratory-based tests, with no replacement, and scenarios in which some replacement occurs. We also examined how future improvements in self-test sensitivity may affect our results. RESULTS: When HIV self-tests are supplemental rather than substitutes for laboratory-based testing, self-testing can decrease HIV incidence among MSM in the US by up to 10 % and increase awareness of status among MSM from 85 % to 91 % over a 10-year period, provided linkage to care and formal diagnosis occur promptly following a positive self-test (90 days or less). As self-tests replace a higher percentage laboratory-based testing algorithms, increases in overall testing rates were necessary to ensure reductions in HIV incidence. However, such needed increases were relatively small (under 10 % for prompt engagement in care and moderate levels of replacement). Improvements in self-test sensitivity and/or decreases in the detection period may further reduce any necessary increases in overall testing by up to 40 %. CONCLUSIONS: If properly utilized, self-testing can provide significant long-term reductions to HIV incidence and improve awareness of HIV status. Ensuring that self-testing increases overall testing and that formal diagnosis and engagement in care occur promptly following a positive self-test are necessary to maximize the benefits of self-testing. Future improvements in self-test sensitivity and reductions in the detection period would further reduce HIV incidence and the potential risks associated with replacing laboratory tests with self-tests.

BACKGROUND: The COVID-19 pandemic impacted sexual behaviors and the HIV continuum-of-care in the United States, reducing HIV testing and diagnosis, and use of pre-exposure prophylaxis (PrEP) and antiretroviral therapy (ART). We aim to understand the future implications of these effects through a modeling study. METHODS: We first ran our compartmental model of HIV transmission in the US accounting for pandemic-related short-term changes in transmission behavior and HIV prevention and care provision in 2020-2021 only. We then ran a comparison scenario that did not apply pandemic effects but assumed a continuation of past HIV prevention and care trends. We compared results from the two scenarios through 2024. RESULTS: HIV incidence was 4·4% lower in 2020-21 for the pandemic scenario compared with the no-pandemic scenario due to reduced levels of transmission behavior, despite reductions in HIV prevention and care caused by the pandemic. However, reduced care led to less viral load suppression among people with HIV (PWH) in 2020 and, in turn, our model resulted in a slightly greater incidence of 2·0% from 2022-24 in the COVID-19 scenario, as compared to the non-COVID scenario. DISCUSSION: Disruptions in HIV prevention and care services during COVID-19 may lead to somewhat higher post-pandemic HIV incidence, than assuming pre-pandemic trends in HIV care and prevention continued. These results underscore the importance of continuing to increase HIV prevention and care efforts in the coming years.

OBJECTIVE: :COVID-19 and related disruptions led to a significant decline in HIV diagnoses in the US in 2020. A previous analysis estimated 18% fewer diagnoses than expected among persons with HIV (PWH) acquiring infection in 2019 or earlier, suggesting that the decline in overall diagnoses cannot be attributed solely to decreased transmission. This analysis evaluates the progress made towards closing the 2020 diagnosis deficit in 2021. METHODS: :We apply previously developed methods analyzing 2021 diagnosis data from the National HIV Surveillance System to determine whether 2021 diagnosis levels of PWH infected pre2020 are above or below the expected pre-COVID trends. Results are stratified by assigned sex at birth, transmission group, geographic region, and race/ethnicity. RESULTS: :In 2021, HIV diagnoses returned to pre-COVID levels among all PWH acquiring infection 2011-19. Among Hispanic/Latino PWH and males, diagnoses returned to pre-COVID levels. White PWH, men who have sex with men, and PWH living in the south and northeast showed higher-than-expected levels of diagnosis in 2021. For the remaining populations, there were fewer HIV diagnoses in 2021 than expected. CONCLUSIONS: :While overall diagnoses among persons acquiring HIV pre2020 returned to pre-COVID levels, the diagnosis gap observed in 2020 remained unclosed at the end of 2021. Fewer than expected diagnoses among certain populations indicate that COVID-19 related disruptions to HIV diagnosis trends remained in 2021. Although some groups showed higher-than-expected levels of diagnoses, such increases were smaller than corresponding 2020 decreases. Expanded testing programs designed to close these gaps are essential.

BACKGROUND: Whether the COVID-19 pandemic has had a disproportionate impact on mortality among persons with diagnosed HIV (PWDH) in United States is unclear. Through our macro-scale analysis, we seek to better understand how the COVID-19 pandemic affected mortality among PWDH. METHODS: We obtained mortality and population data for the years 2018-2020 from the National HIV Surveillance System (NHSS) for the U.S. PWDH population, and from publicly available data for the general population. We computed mortality rates and excess mortality for both the general and PWDH populations. Stratifications by age, race/ethnicity, and sex were considered. For each group, we determined whether the 2020 mortality rates and mortality risk ratio showed a statistically significant change from 2018-2019. RESULTS: Approximately 1550 excess deaths occurred among PWDH in 2020, with Black, Hispanic/Latino and PWDH 55 and older comprising the majority of excess deaths. Mortality rates increased in 2020 from 2018-2019 across the general population in all groups. Among PWDH, mortality rates either increased, or showed no statistically significant change. These increases were similar to, or smaller than, those observed in the general population, resulting in a 7.7% decrease in the mortality risk ratio between PWDH and the general population. CONCLUSIONS: While mortality rates among PWDH increased in 2020 relative to 2018-2019, the increases were smaller, or of similar magnitude, to those observed in the general population. We thus do not find evidence of elevated mortality risk from the COVID-19 pandemic among PWDH. These findings held across subpopulations stratified by age, sex, and racial/ethnic group.

BACKGROUND: Cost-effectiveness analysis of HIV self-testing using patient-level data from a randomized clinical trial can inform HIV prevention funding decisions. Cost-effectiveness analysis using net benefit regression addresses the sampling uncertainty in the trial data and the variability of policymakers' willingness to pay (WTP). METHODS: We used published data from a 12-month longitudinal randomized clinical trial that enrolled 2665 men who sex with men (MSM) randomly assigned to the self-testing arm (participants receiving self-test kits) and control arm (participants receiving standard-of-care), and the self-testing arm identified 48 additional new HIV cases. We used net benefit regression to investigate the cost-effectiveness of an HIV self-testing intervention, which compared the incremental cost per new HIV diagnosis with policymakers' WTP thresholds. We addressed the uncertainties in estimating the incremental cost and the policymakers' WTP per new diagnosis through the incremental net benefit (INB) regression and cost-effectiveness acceptability curve (CEAC) analyses. RESULTS: From the healthcare provider's perspective, the INB analysis showed a positive net-benefit of HIV self-testing compared to standard-of-care when policymakers' WTP per new HIV diagnosis was $9,365 (95% CI: $5,700 - $25,500) or higher. The CEAC showed that the probability of HIV self-testing being cost-effective compared to standard-of-care was 58% and >99% at a WTP of $10 000 and $50 000 per new HIV diagnosis, respectively. CONCLUSION: The INB and CEAC analyses suggest that HIV self-testing has the potential to be cost-effective for relatively low values of policymakers' WTP.

Background: Whether COVID-19 has had a disproportionate impact on mortality among persons with diagnosed HIV (PWDH) in United States is unclear. Through our macro-scale analysis, we seek to better understand how COVID-19 and subsequent behavioral changes affected mortality among PWDH. Method(s): We obtained mortality and population size data for the years 2018-2020 from the National HIV Surveillance System (NHSS) for the PWDH population aged >=13 years in the United States, and from publicly available data for the general population. We computed mortality rates and excess mortality for both the general and PWDH populations. Stratifications by age, race/ethnicity, and sex-at birth were considered. For each group, we determined whether the 2020 mortality rates and mortality risk ratio showed a statistically significant change from 2018-2019. Result(s): Mortality rates increased in 2020 from 2018-2019 across the general population in all groups. Among PWDH, mortality rates either increased, or showed no statistically significant change. The mortality risk ratio between PWDH and the general population decreased 7.7% in 2020. Approximately 1550 excess deaths occurred among PWDH in 2020, with Black, Hispanic/Latino and PWDH above 55 and older representing the majority of excess deaths. Conclusion(s): While mortality rates among PWDH increased in 2020 relative to 2018-2019, the increases were smaller than those observed in the general population. This suggests that COVID-19 and resulting behavioral changes among PWDH did not result in disproportionate mortality among PWDH. These findings suggest that COVID-19, and any associated indirect effects, do not represent a proportionally greater risk for PWDH compared to the general population. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Background: Diagnoses of HIV in the US decreased by 17% in 2020 due to COVID-related disruptions. The extent to which this decrease is attributable to changes in HIV testing versus HIV transmission is unclear. We seek to better understand this issue by analyzing the discrepancy in expected versus observed HIV diagnoses in 2020 among persons who acquired HIV between 2010-2019, as changes in diagnosis patterns in this cohort cannot be attributed to changes in transmission. Method(s): We developed three methods based on the CD4-depletion model to estimate excess missed diagnoses in 2020 among persons with HIV (PWH) infected from 2010-2019. We stratified the results by transmission group, sex assigned at birth, race/ethnicity, and region to examine differences by group and confirm the reliability of our estimates. We performed similar analyses projecting diagnoses in 2019 among PWH infected from 2010-2018 to evaluate the accuracy of our methods against surveillance data. Result(s): There were approximately 3100-3300 (approximately 18%) fewer diagnoses than expected in 2020 among PWH infected from 2010-2019. Females (at birth), heterosexuals, persons who inject drugs, and Hispanic/Latino PWH missed diagnoses at higher levels than the overall population. Validation and stratification analyses confirmed the accuracy and reliability of our estimates. Conclusion(s): The substantial drop in number of previously infected PWH diagnosed in 2020, suggests that changes in testing played a substantial role in the observed decrease. Levels of missed diagnoses differed substantially across population subgroups. Increasing testing efforts and innovative strategies to reach undiagnosed PWH are needed to offset this diagnosis gap. These analyses may be used to inform future estimates of HIV transmission during the COVID-19 pandemic. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

OBJECTIVE: Depression is prevalent among persons with HIV (PWH) and is associated with poorer adherence and lack of viral load suppression (VLS). When treated for depression, PWH are more likely to stay in HIV care and adhere to medications; however, for many PWH, depression is not adequately diagnosed or treated. We adapted Progression and Transmission of HIV (PATH 3.0), a U.S. agent-based dynamic stochastic simulation model, by incorporating a continuum of depression care and estimating the impact on VLS of an enhanced depression diagnosis and care scenario (EDC). METHODS: We compared EDC-whereby every PWH is assessed for depression, gets treatment if diagnosed, and of those, half achieve remission-to a status quo scenario (SQ) on VLS. Based on published findings, assumptions for SQ were: 34.7% depressed, 45% diagnosed, 55.3% treated and 33% of treated achieving remission. Compared to PWH without depression, we assumed the probability of being non-virally suppressed increased by 1.57 times for PWH with depression (PWH-D), and by 0.95 times for PWH with remitted depression. RESULTS: There was an average increase of 14.6% (11.5-18.5) in the proportion of PWH-D who achieved VLS in EDC compared to SQ. Among all PWH, there was a 4.7% (3.4-6.0) increase in the proportion who achieved VLS in EDC compared to SQ. CONCLUSIONS: Fully diagnosing and adequately treating depression would improve health and quality of life for a substantial proportion of PWH-D and result in a nearly 5% increase in expected rates of VLS in the United States, supporting national prevention goals.

BACKGROUND: Diagnoses of HIV in the United States decreased by 17% in 2020 due to COVID-related disruptions. The extent to which this decrease is attributable to changes in HIV testing versus HIV transmission is unclear. We seek to better understand this issue by analyzing the discrepancy in expected versus observed HIV diagnoses in 2020 among persons who acquired HIV between 2010 and 2019 because changes in diagnosis patterns in this cohort cannot be attributed to changes in transmission. METHODS: We developed 3 methods based on the CD4-depletion model to estimate excess missed diagnoses in 2020 among persons with HIV (PWH) infected from 2010 to 2019. We stratified the results by transmission group, sex assigned at birth, race/ethnicity, and region to examine differences by group and confirm the reliability of our estimates. We performed similar analyses projecting diagnoses in 2019 among PWH infected from 2010 to 2018 to evaluate the accuracy of our methods against surveillance data. RESULTS: There were approximately 3100-3300 (approximately 18%) fewer diagnoses than expected in 2020 among PWH infected from 2010 to 2019. Females (at birth), heterosexuals, persons who inject drugs, and Hispanic/Latino PWH missed diagnoses at higher levels than the overall population. Validation and stratification analyses confirmed the accuracy and reliability of our estimates. CONCLUSIONS: The substantial drop in number of previously infected PWH diagnosed in 2020 suggests that changes in testing played a substantial role in the observed decrease. Levels of missed diagnoses differed substantially across population subgroups. Increasing testing efforts and innovative strategies to reach undiagnosed PWH are needed to offset this diagnosis gap. These analyses may be used to inform future estimates of HIV transmission during the COVID-19 pandemic.

We used an agent-based simulation model (Progression and Transmission of HIV) to follow for 20 years a cohort of persons in the United States infected with HIV in 2015. We assessed the benefits of reducing the delay between HIV infection and diagnosis and increasing adherence to HIV care and treatment on the percent of persons surviving 20 years after infection, average annual HIV transmission rates, and time spent virally suppressed. We examined average diagnosis delays of 1.0-7.0 years, monthly care drop-out rates of 5% to 0.1%, and combinations of these strategies. The percent of the cohort surviving the first 20 years of infection varied from 70.8% to 77.5%, and the annual transmission risk, from 1.5 to 5.2 HIV transmissions per 100 person-years. Thus, individuals can enhance their survival and reduce their risk of transmission to partners by frequent testing for HIV and adhering to care and treatment.

BACKGROUND: A goal of the US Department of Health and Human Services' Ending the HIV Epidemic (EHE) in the United States initiative is to reduce the annual number of incident HIV infections in the United States by 75% within 5 years and by 90% within 10 years. We developed a resource allocation analysis to understand how these goals might be met. METHODS: We estimated the current annual societal funding [$2.8 billion (B)/yr] for 14 interventions to prevent HIV and facilitate treatment of infected persons. These interventions included HIV testing for different transmission groups, HIV care continuum interventions, pre-exposure prophylaxis, and syringe services programs. We developed scenarios optimizing or reallocating this funding to minimize new infections, and we analyzed the impact of additional EHE funding over the period 2021-2030. RESULTS: With constant current annual societal funding of $2.8 B/yr for 10 years starting in 2021, we estimated the annual incidence of 36,000 new cases in 2030. When we added annual EHE funding of $500 million (M)/yr for 2021-2022, $1.5 B/yr for 2023-2025, and $2.5 B/yr for 2026-2030, the annual incidence of infections decreased to 7600 cases (no optimization), 2900 cases (optimization beginning in 2026), and 2200 cases (optimization beginning in 2023) in 2030. CONCLUSIONS: Even without optimization, significant increases in resources could lead to an 80% decrease in the annual HIV incidence in 10 years. However, to reach both EHE targets, optimization of prevention funding early in the EHE period is necessary. Implementing these efficient allocations would require flexibility of funding across agencies, which might be difficult to achieve.

In 2018, the U.S. Public Health Service (USPHS) published updated clinical guidelines for the use of preexposure prophylaxis (PrEP) to reduce the risk of HIV infection among men who have sex with men (MSM), heterosexual women and men, and persons who inject drugs.1 PrEP is one of the main tools being used to achieve the Ending the HIV Epidemic in the U.S. incidence-reduction goals.2 Thus, policy makers need accurate estimates of the number of U.S. adults having indications for PrEP.

CONTEXT: The reproduction number is a fundamental epidemiologic concept used to assess the potential spread of infectious diseases and whether they can be eliminated. OBJECTIVE: We estimated the 2017 United States HIV effective reproduction number, Re, the average number of secondary infections from an infected person in a partially infected population. We analyzed the potential effects on Re of interventions aimed at improving patient flow rates along different stages of the HIV care continuum. We also examined these effects by individual transmission groups. DESIGN: We used the HIV Optimization and Prevention Economics (HOPE) model, a compartmental model of disease progression and transmission, and the next-generation matrix method to estimate Re. We then projected the impact of changes in HIV continuum-of-care interventions on the continuum-of-care flow rates and the estimated Re in 2020. SETTING: United States. PARTICIPANTS: The HOPE model simulated the sexually active US population and persons who inject drugs, aged 13 to 64 years, which was stratified into 195 subpopulations by transmission group, sex, race/ethnicity, age, male circumcision status, and HIV risk level. MAIN OUTCOME MEASURES: The estimated value of Re in 2017 and changes in Re in 2020 from interventions affecting the continuum-of-care flow rates. RESULTS: Our estimated HIV Re in 2017 was 0.92 [0.82, 0.94] (base case [min, max across calibration sets]). Among the interventions considered, the most effective way to reduce Re substantially below 1.0 in 2020 was to maintain viral suppression among those receiving HIV treatment. The greatest impact on Re resulted from changing the flow rates for men who have sex with men (MSM). CONCLUSIONS: Our results suggest that current prevention and treatment efforts may not be sufficient to move the country toward HIV elimination. Reducing Re to substantially below 1.0 may be achieved by an ongoing focus on early diagnosis, linkage to care, and sustained viral suppression especially for MSM.

We present the Progression and Transmission of HIV (PATH 4.0), a simulation tool for analyses of cluster detection and intervention strategies. Molecular clusters are groups of HIV infections that are genetically similar, indicating rapid HIV transmission where HIV prevention resources are needed to improve health outcomes and prevent new infections. PATH 4.0 was constructed using a newly developed agent-based evolving network modeling (ABENM) technique and evolving contact network algorithm (ECNA) for generating scale-free networks. ABENM and ECNA were developed to facilitate simulation of transmission networks for low-prevalence diseases, such as HIV, which creates computational challenges for current network simulation techniques. Simulating transmission networks is essential for studying network dynamics, including clusters. We validated PATH 4.0 by comparing simulated projections of HIV diagnoses with estimates from the National HIV Surveillance System (NHSS) for 2010-2017. We also applied a cluster generation algorithm to PATH 4.0 to estimate cluster features, including the distribution of persons with diagnosed HIV infection by cluster status and size and the size distribution of clusters. Simulated features matched well with NHSS estimates, which used molecular methods to detect clusters among HIV nucleotide sequences of persons with HIV diagnosed during 2015-2017. Cluster detection and response is a component of the U.S. Ending the HIV Epidemic strategy. While surveillance is critical for detecting clusters, a model in conjunction with surveillance can allow us to refine cluster detection methods, understand factors associated with cluster growth, and assess interventions to inform effective response strategies. As surveillance data are only available for cases that are diagnosed and reported, a model is a critical tool to understand the true size of clusters and assess key questions, such as the relative contributions of clusters to onward transmissions. We believe PATH 4.0 is the first modeling tool available to assess cluster detection and response at the national-level and could help inform the national strategic plan. © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)

BACKGROUND: Lifetime cost estimates are a useful tool in measuring the economic burden of HIV in the United States. Previous estimation methods need to be updated, given improving antiretroviral therapy regimens and updated costs. METHODS: We used an updated version of the agent-based model Progression and Transmission of HIV (PATH) 3.0 to reflect current regimens and costs. We simulated a cohort of those infected in 2015 until the last person had died to track the lifetime costs for treatment of HIV, including HIV health care utilization costs (inpatient, outpatient, opportunistic infection (OI) prophylaxis, non-HIV medication, and emergency department), OI treatment costs, and testing costs. We assumed a median per-person diagnosis delay of 3 years and a 3% base monthly probability of dropout from care for a base-case scenario. Additionally, we modeled a most-favorable scenario (median diagnosis delay of 1 year and 1% base dropout rate) and a least-favorable scenario (median diagnosis delay of 5 years and 5% base dropout rate). RESULTS: We estimated an average lifetime HIV-related medical cost for a person with HIV of $420,285 (2019 US$) discounted (3%) and $1,079,999 undiscounted for a median 3-year diagnosis delay and 3% base dropout rate. Our discounted cost estimate was $490,045 in our most-favorable scenario and $326,411 in our least-favorable scenario. CONCLUSIONS: Lifetime per-person HIV-related medical costs depend on the time from infection to diagnosis and the likelihood of dropping out of care. Our results, which are similar to previous studies, reflect updated ART regimens and costs for HIV treatment.

BACKGROUND: The purpose of this study was to estimate the number and lifetime medical cost of HIV infections attributable to incident sexually transmitted infections (STIs) in the United States in 2018. METHODS: We combined data from published models regarding the number or percentage of HIV infections attributable to STIs with updated estimates of the lifetime medical cost per HIV infection. We used two distinct calculation methods. Our first calculation used recent estimates of the percentage of HIV infections in men who have sex with men (MSM) attributable to gonorrhea and chlamydia. Our second calculation, based on older studies, used estimates of the expected number of STI-attributable HIV infections per new STI infection, for gonorrhea, chlamydia, syphilis, and trichomoniasis. RESULTS: Our first calculation method suggested that 2,489 (25th-75th percentile: 1,895-3,000) HIV infections in 2018 among MSM could be attributed to gonorrhea and chlamydia, at an estimated lifetime medical cost of $1.05 billion (25th-75th percentile: $0.79-1.26 billion). Our second calculation method suggested that 2,349 (25th-75th percentile: 1,948-2,744) HIV infections in the general population (including MSM) could be attributed to chlamydia, gonorrhea, syphilis, and trichomoniasis acquired in 2018, at an estimated lifetime medical cost of $0.99 billion (25th-75th percentile: $0.80-1.16 billion). CONCLUSIONS: Despite ambiguity regarding the degree to which STIs affect HIV transmission, our combination of data from published STI/HIV transmission models and an HIV lifetime medical cost model can help to quantify the estimated burden of STI-attributable HIV infections in the United States.

BACKGROUND: We estimated the lifetime medical costs attributable to STIs acquired in 2018, including sexually acquired HIV. METHODS: We estimated the lifetime medical costs of infections acquired in 2018 in the United States for eight STIs: chlamydia, gonorrhea, trichomoniasis, syphilis, genital herpes, human papillomavirus (HPV), hepatitis B, and HIV. We limited our analysis to lifetime medical costs incurred for treatment of STIs and for treatment of related sequelae; we did not include other costs such as STI prevention. For each STI except HPV, we calculated the lifetime medical cost by multiplying the estimated number of incident infections in 2018 by the estimated lifetime cost per infection. For HPV, we calculated the lifetime cost based on the projected lifetime incidence of health outcomes attributed to HPV infections acquired in 2018. Future costs were discounted at 3% annually. RESULTS: Incident STIs in 2018 imposed an estimated $15.9 billion (25th-75th percentile: $14.9-16.9 billion) in discounted, lifetime direct medical costs (2019 U.S. dollars). Most of this cost was due to sexually acquired HIV ($13.7 billion) and HPV ($0.8 billion). STIs in women accounted for about one-fourth of the cost of incident STIs when including HIV, but about three-fourths when excluding HIV. STIs among 15-24-year-olds accounted for $4.2 billion (26%) of the cost of incident STIs. CONCLUSIONS: Incident STIs continue to impose a considerable lifetime medical cost burden in the United States. These results can inform health economic analyses to promote the use of cost-effective STI prevention interventions to reduce this burden.

OBJECTIVE: To estimate the optimal allocation of Centers for Disease Control and Prevention (CDC) HIV prevention funds for health departments in 52 jurisdictions, incorporating Health Resources and Services Administration (HRSA) Ryan White HIV/AIDS Program funds, to improve outcomes along the HIV care continuum and prevent infections. METHODS: Using surveillance data from 2010 to 2012 and budgetary data from 2012, we divided the 52 health departments into 5 groups varying by number of persons living with diagnosed HIV (PLWDH), median annual CDC HIV prevention budget, and median annual HRSA expenditures supporting linkage to care, retention in care, and adherence to antiretroviral therapy. Using an optimization and a Bernoulli process model, we solved for the optimal CDC prevention budget allocation for each health department group. The optimal allocation distributed the funds across prevention interventions and populations at risk for HIV to prevent the greatest number of new HIV cases annually. RESULTS: Both the HIV prevention interventions funded by the optimal allocation of CDC HIV prevention funds and the proportions of the budget allocated were similar across health department groups, particularly those representing the large majority of PLWDH. Consistently funded interventions included testing, partner services and linkage to care and interventions for men who have sex with men (MSM). Sensitivity analyses showed that the optimal allocation shifted when there were differences in transmission category proportions and progress along the HIV care continuum. CONCLUSION: The robustness of the results suggests that most health departments can use these analyses to guide the investment of CDC HIV prevention funds into strategies to prevent the most new cases of HIV.

BACKGROUND: The effect of improving diagnosis, care, and treatment of persons living with HIV (PLWH) on PrEP effectiveness in the United States has not be well established. METHODS: We used a dynamic, compartmental model that simulates the sexually active US population. We investigated the change in cumulative HIV incidence from 2016 to 2020 for three HIV care continuum levels, and the marginal benefit of PrEP compared with each. We also explored the marginal benefit of PrEP for individual risk groups, and as PrEP adherence, coverage and dropout rates varied. RESULTS: Delivering PrEP in 2016 to persons at high risk of acquiring HIV resulted in an 18.1% reduction in new HIV infections from 2016 to 2020 under current care continuum levels. Achieving HIV national goals of 90% of PLWH with diagnosed infection, 85% of newly diagnosed PLWH linked to care at diagnosis, and 80% of diagnosed PLWH virally suppressed reduced cumulative incidence by 34.4%. Delivery of PrEP in addition to this scenario resulted in a marginal benefit of 11.1% additional infections prevented. When national goals were reached, PrEP prevented an additional 15.2% cases among men who have sex with men (MSM), 3.9% among heterosexuals, and 3.8% among persons who inject drugs. CONCLUSIONS: The marginal benefit of PrEP was larger when current HIV care continuum percentages were maintained, but continued to be substantial even when national care goals were met. The high-risk MSM population was the chief beneficiary of PrEP.

CONTEXT: Human immunodeficiency virus (HIV) incidence and prevalence in the United States are characterized by significant disparities by race/ethnicity. National HIV care goals, such as boosting to 90% the proportion of persons whose HIV is diagnosed and increasing to 80% the proportion of persons living with diagnosed HIV who are virally suppressed, will likely reduce HIV incidence, but their effects on HIV-related disparities are uncertain. OBJECTIVE: We sought to understand by race/ethnicity how current HIV care varies, the level of effort required to achieve national HIV care goals, and the effects of reaching those goals on HIV incidence and disparities. DESIGN: Using a dynamic model of HIV transmission, we identified 2016 progress along the HIV care continuum among blacks, Hispanics, and whites/others compared with national 2020 goals. We examined disparities over time. SETTING: United States. PARTICIPANTS: Beginning in 2006, our dynamic compartmental model simulated the sexually active US population 13 to 64 years of age, which was stratified into 195 subpopulations by transmission group, sex, race/ethnicity, age, male circumcision status, and HIV risk level. MAIN OUTCOME MEASURE: We compared HIV cumulative incidence from 2016 to 2020 when goals were reached compared with base case assumptions about progression along the HIV care continuum. RESULTS: The 2016 proportion of persons with diagnosed HIV who were on treatment and virally suppressed was 50% among blacks, 56% among Hispanics, and 61% among whites/others, compared with a national goal of 80%. When diagnosis, linkage, and viral suppression goals were reached in 2020, cumulative HIV incidence fell by 32% (uncertainty range: 18%-37%) for blacks, 25% (22%-31%) for Hispanics, and 25% (21%-28%) for whites/others. Disparity measures changed little. CONCLUSIONS: Achieving national HIV care goals will require different levels of effort by race/ethnicity but likely will result in substantial declines in cumulative HIV incidence. HIV-related disparities in incidence and prevalence may be difficult to resolve.

OBJECTIVE: Analyzing HIV care service targets for achieving a national goal of a 25% reduction in annual HIV incidence and evaluating the use of annual HIV diagnoses to measure progress in incidence reduction. DESIGN: Because there are considerable interactions among HIV care services, we model the dynamics of combinations of increases in HIV care continuum targets to identify those that would achieve 25% reductions in annual incidence and diagnoses. METHODS: We used Progression and Transmission of HIV/AIDS (PATH 2.0), an agent-based dynamic stochastic simulation of HIV in the United States. RESULTS: A 25% reduction in annual incidence could be achieved by multiple alternative combinations of percentages of persons with diagnosed infection and persons with viral suppression including 85% and 68%, respectively, and 90% and 59%, respectively. The first combination corresponded to an 18% reduction in annual diagnoses, and infections being diagnosed at a median CD4 count of 372 cells/muL or approximately 3.8 years from time of infection. The corresponding values on the second combination are 4%, 462 cells/muL, and 2.0 years, respectively. CONCLUSIONS: Our analysis provides policy makers with specific targets and alternative choices to achieve the goal of a 25% reduction in HIV incidence. Reducing annual diagnoses does not equate to reducing annual incidence. Instead, progress toward reducing incidence can be measured by monitoring HIV surveillance data trends in CD4 count at diagnosis along with the proportion who have achieved viral suppression to determine where to focus local programmatic efforts.

BACKGROUND: HIV transmission is the result of complex dynamics in the risk behaviors, partnership choices, disease stage and position along the HIV care continuum-individual characteristics that themselves can change over time. Capturing these dynamics and simulating transmissions to understand the chief sources of transmission remain important for prevention. METHODS: The Progression and Transmission of HIV/AIDS (PATH 2.0) is an agent-based model of a sample of 10,000 people living with HIV (PLWH), who represent all men who have sex with men (MSM) and heterosexuals living with HIV in the U.S.A. Persons uninfected were modeled as populations, stratified by risk and gender. The model included detailed individual-level data from several large national surveillance databases. The outcomes focused on average annual transmission rates from 2008 through 2011 by disease stage, HIV care continuum, and sexual risk group. RESULTS: The relative risk of transmission of those in the acute phase was nine-times [5th and 95th percentile simulation interval (SI): 7, 12] that of those in the non-acute phase, although, on average, those with acute infections comprised 1% of all PLWH. The relative risk of transmission was 24- to 50-times as high for those in the non-acute phase who had not achieved viral load suppression as compared with those who had. The relative risk of transmission among MSM was 3.2-times [SI: 2.7, 4.0] that of heterosexuals. Men who have sex with men and women generated 46% of sexually acquired transmissions among heterosexuals. CONCLUSIONS: The model results support a continued focus on early diagnosis, treatment and adherence to ART, with an emphasis on prevention efforts for MSM, a subgroup of whom appear to play a role in transmission to heterosexuals.

An estimated 1.2 million people aged 13 years and older are living with human immunodeficiency virus (HIV) infection in the United States1, and approximately 45,000 people are newly diagnosed with the virus each year.2 Over the last 30 years, condom use has been a key element of comprehensive approaches to HIV prevention.3–9 For instance, the National HIV/AIDS Strategy for the United States 2010 (updated in 2015) calls for promotion of condom use in combination with other prevention approaches.10 Condom distribution campaigns, a frequently used public health intervention, make condoms freely available in settings frequented by people believed to be at high risk of transmitting or acquiring HIV. However, data regarding the effectiveness of condom distribution campaigns remain limited due to several methodological challenges. Knowledge of the strength of evidence of condom distribution campaign effectiveness is important for priority setting and the efficient allocation of HIV prevention resources among competing interventions.11–13 This paper examines limitations in the literature regarding condom distribution campaigns and the difficulties in estimating the effectiveness of campaigns through observational studies and mathematical modeling.

INTRODUCTION: The purpose of this study was to assess and compare the cost effectiveness of current HIV prevention interventions in the U.S. using a consistent, standardized methodology. METHODS: The cost effectiveness of common and emerging HIV biomedical and behavioral prevention interventions as delivered to men who have sex with men, injection drug users, and sexually active heterosexuals was estimated. Data on program costs, intervention efficacy, risk behaviors, and per contact transmission probabilities were collected from peer-reviewed papers and health department reports. These data were combined with 2010 national HIV incidence and prevalence surveillance data in a Bernoulli process model to estimate the reduced annual risk of HIV transmission or acquisition associated with these interventions. The cost per prevented case of HIV and the cost per saved quality-adjusted life year were then calculated. Analyses were conducted between 2014 and 2015. RESULTS: Interventions to diagnose HIV and provide ongoing care and treatment had the lowest cost per prevented case. Among interventions targeted at specific risk groups, interventions for men who have sex with men were the most cost effective. The least cost-effective interventions typically addressed people at risk of acquiring HIV rather than those at risk of transmitting the disease. CONCLUSIONS: HIV prevention interventions targeted at high-risk populations, those associated with the care continuum, and those that reduce the transmission risk of HIV-infected people are typically the most cost effective. Decision makers can consider these results in planning an efficient allocation of HIV prevention resources.

The effects of HIV infection on national labor-force participation have not been rigorously evaluated. Using data from the Medical Monitoring Project and the National Health Interview Survey, we present nationally representative estimates of the receipt of disability benefits by adults living with HIV receiving care compared with the general US adult population. We found that in 2009, adults living with HIV were nine times more likely than adults in the general population to receive disability benefits. The risk of being on disability is also greater for younger and more educated adults living with HIV compared to the general population, which suggests that productivity losses can result from HIV infection. To prevent disability, early diagnosis and treatment of HIV are essential. This study offers a baseline against which to measure the impacts of recently proposed or enacted changes to Medicaid and private insurance markets, including the Affordable Care Act and proposed revisions to the Social Security Administration's HIV Infection Listings.

PURPOSE: Data showing a high incidence of HIV infection among men who have sex with men (MSM) who had annual testing suggest that more frequent HIV testing may be warranted. Testing technology is also a consideration given the availability of sensitive testing modalities as well as the increased use of less sensitive rapid, point-of-care antibody tests. We assessed the cost-effectiveness of HIV testing of MSM and injection drug users (IDUs) at 3- and 6-month intervals using fourth-generation and rapid tests. METHODS: We used a published mathematical model of HIV transmission to evaluate testing intervals for each population using cohorts of 10,000 MSM and IDU. We incorporated HIV transmissions averted due to serostatus awareness and viral suppression. We included costs for HIV testing and treatment initiation, as well as treatment costs saved from averted transmissions. RESULTS: For MSM, HIV testing was cost-saving or cost-effective over a 1-year time period for both 6-month compared to annual testing, and quarterly compared to 6-month testing using either test. Testing IDU every 6 months compared to annually was moderately cost-effective over a 1-year time period with a fourth-generation test, while testing with rapid, point-of care tests or quarterly was not cost-effective. MSM results remained robust in sensitivity analysis, while IDU results were sensitive to changes in HIV incidence and continuum-of-care parameters. Threshold analyses on costs suggested additional implementation costs could be incurred for more frequent testing for MSM while remaining cost-effective. CONCLUSION: HIV testing of MSM as frequently as quarterly is cost-effective compared to annual testing, but testing IDU more frequently than annually is generally not cost-effective.

OBJECTIVE: To develop a resource allocation model to optimize health departments' Centers for Disease Control and Prevention (CDC)-funded HIV prevention budgets to prevent the most new cases of HIV infection and to evaluate the model's implementation in 4 health departments. DESIGN, SETTINGS, AND PARTICIPANTS: We developed a linear programming model combined with a Bernoulli process model that allocated a fixed budget among HIV prevention interventions and risk subpopulations to maximize the number of new infections prevented. The model, which required epidemiologic, behavioral, budgetary, and programmatic data, was implemented in health departments in Philadelphia, Chicago, Alabama, and Nebraska. MAIN OUTCOME MEASURES: The optimal allocation of funds, the site-specific cost per case of HIV infection prevented rankings by intervention, and the expected number of HIV cases prevented. RESULTS: The model suggested allocating funds to HIV testing and continuum-of-care interventions in all 4 health departments. The most cost-effective intervention for all sites was HIV testing in nonclinical settings for men who have sex with men, and the least cost-effective interventions were behavioral interventions for HIV-negative persons. The pilot sites required 3 to 4 months of technical assistance to develop data inputs and generate and interpret the results. Although the sites found the model easy to use in providing quantitative evidence for allocating HIV prevention resources, they criticized the exclusion of structural interventions and the use of the model to allocate only CDC funds. CONCLUSIONS: Resource allocation models have the potential to improve the allocation of limited HIV prevention resources and can be used as a decision-making guide for state and local health departments. Using such models may require substantial staff time and technical assistance. These model results emphasize the allocation of CDC funds toward testing and continuum-of-care interventions and populations at highest risk of HIV transmission.