Assessing the Impact of COVID-19 on HIV Outcomes in the United States: A Modeling Study.

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 preexposure prophylaxis and antiretroviral therapy. We aimed to understand the future implications of these effects through a modeling study. METHODS: We first ran our compartmental model of HIV transmission in the United States accounting for pandemic-related short-term changes in transmission behavior and HIV prevention and care provision in 2020 to 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 2 scenarios through 2024. RESULTS: HIV incidence was 4·4% lower in 2020 to 2021 for the pandemic scenario compared with the no-pandemic scenario because of 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 in 2020, and in turn, our model resulted in a slightly greater incidence of 2·0% from 2022 to 2024 in the COVID-19 scenario, as compared with the non-COVID scenario. DISCUSSION: Disruptions in HIV prevention and care services during COVID-19 may lead to somewhat higher postpandemic HIV incidence than assuming prepandemic 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.

Assessing the individual benefits of reducing HIV diagnosis delay and increasing adherence to HIV care and treatment.

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.

Optimizing HIV Prevention Efforts to Achieve EHE Incidence Targets.

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.

Estimated Lifetime HIV-Related Medical Costs in the United States.

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 prophylaxis, non-HIV medication, and emergency department), opportunistic infection 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 antiretroviral therapy regimens and costs for HIV treatment.

Optimal Allocation of Societal HIV Prevention Resources to Reduce HIV Incidence in the United States.

Objectives. To optimize combined public and private spending on HIV prevention to achieve maximum reductions in incidence.Methods. We used a national HIV model to estimate new infections from 2018 to 2027 in the United States. We estimated current spending on HIV screening, interventions that move persons with diagnosed HIV along the HIV care continuum, pre-exposure prophylaxis, and syringe services programs. We compared the current funding allocation with 2 optimal scenarios: (1) a limited-reach scenario with expanded efforts to serve eligible persons and (2) an ideal, unlimited-reach scenario in which all eligible persons could be served.Results. A continuation of the current allocation projects 331 000 new HIV cases over the next 10 years. The limited-reach scenario reduces that number by 69%, and the unlimited reach scenario by 94%. The most efficient funding allocations resulted in prompt diagnosis and sustained viral suppression through improved screening of high-risk persons and treatment adherence support for those infected.Conclusions. Optimal allocations of public and private funds for HIV prevention can achieve substantial reductions in new infections. Achieving reductions of more than 90% under current funding will require that virtually all infected receive sustained treatment.

A mathematical model to estimate the state-specific impact of the Health Resources and Services Administration's Ryan White HIV/AIDS Program.

BACKGROUND: Access to and engagement in high-quality HIV medical care and treatment is essential for ending the HIV epidemic. The Health Resources and Services Administration's (HRSA) Ryan White HIV/AIDS Program (RWHAP) plays a critical role in ensuring that people living with diagnosed HIV (PLWH) are linked to and consistently engaged in high quality care and receive HIV medication in a timely manner. State variation in HIV prevalence, the proportion of PLWH served by the RWHAP, and local health care environments could influence the state-specific impact of the RWHAP. This analysis sought to measure the state-specific impact of the RWHAP on the HIV service delivery system and health outcomes for PLWH, and presents template language to communicate this impact for state planning and stakeholder engagement. METHODS AND FINDINGS: The HRSA's HIV/AIDS Bureau (HAB) and the Centers for Disease Control and Prevention's Division of HIV/AIDS Prevention (CDC DHAP) have developed a mathematical model to estimate the state-specific impact of the RWHAP. This model was parameterized using RWHAP data, HIV surveillance data, an existing CDC model of HIV transmission and disease progression, and parameters from the literature. In this study, the model was used to analyze the hypothetical scenario of an absence of the RWHAP and to calculate the projected impact of this scenario on RWHAP clients, RWHAP-funded providers, mortality, new HIV cases, and costs compared with the current state inclusive of the RWHAP. To demonstrate the results of the model, we selected two states, representing high HIV prevalence and low HIV prevalence areas. These states serve to demonstrate the functionality of the model and how state-specific results can be translated into a state-specific impact statement using template language. CONCLUSIONS: In the example states presented, the RWHAP provides HIV care, treatment, and support services to a large proportion of PLWH in each state. The absence of the RWHAP in these states could result in substantially more deaths and HIV cases than currently observed, resulting in considerable lifetime HIV care and treatment costs associated with additional HIV cases. State-specific impact statements may be valuable in the development of state-level HIV prevention and care plans or for communications with planning bodies, state health department leadership, and other stakeholders. State-specific impact statements will be available to RWHAP Part B recipients upon request from HRSA's HIV/AIDS Bureau.

Projected Cancer Incidence Rates and Burden of Incident Cancer Cases in HIV-Infected Adults in the United States Through 2030.

Background: Persons living with HIV (PLWH) have an elevated risk for certain types of cancer. With modern antiretroviral therapy, PLWH are aging and cancer rates are changing. Objective: To project cancer incidence rates and burden (number of new cancer diagnoses) among adult PLWH in the United States through 2030. Design: Descriptive. Setting: HIV/AIDS Cancer Match Study to project cancer rates and HIV Optimization and Prevention Economics model to project HIV prevalence. Participants: HIV-infected adults. Measurements: Projected cancer rates and burden among HIV-infected adults in the United States by age during 2006 to 2030 for AIDS-defining cancer (ADC)-that is, Kaposi sarcoma, non-Hodgkin lymphoma, and cervical cancer-and certain types of non-AIDS-defining cancer (NADC). All other cancer types were combined. Results: The proportion of adult PLWH in the United States aged 65 years or older is projected to increase from 8.5% in 2010 to 21.4% in 2030. Age-specific rates are projected to decrease through 2030 across age groups for Kaposi sarcoma, non-Hodgkin lymphoma, cervical cancer, lung cancer, Hodgkin lymphoma, and other cancer types combined, and among those aged 65 years or older for colon cancer. Prostate cancer rates are projected to increase. The estimated total cancer burden in PLWH will decrease from 8150 cases in 2010 (2730 of ADC and 5420 of NADC) to 6690 cases in 2030 (720 of ADC and 5980 of NADC). In 2030, prostate cancer (n = 1590) and lung cancer (n = 1030) are projected to be the most common cancer types. Limitation: Projections assume that current trends in cancer incidence rates, HIV transmission, and survival will continue. Conclusion: The cancer burden among PLWH is projected to shift, with prostate and lung cancer expected to emerge as the most common types by 2030. Cancer will remain an important comorbid condition, and expanded access to HIV therapies and cancer prevention, screening, and treatment is needed. Primary Funding Source: National Cancer Institute.

Impact of Improved HIV Care and Treatment on PrEP Effectiveness in the United States, 2016-2020.

BACKGROUND: The effect of improving diagnosis, care, and treatment of persons living with HIV (PLWH) on pre-exposure prophylaxis (PrEP) effectiveness in the United States has not been 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 3 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, 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 men who have sex with men population was the chief beneficiary of PrEP.

Effects of Reaching National Goals on HIV Incidence, by Race and Ethnicity, in the United States.

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.

Unintended costs and consequences of school closures implemented in preparation for Hurricane Isaac in Harrison County School District, Mississippi, August-September 2012.

INTRODUCTION: School closures, while an effective measure against the spread of disease during a pandemic, may carry unintended social and economic consequences for students and families. We evaluated these costs and consequences following a 4-day school closure in Mississippi's Harrison County School District (HCSD). METHODS: In a survey of all households with students enrolled in HCSD, we collected information on difficulties related to the school closure, including interruption of employment and pay, loss of access to subsidized school meals, and arrangement of alternative childcare. We analyzed this information in the context of certain demographic characteristics of the survey respondents and households, such as race, level of education, and income. We also estimated the average number of lost work days and documented the childcare alternatives chosen by households affected by the school closure. RESULTS: We received 2,229 (28.4%) completed surveys from an estimated 7,851 households eligible to participate. About half (1,082 [48.5%]) of the households experienced at least some difficulty during the closure, primarily in three areas: uncertainty about duration of the closure, lost income, and the effort of arranging alternate childcare. Adults working outside the home, particularly the major wage earner in the household, were more likely to suffer lost income while schools were closed, an effect mitigated by paid leave benefits. Difficulty arranging childcare was reported most frequently by respondents with lower levels of education and households with younger children. Beyond the top three concerns expressed by households in HCSD, the survey also shed light on the issue of food insecurity when subsidized school meals are not available. Reported by 17.9% of households participating in the subsidized school lunch program, difficulty providing meals during the closure was associated with higher numbers of dependent children, selection of "other" as the race of the household respondent, and lower levels of education. CONCLUSION: To help prevent undue financial hardship in families of school children, public health authorities and school administrators should provide recommendations for childcare alternatives and paid leave or remote work options during prolonged school closures, particularly to households in which all adults work outside of the home.

Modeling in Real Time During the Ebola Response.

To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).

Design of the national health security preparedness index.

The importance of health security in the United States has been highlighted by recent emergencies such as the H1N1 influenza pandemic, Superstorm Sandy, and the Boston Marathon bombing. The nation's health security remains a high priority today, with federal, state, territorial, tribal, and local governments, as well as nongovernment organizations and the private sector, engaging in activities that prevent, protect, mitigate, respond to, and recover from health threats. The Association of State and Territorial Health Officials (ASTHO), through a cooperative agreement with the Centers for Disease Control and Prevention (CDC) Office of Public Health Preparedness and Response (OPHPR), led an effort to create an annual measure of health security preparedness at the national level. The collaborative released the National Health Security Preparedness Index (NHSPI(™)) in December 2013 and provided composite results for the 50 states and for the nation as a whole. The Index results represent current levels of health security preparedness in a consistent format and provide actionable information to drive decision making for continuous improvement of the nation's health security. The overall 2013 National Index result was 7.2 on the reported base-10 scale, with areas of greater strength in the domains of health surveillance, incident and information management, and countermeasure management. The strength of the Index relies on the interdependencies of the many elements in health security preparedness, making the sum greater than its parts. Moving forward, additional health security-related disciplines and measures will be included alongside continued validation efforts.