Potential Effects of the Coronavirus Disease 2019 (COVID-19) Pandemic on Human Immunodeficiency Virus (HIV) Transmission: A Modeling Study in 32 US Cities

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.

Projecting the Clinical and Economic Impacts of Changes to HIV Care Among Adolescents and Young Adults in the United States: Lessons From the COVID-19 Pandemic

BACKGROUND

During the COVID-19 pandemic, many US youth with HIV (YHIV) used telehealth services; others experienced disruptions in clinic and antiretroviral therapy (ART) access.

METHODS

Using the Cost-effectiveness of Preventing AIDS Complications (CEPAC)-Adolescent HIV microsimulation model, we evaluated 3 scenarios: 1) Clinic: in-person care; 2) Telehealth: virtual visits, without CD4 or viral load monitoring for 12 months, followed by return to usual care; and 3) Interruption: complete care interruption with no ART access or laboratory monitoring for 6 months (maximum clinic closure time), followed by return to usual care for 80%. We assigned higher 1-year retention (87% vs 80%) and lower cost/visit ($49 vs $56) for Telehealth vs Clinic. We modeled 2 YHIV cohorts with non-perinatal (YNPHIV) and perinatal (YPHIV) HIV, which differed by mean age (22 vs 16 years), sex at birth (85% vs 47% male), starting CD4 count (527/μL vs 635/μL), ART, mortality, and HIV-related costs. We projected life months (LMs) and costs/100 YHIV over 10 years.

RESULTS

Over 10 years, LMs in Clinic and Telehealth would be similar (YNPHIV: 11 350 vs 11 360 LMs; YPHIV: 11 680 LMs for both strategies); costs would be $0.3M (YNPHIV) and $0.4M (YPHIV) more for Telehealth than Clinic. Interruption would be less effective (YNPHIV: 11 230 LMs; YPHIV: 11 620 LMs) and less costly (YNPHIV: $1.3M less; YPHIV: $0.2M less) than Clinic. Higher retention in Telehealth led to increased ART use and thus higher costs.

CONCLUSIONS

Telehealth could be as effective as in-person care for some YHIV, at slightly increased cost. Short interruptions to ART and laboratory monitoring may have negative long-term clinical implications.

Scoping review of modelling studies assessing the impact of disruptions to essential health services during COVID-19

BACKGROUND

Studies assessing the indirect impact of COVID-19 using mathematical models have increased in recent years. This scoping review aims to identify modelling studies assessing the potential impact of disruptions to essential health services caused by COVID-19 and to summarise the characteristics of disruption and the models used to assess the disruptions.

METHODS

Eligible studies were included if they used any models to assess the impact of COVID-19 disruptions on any health services. Articles published from January 2020 to December 2022 were identified from PubMed, Embase and CINAHL, using detailed searches with key concepts including COVID-19, modelling and healthcare disruptions. Two reviewers independently extracted the data in four domains. A descriptive analysis of the included studies was performed under the format of a narrative report.

RESULTS

This scoping review has identified a total of 52 modelling studies that employed several models (n=116) to assess the potential impact of disruptions to essential health services. The majority of the models were simulation models (n=86; 74.1%). Studies covered a wide range of health conditions from infectious diseases to non-communicable diseases. COVID-19 has been reported to disrupt supply of health services, demand for health services and social change affecting factors that influence health. The most common outcomes reported in the studies were clinical outcomes such as mortality and morbidity. Twenty-five studies modelled various mitigation strategies; maintaining critical services by ensuring resources and access to services are found to be a priority for reducing the overall impact.

CONCLUSION

A number of models were used to assess the potential impact of disruptions to essential health services on various outcomes. There is a need for collaboration among stakeholders to enhance the usefulness of any modelling. Future studies should consider disparity issues for more comprehensive findings that could ultimately facilitate policy decision-making to maximise benefits to all.

Impact of COVID-19 Response on the HIV Epidemic in Men Who Have Sex With Men in San Francisco County: The Importance of Rapid Return to Normalcy

BACKGROUND

In response to the COVID-19 pandemic, San Francisco County (SFC) had to shift many nonemergency health care resources to COVID-19, reducing HIV control resources. We sought to quantify COVID-19 effects on HIV burden among men who have sex with men (MSM) as SFC returns to pre-COVID service levels and progresses toward the Ending the HIV Epidemic (EHE) goals.

SETTING

Microsimulation model of MSM in SFC tracking HIV progression and treatment.

METHODS

Scenario analysis where services affected by COVID-19 [testing, care engagement, pre-exposure prophylaxis (PrEP) uptake, and retention] return to pre-COVID levels by the end of 2022 or 2025, compared against a counterfactual where COVID-19 changes never occurred. We also examined scenarios where resources are prioritized to reach new patients or retain of existing patients from 2023 to 2025 before all services return to pre-COVID levels.

RESULTS

The annual number of MSM prescribed PrEP, newly acquired HIV, newly diagnosed, and achieving viral load suppression (VLS) rebound quickly after HIV care returns to pre-COVID levels. However, COVID-19 service disruptions result in measurable reductions in cumulative PrEP use, VLS person-years, incidence, and an increase in deaths over the 2020-2035 period. The burden is statistically significantly larger if these effects end in 2025 instead of 2022. Prioritizing HIV care/prevention initiation over retention results in more person-years of PrEP but less VLS person-years and more deaths, influencing EHE PrEP outcomes.

CONCLUSIONS

Earlier HIV care return to pre-COVID levels results in lower cumulative HIV burdens. Resource prioritization decisions may differentially affect different EHE goals.

Isolating the Effect of COVID-19-Related Disruptions on HIV Diagnoses in the United States in 2020

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.

Impacts of COVID-19 on HIV/AIDS-Related Services in California

The degree to which COVID-19 has disrupted the advances in reducing new HIV infections and preventing AIDS-related deaths is unknown. We present findings related to the effect COVID-19 had on HIV, sexual health and harm reduction service delivery in the state of California. We conducted a qualitative rapid assessment with health care providers, as well as representatives from non-medical support service agencies serving clients living with HIV in a range of counties in California. Some organizations adapted fairly easily while others struggled or were unable to adapt at all. Clinics were better positioned than community-based organizations to accommodate COVID restrictions and to quickly reestablish services. Influential forces that softened or calcified the hardships created by COVID-19 included influx of funding, flexibility in managing funds, networking and relationships, and workforce vulnerabilities. These data clearly suggest that an enhanced level of flexibility within funding streams and reporting requirements should be continued.