Projected Life Expectancy for Adolescents With HIV in the US

Importance

Life expectancy is a key measure of overall population health. Life expectancy estimates for youth with HIV in the US are needed in the current HIV care and treatment context to guide health policies and resource allocation.

Objective

To compare life expectancy between 18-year-old youth with perinatally acquired HIV (PHIV), youth with nonperinatally acquired HIV (NPHIV), and youth without HIV.

Design, Setting, and Participants

Using a US-focused adolescent-specific Monte Carlo state-transition HIV model, we simulated individuals from age 18 years until death. We estimated probabilities of HIV treatment and care engagement, HIV progression, clinical events, and mortality from observational cohorts and clinical trials for model input parameters. The simulated individuals were 18-year-old race and ethnicity-matched youth with PHIV, youth with NPHIV, and youth without HIV; 47%, 85%, and 50% were assigned male sex at birth, respectively. Individuals were categorized by US Centers for Disease Control and Prevention-defined HIV acquisition risk: men who have sex with men, people who ever injected drugs, heterosexually active individuals at increased risk for HIV infection, or average risk for HIV infection. Distributions were 3%, 2%, 12%, and 83% for youth with PHIV and youth without HIV, and 80%, 6%, 14%, and 0% for youth with NPHIV, respectively. Among the simulated youth in this analysis, individuals were 61% Black, 24% Hispanic, and 15% White, respectively.

Exposures

HIV status by timing of acquisition.

Main Outcomes

Life expectancy loss for youth with PHIV and youth with NPHIV: difference between mean projected life expectancy under current and ideal HIV care scenarios compared with youth without HIV. Uncertainty intervals reflect varying adolescent HIV-related mortality inputs (95% CIs).

Results

Compared with youth without HIV (life expectancy: male, 76.3 years; female, 81.7 years), male youth with PHIV and youth with NPHIV had projected life expectancy losses of 10.4 years (95% CI, 5.5-18.1) and 15.0 years (95% CI, 9.3-26.8); female youth with PHIV and youth with NPHIV had projected life expectancy losses of 11.8 years (95% CI, 6.4-20.2) and 19.5 years (95% CI, 13.8-31.6), respectively. When receiving ideal HIV care, life expectancy losses were projected to improve for youth with PHIV (male: 0.5 years [95% CI, 0.3-1.8]: female: 0.6 years [95% CI, 0.4-2.1]) but were projected to persist for youth with NPHIV (male: 6.0 years [95% CI, 5.0-9.1]; female: 10.4 years [95% CI, 9.4-13.6]).

Conclusions

This adolescent-focused microsimulation modeling analysis projected that youth with HIV would have shorter life expectancy than youth without HIV. Projected differences were larger for youth with NPHIV compared with youth with PHIV. Differences in mortality by sex at birth, sexual behavior, and injection drug use contributed to lower projected life expectancy among youth with NPHIV. Interventions focused on HIV care and social factors are needed to improve life expectancy for youth with HIV in the US.

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.

Evaluation of "Test to Return" after COVID-19 Diagnosis in a Massachusetts Public School District

BACKGROUND

Per Centers for Disease Control and Prevention guidance, students with COVID-19 may end isolation after 5 days if symptoms are improving; some individuals may still be contagious. Rapid antigen testing identifies possibly infectious virus. We report on a test-to-return (TTR) program in a Massachusetts school district to inform policy decisions about return to school after COVID-19.

METHODS

During the 2021-2022 Omicron BA.1 surge, students with COVID-19 could return on day 6-10 if they met symptom criteria and had a negative rapid test; students with positive rapid tests and those who declined TTR remained isolated until day 11. TTR positivity rates were compared by grade level, vaccination status, symptom status, and day of infection.

RESULTS

31.4% of students had a positive TTR rapid test; there were no differences by grade or vaccination status. Ever-symptomatic students were more likely to have a positive rapid test (75/174 [43.1%] vs 18/104 [17.3%]). For ever-symptomatic students, TTR positivity decreased by day of infection.

CONCLUSIONS

A substantial proportion of students may still be contagious 6 days after onset of COVID-19 infection. TTR programs may increase or reduce missed school days, depending on when return is otherwise allowed (day 6 or 11). The impact of TTR programs on school-associated transmission remains unknown.

Prevalence and Risk Factors for School-Associated Transmission of SARS-CoV-2

Importance

School-associated SARS-CoV-2 transmission is described as uncommon, although the true transmission rate is unknown.

Objective

To identify the SARS-CoV-2 secondary attack rate (SAR) in schools and factors associated with transmission.

Design, Setting, and Participants

This cohort study examined the risk of school-based transmission of SARS-CoV-2 among kindergarten through grade 12 students and staff in 10 Massachusetts school districts during 2 periods: fall 2020/spring 2021 (F20/S21) and fall 2021 (F21). School staff collected data on SARS-CoV-2 index cases and school-based contacts, and SAR was defined as the proportion of contacts acquiring SARS-CoV-2 infection.

Exposure

SARS-CoV-2.

Main Outcomes and Measures

Potential factors associated with transmission, including grade level, masking, exposure location, vaccination history, and Social Vulnerability Index (SVI), were analyzed using univariable and multivariable logistic regression models.

Results

For F20/S21, 8 school districts (70 schools, >33 000 students) were included and reported 435 index cases (151 staff, 216 students, and 68 missing role) with 1771 school-based contacts (278 staff, 1492 students, and 1 missing role). For F21, 5 districts (34 schools, >18 000 students) participated and reported 309 index cases (37 staff, 207 students, and 65 missing role) with 1673 school-based contacts (107 staff and 1566 students). The F20/S21 SAR was 2.2% (lower bound, 1.6%; upper bound, 26.7%), and the F21 SAR was 2.8% (lower bound, 2.6%; upper bound, 7.4%). In multivariable analysis, during F20/S21, masking was associated with a lower odds of transmission compared with not masking (odds radio [OR], 0.12; 95% CI, 0.04-0.40; P < .001). In F21, classroom exposure vs out-of-classroom exposure was associated with increased odds of transmission (OR, 2.47; 95% CI, 1.07-5.66; P = .02); a fully vaccinated vs unvaccinated contact was associated with a lower odds of transmission (OR, 0.04; 95% CI, 0.00-0.62; P < .001). In both periods, a higher SVI was associated with a greater odds of transmission.

Conclusions and Relevance

In this study of Massachusetts schools, the SAR for SARS-CoV-2 among school-based contacts was low during 2 periods, and factors associated with transmission risk varied over time. These findings suggest that ongoing surveillance efforts may be essential to ensure that both targeted resources and mitigation practices remain optimal and relevant for disease prevention.

Pharyngeal timing and particle transport defects in Caenorhabditis elegans feeding mutants

The nematode C. elegans uses rhythmic muscle contractions (pumps) of the pharynx, a tubular feeding organ, to filter, transport, and crush food particles. A number of feeding mutants have been identified, including those with slow pharyngeal pumping rate, weak muscle contraction, defective muscle relaxation, and defective grinding of bacteria. Many aspects of these pharyngeal behavioral defects and how they affect pharyngeal function are not well understood. For example, the behavioral deficits underlying inefficient particle transport in 'slippery' mutants have been unclear. Here we use high speed video microscopy to describe pharyngeal pumping behaviors and particle transport in wild-type animals and in feeding mutants. Different 'slippery' mutants exhibit distinct defects including weak isthmus contraction, failure to trap particles in the anterior isthmus, and abnormal timing of contraction and relaxation in pharyngeal compartments. Our results show that multiple deficits in pharyngeal timing or contraction can cause defects in particle transport.