BACKGROUND: The Ending the HIV Epidemic (EHE) initiative aims to reduce incident HIV infections by 90% over a span of 10 years. The intensity of interventions needed to achieve this for local epidemics is unclear. OBJECTIVE: To estimate the effect of HIV interventions at the city level. DESIGN: A compartmental model of city-level HIV transmission stratified by age, race, sex, and HIV risk factor was developed and calibrated. SETTING: 32 priority metropolitan statistical areas (MSAs). PATIENTS: Simulated populations in each MSA. INTERVENTION: Combinations of HIV testing and preexposure prophylaxis (PrEP) coverage among those at risk for HIV, plus viral suppression in persons with diagnosed HIV infection. MEASUREMENTS: The primary outcome was the projected reduction in incident cases from 2020 to 2030. RESULTS: Absent intervention, HIV incidence was projected to decrease by 19% across all 32 MSAs. Modest increases in testing (1.25-fold per year), PrEP coverage (5 percentage points), and viral suppression (10 percentage points) across the population could achieve reductions of 34% to 67% by 2030. Twenty-five percent PrEP coverage, testing twice a year on average, and 90% viral suppression among young Black and Hispanic men who have sex with men (MSM) achieved similar reductions (13% to 68%). Including all MSM and persons who inject drugs could reduce incidence by 48% to 90%. Thirteen of 32 MSAs could achieve greater than 90% reductions in HIV incidence with large-scale interventions that include heterosexuals. A web application with location-specific results is publicly available (www.jheem.org). LIMITATION: The COVID-19 pandemic was not represented. CONCLUSION: Large reductions in HIV incidence are achievable with substantial investment, but the EHE goals will be difficult to achieve in most locations. An interactive model that can help policymakers maximize the effect in their local environments is presented. PRIMARY FUNDING SOURCE: National Institutes of Health.
BACKGROUND: The Ending the HIV Epidemic (EHE) initiative aims to reduce incident HIV infections by 90% over a span of 10 years. The intensity of interventions needed to achieve this for local epidemics is unclear. OBJECTIVE: To estimate the effect of HIV interventions at the city level. DESIGN: A compartmental model of city-level HIV transmission stratified by age, race, sex, and HIV risk factor was developed and calibrated. SETTING: 32 priority metropolitan statistical areas (MSAs). PATIENTS: Simulated populations in each MSA. INTERVENTION: Combinations of HIV testing and preexposure prophylaxis (PrEP) coverage among those at risk for HIV, plus viral suppression in persons with diagnosed HIV infection. MEASUREMENTS: The primary outcome was the projected reduction in incident cases from 2020 to 2030. RESULTS: Absent intervention, HIV incidence was projected to decrease by 19% across all 32 MSAs. Modest increases in testing (1.25-fold per year), PrEP coverage (5 percentage points), and viral suppression (10 percentage points) across the population could achieve reductions of 34% to 67% by 2030. Twenty-five percent PrEP coverage, testing twice a year on average, and 90% viral suppression among young Black and Hispanic men who have sex with men (MSM) achieved similar reductions (13% to 68%). Including all MSM and persons who inject drugs could reduce incidence by 48% to 90%. Thirteen of 32 MSAs could achieve greater than 90% reductions in HIV incidence with large-scale interventions that include heterosexuals. A web application with location-specific results is publicly available (www.jheem.org). LIMITATION: The COVID-19 pandemic was not represented. CONCLUSION: Large reductions in HIV incidence are achievable with substantial investment, but the EHE goals will be difficult to achieve in most locations. An interactive model that can help policymakers maximize the effect in their local environments is presented. PRIMARY FUNDING SOURCE: National Institutes of Health.
Authors: E R Monterroso; M E Hamburger; D Vlahov; D C Des Jarlais; L J Ouellet; F L Altice; R H Byers; P R Kerndt; J K Watters; B P Bowser; M D Fernando; S D Holmberg Journal: J Acquir Immune Defic Syndr Date: 2000-09-01 Impact factor: 3.731
Authors: S A Strathdee; D D Celentano; N Shah; C Lyles; V A Stambolis; G Macalino; K Nelson; D Vlahov Journal: J Urban Health Date: 1999-12 Impact factor: 3.671
Authors: Anthony T Fojo; Emily A Kendall; Parastu Kasaie; Sourya Shrestha; Thomas A Louis; David W Dowdy Journal: Open Forum Infect Dis Date: 2017-08-14 Impact factor: 4.423