DC has a goal: Fewer than 130 new HIV diagnoses a year by 2030.
DC’s first plan to end the HIV epidemic, known as the 90/90/90/50 Plan, had four goals: 90% of people with HIV knowing their status; 90% of people diagnosed with HIV being in treatment; 90% of people with HIV on treatment achieving viral suppression; and a 50% reduction in new diagnoses by the year 2020.
For this updated plan, DC Health has made the 90/90/90 a floor rather than the ceiling. By 2030, we are aiming for a new ceiling with 95% of people knowing their HIV status, 95% of those diagnosed being in treatment, and 95% of those in treatment reaching viral suppression.
Instead of a percentage decrease in new diagnoses, we want to give DC a solid number: an ambitious but achievable number that represents ending the epidemic — a number that means we have maximized all the tools we have in order to end the epidemic. It is not zero, because we do not yet have a cure or vaccine. However, the number means we are making new HIV diagnoses as rare as possible in DC.
That number is 130 or fewer new diagnoses by 2030.
To precisely assess progress toward the goal of fewer than 130 new HIV diagnoses a year by 2030, DC Health developed a predictive model for estimating the planned impact of scale-up of plan strategies. DC Health needed to determine starting points, or baseline values, for several parameters: people living with HIV; of those living with HIV, the number who are diagnosed; of those diagnosed, the number who are “in treatment” — defined here to mean on using antiretrovial therapy (ART); and of those in treatment, the number who have reached viral suppression. Those parameters are known as the HIV care continuum.
DC Health attributes most of the goal of fewer than 130 new diagnoses by the year 2030 to increasing the numbers of the care continuum. However, to reach the goal will also require expansion of PrEP. Given gaps in certain data, establishing baseline model inputs required the estimation of several parameters.
Undiagnosed model estimates
DC Health used the Fellows model¹, which produced the estimate that 11% to 17.7% of HIV cases were undiagnosed within the District.DC Health used the more conservative (base bound) estimate (11%) for its reported estimates of total HIV infection (see Figure 1).
To measure the progress of the DC Ends HIV plan and to achieve its goal by 2030, DC Health calculated its baseline for several parameters. DC Health used a data-driven model¹ that uses local surveillance data to project care continuum targets for each year. The model calibrated predicted incidence estimates from HAHSTA’s Annual Epidemiology & Surveillance Report ² for the years 2015–2019 by scaling predicted values using the following formula:
— where n is the number of years and x is the year in question. To bring the latest surveillance estimates to the year 2020, the model assumed that care continuum parameters of percentage diagnosed, in treatment, and virally suppressed continued to improve at a linear rate since last observed; after 2020, these parameters formed the basis of intervention scenarios. The denominator remained n-1 for the years after 2020.
DC Health changed the model and assumed the mortality rate continued at the 0.97% annual decline observed during 2015-2019. After 2019, the model projected the end epidemic goal by achieving 95% of people diagnosed, 95% in treatment, and 95% virally suppressed by 2030 with 20% of new diagnoses averted by PrEP. The 20% of diagnoses averted by PrEP scenario approximately corresponds to the AIDSVu estimate of PrEP use for DC³.
As of November 2020, the number of people diagnosed and residing in DC was 12,408 (89%). Retention to care, which is based on laboratory visits reported to DC Health, was 9,745 (78.5%) in 2019. The number of people virally suppressed retained in HIV care at the end of 2019 was 8,495 (87.2%). The model estimated 12,202 (95%) diagnosed, 11,592 (95%) retained, and 11,012 (95%) virally suppressed (Figures 1 and 2) in 2030. DC Health used the model to estimate the number of new diagnoses of 130 by 2030. The number of death estimates includes all deaths and is not restricted to only HIV-related deaths.
As additional data and information become available, the model will be updated to reflect the evolving knowledge of the characteristics of the HIV epidemic within the District and the efficacy of intervention strategies within the local population.
Effectively monitoring progress in maximizing the benefits of pre-exposure prophylaxis (PrEP)in the prevention of HIV at the population level is in part dependent on an accurate assessment of optimal targets for utilization coverage. Such information is essential for not only understanding the total number of individuals who can potentially benefit from PrEP use, but it is also integral in defining the key populations for PrEP awareness, linkage, and adherence support programs.Modeled after a previous analysis done by the CDC Centers for Disease Control and Prevention, a multiplier method was applied to local demographic and HIV surveillance data to ascertain estimates of the number of individuals living in the District with indications for PrEP use. To facilitate a focused assessment of local PrEP coverage needs, estimates were stratified by four key categories: men who have sex with men (MSM),heterosexually active men, heterosexually active women, and people who inject drugs.
Although inadequate information regarding risk behavior patterns within the HIV-negative population limits the ability to conduct a direct assessment of PrEP need, an estimation can be derived through extrapolating information from national and local survey and disease surveillance data. According to information available from the 2019 American Community Survey (ACS) 5-Year Estimate Data Profile, the documents an adult (i.e., people 18 or older) male population in the District is 266,022. With this number as a base, there are around 40,701 MSM living in the District, assuming previous estimates (15.3% of adult male population) derived from the ACS and National Health and Nutrition Examination Survey (NHANES).⁶ Based on local surveillance data, there were 6,081 MSM diagnosed with HIV living in the District in 2019. Subtracting the number of MSM diagnosed with HIV from the total MSM population produces a local HIV-negative MSM population estimate of 34,620. Nationally, it is estimated that 24.7% of HIV-negative MSM have indications for PrEP based on an assessment of NHANES data documenting the number of individuals reporting sex with two or more men and any sex without condoms or sexually transmitted infections within 12 months.⁴ Applying this percentage to the local HIV-negative MSM population produces an estimate of 8,551 MSM in the District with indications for PrEP.
Consistent with previous analysis,⁵ there is a similar assumption of the ratio of the number of people in other focus populations (heterosexual men, heterosexual women, and people who inject drugs) with indications for PrEP relative to the proportion of new HIV diagnoses attributable to their populations based on the MSM calculation above. By multiplying the latter ratios by the number of MSM in the District with indications for PrEP, estimates for the number of individuals with PrEP indications can be derived for each of the additional focus populations. Of the 1,766 new HIV diagnoses documented in the District between 2015 and 2019, 53% were accounted for by MSM, 17% heterosexual women, 11% heterosexual men, and 2% people who inject drugs. Using these percentages, the ratio of the proportion of new HIV diagnoses attributable to focus populations relative to the proportion of new HIV diagnoses attributable to the MSM population is 0.32 (i.e., ratio = 17/53) for heterosexual women, 0.21 (i.e., ratio = 11/53) for heterosexual men, and 0.04 (i.e., ratio = 2/53) for the people who inject drugs. Based on applying these ratios to the estimated number of MSM (n = 8,551) with indications for PrEP, there are around 2,743 heterosexual women, 1,775 heterosexual men, and 323 people who inject drugs with indications for PrEP in the District.
Similar to previously published assessments,⁴ ⁵ DC Health estimates that 13,392 individuals have indications for PrEP in the District, based on analysis using the most current demographic and HIV surveillance data.
As additional data and information are available, the model will be updated to reflect the evolving knowledge of the characteristics of the HIV epidemic within the District and the efficacy of intervention strategies within the local population.
1. Bradley H, Rosenberg ES, Holtgrave DR. data-driven goals for curbing the U.S. HIV epidemic by 2030. AIDS and Behavior. 2019;23(0123456789):557-563. doi:10.1007/s10461-019-02442-7.
2. HAHSTA. Annual epidemiology & surveillance report; 2019.
3. AIDSVu. All states PrEP data Sets. Retrieved from https://aidsvu.org/resources/#/.
4. Smith DK, Van Handel M, Wolitski RJ, Stryker JE, Hall HI, Prejean J, et al. Vital Signs: Estimated percentages and numbers of adults with indications for pre-exposure prophylaxis to prevent HIV acquisition-United States, 2015. MMWR Morb Mortal Wkly Rep 2015;64(46):1291-5.
5. Smith DK, Van Handel M, Grey J. Estimates of adults with indications for HIV pre-exposure prophylaxis by jurisdiction, transmission risk group, and race/ethnicity, United States, 2015. Annuals of Epidemiology 2018; 28:850-857.
6. Grey JA, Bernstein KT, Sullivan PS, Purcell DW, Chesson HW, Gift TI, et al. Estimating the population sizes of men who have sex with men in US states and counties using data from the American Community Survey. JIMR Public Health Surveill 2016; 2(1):e14.