Simulating the End of AIDS in New York: Using Participatory Dynamic Modeling to Improve Implementation of the Ending the Epidemic Initiative.

OBJECTIVES: In 2014, the governor of New York announced the Ending the Epidemic (ETE) plan to reduce annual new HIV infections from 3000 to 750, achieve a first-ever decrease in HIV prevalence, and reduce AIDS progression by the end of 2020. The state health department undertook participatory simulation modeling to develop a baseline for comparing epidemic trends and feedback on ETE strategies. METHODS: A dynamic compartmental model projected the individual and combined effects of 3 ETE initiatives: enhanced linkage to and retention in HIV treatment, increased preexposure prophylaxis (PrEP) among men who have sex with men, and expanded housing assistance. Data inputs for model calibration and low-, medium-, and high-implementation scenarios (stakeholders' rollout predictions, and lower and upper bounds) came from surveillance and program data through 2014, the literature, and expert judgment. RESULTS: Without ETE (baseline scenario), new HIV infections would decline but remain >750, and HIV prevalence would continue to increase by 2020. Concurrently implementing the 3 programs would lower annual new HIV infections by 16.0%, 28.1%, and 45.7% compared with baseline in the low-, medium-, and high-implementation scenarios, respectively. In all concurrent implementation scenarios, although annual new HIV infections would remain >750, there would be fewer new HIV infections than deaths, yielding the first-ever decrease in HIV prevalence. PrEP and enhanced linkage and retention would confer the largest population-level changes. CONCLUSIONS: New York State will achieve 1 ETE benchmark under the most realistic (medium) implementation scenario. Findings facilitated framing of ETE goals and underscored the need to prioritize men who have sex with men and maintain ETE's multipronged approach, including other programs not modeled here.

Policy modeling to support administrative decisionmaking on the New York state HIV testing law.

A recent New York law requires medical providers to offer HIV tests as part of routine care. We developed a system dynamics simulation model of the HIV testing and care system to help administrators understand the law's potential epidemic impact, resource needs, strategies to improve implementation, and appropriate outcome indicators for future policy evaluations once postlaw data become available. Policy modeling allowed us to synthesize information from numerous sources including quantitative administrative data sets and practitioners' content expertise, structure the information to be viewed both numerically and visually, and organize consensus for decisionmaking purposes. This case illustrates how policy modeling can provide an integrated framework for administrators to examine policy problems in complex systems, particularly when data time lags limit pre--post comparisons and key outcomes cannot be measured directly.

Modeling the Declining Positivity Rates for Human Immunodeficiency Virus Testing in New York State.

OBJECTIVE: New York health care providers have experienced declining percentages of positive human immunodeficiency virus (HIV) tests among patients. Furthermore, observed positivity rates are lower than expected on the basis of the national estimate that one-fifth of HIV-infected residents are unaware of their infection. We used mathematical modeling to evaluate whether this decline could be a result of declining numbers of HIV-infected persons who are unaware of their infection, a measure that is impossible to measure directly. DESIGN AND SETTING: A stock-and-flow mathematical model of HIV incidence, testing, and diagnosis was developed. The model includes stocks for uninfected, infected and unaware (in 4 disease stages), and diagnosed individuals. Inputs came from published literature and time series (2006-2009) for estimated new infections, newly diagnosed HIV cases, living diagnosed cases, mortality, and diagnosis rates in New York. MAIN OUTCOME MEASURES: Primary model outcomes were the percentage of HIV-infected persons unaware of their infection and the percentage of HIV tests with a positive result (HIV positivity rate). RESULTS: In the base case, the estimated percentage of unaware HIV-infected persons declined from 14.2% in 2006 (range, 11.9%-16.5%) to 11.8% in 2010 (range, 9.9%-13.1%). The HIV positivity rate, assuming testing occurred independent of risk, was 0.12% in 2006 (range, 0.11%-0.15%) and 0.11% in 2010 (range, 0.10%-0.13%). The observed HIV positivity rate was more than 4 times the expected positivity rate based on the model. CONCLUSIONS: HIV test positivity is a readily available indicator, but it cannot distinguish causes of underlying changes. Findings suggest that the percentage of unaware HIV-infected New Yorkers is lower than the national estimate and that the observed HIV test positivity rate is greater than expected if infected and uninfected individuals tested at the same rate, indicating that testing efforts are appropriately targeting undiagnosed cases.

Timing of entry to care by newly diagnosed HIV cases before and after the 2010 New York State HIV testing law.

Prompt entry to care after HIV diagnosis benefits the infected individual and reduces the likelihood of further transmission of the virus. The New York State HIV Testing Law of 2010 requires diagnosing providers to refer persons newly diagnosed with HIV to follow-up medical care. This study used routinely collected HIV-related laboratory data from the New York State HIV surveillance system to assess whether the fraction of newly diagnosed cases entering care within 90 days of diagnosis increased after the implementation of the law. Laboratory data on 23,302 newly diagnosed cases showed that entry to care within 90 days rose steadily from 72.0% in 2007 to 85.4% in 2012. The rise was observed across all race/ethnic groups, ages, transmission risk groups, sexes, and regions of residence. Logistic regression analyses of entry to care pre-law and post-law, controlling for demographic characteristics, transmission risk, and geographic area, indicate that percentage of newly diagnosed cases entering care within 90 days grew more rapidly in the post-law period. This is consistent with a positive effect of the law on entry to care.

Mandating the offer of HIV testing in New York: simulating the epidemic impact and resource needs.

BACKGROUND: A 2010 New York law requires that patients aged 13-64 years be offered HIV testing in routine medical care settings. Past studies report the clinical outcomes, cost-effectiveness, and budget impact of expanded HIV testing nationally and within clinics but have not examined how state policies affect resource needs and epidemic outcomes. METHODS: A system dynamics model of HIV testing and care was developed, where disease progression and transmission differ by awareness of HIV status, engagement in care, and disease stage. Data sources include HIV surveillance, Medicaid claims, and literature. The model projected how alternate implementation scenarios would change new infections, diagnoses, linkage to care, and living HIV cases over 10 years. RESULTS: Without the law, the model projects declining new infections, newly diagnosed cases, individuals newly linked to care, and fraction of undiagnosed cases (reductions of 62.8%, 59.7%, 54.1%, and 57.8%) and a slight increase in living diagnosed cases and individuals in care (2.2% and 6.1%). The law will further reduce new infections, diagnosed AIDS cases, and the fraction undiagnosed and initially increase and then decrease newly diagnosed cases. Outcomes were consistent across scenarios with different testing offer frequencies and implementation times but differed according to the level of implementation. CONCLUSIONS: A mandatory offer of HIV testing may increase diagnoses and avert infections but will not eliminate the epidemic. Despite declines in new infections, previously diagnosed cases will continue to need access to antiretroviral therapy, highlighting the importance of continued funding for HIV care.

Transmitted antiretroviral drug resistance in New York State, 2006-2008: results from a new surveillance system.

BACKGROUND: HIV transmitted drug resistance (TDR) is a public health concern because it has the potential to compromise antiretroviral therapy (ART) at the population level. In New York State, high prevalence of TDR in a local cohort and a multiclass resistant case cluster led to the development and implementation of a statewide resistance surveillance system. METHODOLOGY: We conducted a cross-sectional analysis of the 13,109 cases of HIV infection that were newly diagnosed and reported in New York State between 2006 and 2008, including 4,155 with HIV genotypes drawn within 3 months of initial diagnosis and electronically reported to the new resistance surveillance system. We assessed compliance with DHHS recommendations for genotypic resistance testing and estimated TDR among new HIV diagnoses. PRINCIPAL FINDINGS: Of 13,109 new HIV diagnoses, 9,785 (75%) had laboratory evidence of utilization of HIV-related medical care, and 4,155 (43%) had a genotype performed within 3 months of initial diagnosis. Of these, 11.2% (95% confidence interval [CI], 10.2%-12.1%) had any evidence of TDR. The proportion with mutations associated with any antiretroviral agent in the NNRTI, NRTI or PI class was 6.3% (5.5%-7.0%), 4.3% (3.6%-4.9%) and 2.9% (2.4%-3.4%), respectively. Multiclass resistance was observed in <1%. TDR did not increase significantly over time (p for trend = 0.204). Men who have sex with men were not more likely to have TDR than persons with heterosexual risk factor (OR 1.0 (0.77-1.30)). TDR to EFV+TDF+FTC and LPV/r+TDF+FTC regimens was 7.1% (6.3%-7.9%) and 1.4% (1.0%-1.8%), respectively. CONCLUSIONS/SIGNIFICANCE: TDR appears to be evenly distributed and stable among new HIV diagnoses in New York State; multiclass TDR is rare. Less than half of new diagnoses initiating care received a genotype per DHHS guidelines.

Projections of diagnosed HIV infection in children and adolescents in New York State.

Decreasing mother-to-child transmission is changing the population of children and adolescents with HIV. This project used recent epidemiological data to develop short-term projections of children and adolescents living with diagnosed HIV infection in New York State. A population simulation model was created to project prevalence of diagnosed HIV cases aged 0-19 years by age, sex, race/ethnicity and risk for years 2007-2014. Using 2006 data as the baseline population and 2001-2006 diagnosis and death data, annual diagnoses and deaths were calculated for each age/sex/race/risk category and known cases were 'aged' into the next year. The model produced annual estimates until 2014. The model predicts a decline in the number of persons aged 0-19 years living with diagnosed HIV in New York from 2810 in 2006 to 1431 in 2014, a net decrease of 49%. Living cases with paediatric risk continue to decrease. Cases aged 13-19 with non-paediatric risk increase slowly, leading to a shift in the risk composition of the population. The dominant effect seen in the model is the ageing out of perinatally infected children born before measures to prevent mother-to-child transmission were broadly implemented in the mid- to late 1990s. Changing trends in the young HIV-infected population should be considered in developing public health programmes for HIV prevention and care in New York State for the coming years.