TRENDS IN THE TIMELINESS OF HIV DIAGNOSIS AND ANTIRETROVIRAL TREATMENT INITIATION BEFORE, DURING AND AFTER THE “TREAT ALL” RECOMMENDATION – NEW YORK CITY, 2006 - 2015

BACKGROUND: Voluntary HIV testing followed by immediate antiretroviral treatment (ART) initiation (universal testing and treatment) has become an integral part of strategies to eliminate HIV and control the HIV/AIDS epidemic. Minimizing the time from HIV infection to ART initiation is essential for universal test and treatment to be optimally effective. In New York City, an epicenter of the HIV epidemic, the ‘treat all’ recommendation, immediate treatment for all people diagnosed with HIV, was made in late 2011, and efforts to ‘treat all’ were contemporaneous with large scale HIV testing initiatives in NYC. The overarching goal of this dissertation was to examine trends in the timeliness of diagnosis and ART initiation using data from the population-based New York City HIV surveillance registry before, during and after the “treat all” recommendation. METHODS: I utilized data from the New York City population-based HIV surveillance registry to assess the timing of diagnosis and ART initiation in New York City. For aim 1, to describe and quantify trends in early diagnosis (e.g., examine median CD4 count at diagnosis and proportion of acute HIV cases among all new diagnoses) and early ART initiation (e.g., proportion with CD4 count \u3e500 at ART initiation), I used data on NYC residents diagnosed from 2012-2015. For aim 2, to estimate the time from seroconversion to diagnosis, we applied published estimates of CD4 decline after infection from seroconverter cohorts to our population, NYC residents newly diagnosed with HIV. To verify the assumption that the square root of the CD4 cell count decreases linearly over time prior to antiretroviral treatment (ART) initiation, we compared estimates of diagnosis delay based on first versus second pre-ART CD4 counts, using data on NYC residents diagnosed from 2006-2015 (sub-aim 2a). Finally, using methods developed in Aim 2, we estimated the time from HIV seroconversion to diagnosis and to ART initiation among NYC residents diagnosed from 2006-2015 for aim 3. RESULTS: In the first aim, I examined the timeliness of diagnosis and treatment initiation in the universal test and treatment era. Among 9987 NYC residents with HIV diagnosed from 2012 to 2015, diagnosis was early (a CD4 cell count ≥500/μL or diagnosed with acute HIV infection) in 35%, and 87% started ART by June 2017. The annual proportion of persons with early diagnosis did not increase appreciably (35% in 2012 vs 37% in 2015; P = .08, Cochran-Armitage test for trend). Overall, 69% of persons had started ART at 6 months after diagnosis. The time from diagnosis to ART initiation decreased from year to year. Within 6 months of diagnosis, 62%, 67%, 72% and 77% of persons with HIV diagnosed in 2012, 2013, 2014, or 2015, respectively, had started ART, with median (interquartile range) times to ART initiation of 3.34 (1.34–12.75), 2.62 (1.28–10.13), 2.16 (1.15–7.11), and 2.03 (1.11–5.61) months, respectively. In the second aim, I adapted a CD4 decline model to estimate diagnosis delay (time from seroconversions to diagnosis). Among 12,849 NYC residents who were diagnosed with HIV from 2006 to 2015 with at least 2 pre-ART CD4 count measurements around time of diagnosis, the average diagnosis delays based on the first or second pre-ART CD4 count were similar (4.93 years (95% Confidence intervals (CI):4.84-5.03) and 4.85 years (95% CI:4.76-4.95), respectively, p-value=0.09, Wilcoxon signed-rank). In the third aim, I used methods developed in Aim 2 to estimate the timing of seroconversion and estimated the timeliness of diagnosis and treatment initiation. Among 28,162 people diagnosed with HIV during 2006-2015, 89% initiated ART by June 2017. The median CD4 count at diagnosis increased from 326 (Interquartile range (IQR):132-504) to 390 (IQR:216-571) cells/µL from 2006-2015. The average time from estimated seroconversion to ART initiation decreased by 33% from 8.0 years (95% confidence interval [CI]:7.8-8.2) in 2006 to 5.4 years (95%CI: 5.1-5.6) in 2015. Contributing to the reduction in time to ART initiation, the average time from estimated seroconversion to diagnosis decreased by 22%, from 6.5 years (95% CI:6.3-6.7) to 5.1 years (95% CI:4.9-5.4) from 2006-2015, and the average time from diagnosis to ART initiation reduced by 87%, from 1.5 years (95% CI:1.4-1.5) to 0.2 years (95% CI:0.2-0.3) from 2006-2015. DISCUSSION: The time to ART initiation was reduced in tandem with expanded HIV testing and treatment efforts in New York City. We found considerable progress in rapid ART initiation: a) the proportion of persons initiating ART within 6 months of diagnosis increased from 2012 to 2015, b) the time from seroconversion to ART initiation decreased by 33% over a 10 year period, and c) the time from diagnosis to ART initiation decreased by 87%, and is now on average very short. Despite these improvements, disparities persist in the ART initiation delay so efforts should focus on subgroups for whom progress still needs to be made. Finally, substantive efforts are needed to reduce delays in diagnosis (i.e., the time from seroconversion to diagnosis). Targeted HIV testing strategies are needed to more rapidly identify people with undiagnosed HIV soon after HIV seroconversion in order to achieve further reductions in HIV incidence and mortality in key subgroups who continue to be negatively impacted by the HIV epidemic

Inferring random change point from left-censored longitudinal data by segmented mechanistic nonlinear models, with application in HIV surveillance study

The primary goal of public health efforts to control HIV epidemics is to diagnose and treat people with HIV infection as soon as possible after seroconversion. The timing of initiation of antiretroviral therapy (ART) treatment after HIV diagnosis is, therefore, a critical population-level indicator that can be used to measure the effectiveness of public health programs and policies at local and national levels. However, population-based data on ART initiation are unavailable because ART initiation and prescription are typically measured indirectly by public health departments (e.g., with viral suppression as a proxy). In this paper, we present a random change-point model to infer the time of ART initiation utilizing routinely reported individual-level HIV viral load from an HIV surveillance system. To deal with the left-censoring and the nonlinear trajectory of viral load data, we formulate a flexible segmented nonlinear mixed effects model and propose a Stochastic version of EM (StEM) algorithm, coupled with a Gibbs sampler for the inference. We apply the method to a random subset of HIV surveillance data to infer the timing of ART initiation since diagnosis and to gain additional insights into the viral load dynamics. Simulation studies are also performed to evaluate the properties of the proposed method

Post-Disaster Reproductive Health Outcomes

We examined methodological issues in studies of disaster-related effects on reproductive health outcomes and fertility among women of reproductive age and infants in the United States (US). We conducted a systematic literature review of 1,635 articles and reports published in peer-reviewed journals or by the government from January 1981 through December 2010. We classified the studies using three exposure types: (1) physical exposure to toxicants; (2) psychological trauma; and (3) general exposure to disaster. Fifteen articles met our inclusion criteria concerning research focus and design. Overall studies pertained to eight different disasters, with most (n = 6) focused on the World Trade Center attack. Only one study examined pregnancy loss, i.e., occurrence of spontaneous abortions post-disaster. Most studies focused on associations between disaster and adverse birth outcomes, but two studies pertained only to post-disaster fertility while another two examined it in addition to adverse birth outcomes. In most studies disaster-affected populations were assumed to have experienced psychological trauma, but exposure to trauma was measured in only four studies. Furthermore, effects of both physical exposure to toxicants and psychological trauma on disaster-affected populations were examined in only one study. Effects on birth outcomes were not consistently demonstrated, and study methodologies varied widely. Even so, these studies suggest an association between disasters and reproductive health and highlight the need for further studies to clarify associations. We postulate that post-disaster surveillance among pregnant women could improve our understanding of effects of disaster on the reproductive health of US pregnant women

A national prospective cohort study of SARS/COV2 pandemic outcomes in the U.S.: The CHASING COVID Cohort

Introduction: The Chasing COVID Cohort (C 3 ) study is a US-based, geographically and socio-demographically diverse sample of adults (18 and older) enrolled into a prospective cohort study during the upswing of the U.S. COVID-19 pandemic. Methods: We used internet-based strategies to enroll C 3 participants beginning March 28th, 2020. Following baseline questionnaire completion, study participants will be contacted monthly (for 6 months) to complete assessments of engagement in non-pharmaceutical interventions (e.g., use of cloth masks, avoiding large gatherings); COVID-19 symptoms; SARS/COV2 testing and diagnosis; hospitalizations; healthcare access; and uptake of health messaging. Dried blood spot (DBS) specimens will be collected at the first follow-up assessment (last week of April 2020) and at month 3 (last week of June 2020) and stored until a validated serologic test is available. Results: As of April 20, 2020, the number of people that completed the baseline survey and provided contact information for follow-up was 7,070. Participants resided in all 50 US states, the District of Columbia, Puerto Rico, and Guam. At least 24% of participants were frontline workers (healthcare and other essential workers). Twenty-three percent (23%) were 60+ years, 24% were Black or Hispanic, 52% were men, and 52% were currently employed. Nearly 20% reported recent COVID-like symptoms (cough, fever or shortness of breath) and a high proportion reported engaging in non-pharmaceutical interventions that reduce SARS/COV2 spread (93% avoided groups \u3e20, 58% wore masks; 73% quarantined). More than half (54%) had higher risk for severe COVID-19 illness should they become infected with SARS/COV2 based on age, underlying health conditions (e.g., chronic lung disease), or daily smoking. Discussion: A geographically and socio-demographically diverse group of participants was rapidly enrolled in the C3 during the upswing of the SARS/COV2 pandemic. Strengths of the C3 include the potential for direct observation of, and risk factors for, seroconversion and incident COVID disease (among those with or without antibodies to SARS/COV2) in areas of active transmission

HIV Care Coordination promotes care re-engagement and viral suppression among people who have been out of HIV medical care: an observational effectiveness study using a surveillance-based contemporaneous comparison group

Background Medical care re-engagement is critical to suppressing viral load and preventing HIV transmission, morbidity and mortality, yet few rigorous intervention studies address this outcome. We assessed the effectiveness of a Ryan White Part A-funded HIV Care Coordination Program relative to ‘usual care,’ for short-term care re-engagement and viral suppression among people without recent HIV medical care. Methods The Care Coordination Program was launched in 2009 at 28 hospitals, health centers, and community-based organizations in New York City. Designed for people with HIV (PWH) experiencing or at risk for poor HIV outcomes, the Care Coordination Program provides long-term, comprehensive medical case management utilizing interdisciplinary teams, structured health education and patient navigation. The intervention was implemented as a safety-net services program, without a designated comparison group. To evaluate it retrospectively, we created an observational, matched cohort of clients and controls. Using the HIV surveillance registry, we identified individuals meeting program eligibility criteria from December 1, 2009 to March 31, 2013 and excluded those dying prior to 12 months of follow-up. We then matched clients to controls on baseline status (lacking evidence of viral suppression, consistently suppressed, inconsistently suppressed, or newly diagnosed in the past 12 months), start of follow-up and propensity score. For this analysis, we limited to those out of care at baseline (defined as having no viral load test in the 12 months pre-enrollment) and still residing within jurisdiction (defined as having a viral load or CD4 test reported to local surveillance and dated within the 12-month follow-up period). Using a GEE model with binary error distribution and logit link, we compared odds of care re-engagement (defined as having ≥ 2 laboratory events ≥ 90 days apart) and viral suppression (defined as having HIV RNA ≤ 200 copies/mL on the most recent viral load test) at 12-month follow-up. Results Among 326 individuals out of care at baseline, 87.2% of clients and 48.2% of controls achieved care re-engagement (Odds Ratio: 4.53; 95%CI 2.66, 7.71); 58.3% of clients and 49.3% of controls achieved viral suppression (Odds Ratio: 2.05; 95%CI 1.30, 3.23). Conclusions HIV Care Coordination shows evidence of effectiveness for care and treatment re-engagement

Food Insecurity During the First Year of COVID-19: Employment and Sociodemographic Factors Among Participants in the CHASING COVID Cohort Study

Objective: While much has been reported about the impact of the COVID-19 pandemic on food insecurity, longitudinal data and the variability experienced by people working in various industries are limited. This study aims to further characterize people experiencing food insecurity during the pandemic in terms of employment, sociodemographic characteristics, and degree of food insecurity. Methods: The study sample consisted of people enrolled in the Communities, Households and SARS-CoV-2 Epidemiology (CHASING) COVID Cohort Study from visit 1 (April–July 2020) through visit 7 (May–June 2021). We created weights to account for participants with incomplete or missing data. We used descriptive statistics and logistic regression models to determine employment and sociodemographic correlates of food insecurity. We also examined patterns of food insecurity and use of food support programs. Results: Of 6740 participants, 39.6% (n = 2670) were food insecure. Non-Hispanic Black and Hispanic (vs non-Hispanic White) participants, participants in households with children (vs no children), and participants with lower (vs higher) income and education levels had higher odds of food insecurity. By industry, people employed in construction, leisure and hospitality, and trade, transportation, and utilities industries had the highest prevalence of both food insecurity and income loss. Among participants reporting food insecurity, 42.0% (1122 of 2670) were persistently food insecure (≥4 consecutive visits) and 43.9% (1172 of 2670) did not use any food support programs. Conclusions: The pandemic resulted in widespread food insecurity in our cohort, much of which was persistent. In addition to addressing sociodemographic disparities, future policies should focus on the needs of those working in industries vulnerable to economic disruption and ensure those experiencing food insecurity can access food support programs for which they are eligible

Household factors and the risk of severe COVID-like illness early in the U.S. pandemic

Objective To investigate the role of children in the home and household crowding as risk factors for severe COVID-19 disease. Methods We used interview data from 6,831 U.S. adults screened for the Communities, Households and SARS/CoV-2 Epidemiology (CHASING) COVID Cohort Study in April 2020. Results In logistic regression models, the adjusted odds ratio [aOR] of hospitalization due to COVID-19 for having (versus not having) children in the home was 10.5 (95% CI:5.7–19.1) among study participants living in multi-unit dwellings and 2.2 (95% CI:1.2–6.5) among those living in single unit dwellings. Among participants living in multi-unit dwellings, the aOR for COVID-19 hospitalization among participants with more than 4 persons in their household (versus 1 person) was 2.5 (95% CI:1.0–6.1), and 0.8 (95% CI:0.15–4.1) among those living in single unit dwellings. Conclusion Early in the US SARS-CoV-2 pandemic, certain household exposures likely increased the risk of both SARS-CoV-2 acquisition and the risk of severe COVID-19 disease

Study protocol for data to suppression (D2S): a cluster-randomised, stepped-wedge effectiveness trial of a reporting and capacity-building intervention to improve HIV viral suppression in housing and behavioural health programmes in New York City

Introduction With progress in the ‘diagnose’, ‘link’ and ‘retain’ stages of the HIV care continuum, viral suppression (VS) gains increasingly hinge on antiretroviral adherence among people with HIV (PWH) retained in care. The Centers for Disease Control and Prevention estimate that unsuppressed viral load among PWH in care accounts for 20% of onward transmission. HIV intervention strategies include ‘data to care’ (D2C)—using surveillance to identify out-of-care PWH for follow-up. However, most D2C efforts target care linkage, not antiretroviral adherence, and limit client-level data sharing to medical (versus support-service) providers. Drawing on lessons learnt in D2C and successful local pilots, we designed a ‘data-to-suppression’ intervention that offers HIV support-service programmes surveillance-based reports listing their virally unsuppressed clients and capacity-building assistance for quality-improvement activities. We aimed to scale and test the intervention in agencies delivering Ryan White HIV/AIDS Programme-funded behavioural health and housing services.Methods and analysis To estimate intervention effects, this study applies a cross-sectional, stepped-wedge design to the intervention’s rollout to 27 agencies randomised within matched pairs to early or delayed implementation. Data from three 12-month periods (pre-implementation, partial implementation and full implementation) will be examined to assess intervention effects on timely VS (within 6 months of a report listing the client as needing follow-up for VS). Based on projected enrolment (n=1619) and a pre-implementation outcome probability of 0.40–0.45, the detectable effect size with 80% power is an OR of 2.12 (relative risk: 1.41–1.46).Ethics and dissemination This study was approved by the New York City Department of Health and Mental Hygiene’s institutional review board (protocol: 21–036) with a waiver of informed consent. Findings will be disseminated via publications, conferences and meetings including provider-agency representatives.Trial registration number NCT05140421

Cost-effectiveness of HIV care coordination scale-up among persons at high risk for sub-optimal HIV care outcomes.

BackgroundA study of a comprehensive HIV Care Coordination Program (CCP) showed effectiveness in increasing viral load suppression (VLS) among PLWH in New York City (NYC). We evaluated the cost-effectiveness of a scale-up of the CCP in NYC.MethodsWe incorporated observed effects and costs of the CCP into a computer simulation of HIV in NYC, comparing strategy scale-up with no implementation. The simulation combined a deterministic compartmental model of HIV transmission with a stochastic microsimulation of HIV progression, and was calibrated to NYC HIV epidemiological data from 1997 to 2009. We assessed incremental cost-effectiveness from a health sector perspective using 2017 $US, a 20-year time horizon, and a 3$898,104 and a cost-per-QALY-gained of $423,721. In sensitivity analyses, scale-up achieved cost-effectiveness if effectiveness increased from RR1.11 to RR1.37 or costs decreased by 41.7$705,171 and cost-per-QALY-gained of $720,970. In sensitivity analyses, scale-up achieved cost-effectiveness if effectiveness increased from RR1.11 to RR1.46 or program costs decreased by 71.3%. Limiting the intervention to persons with unsuppressed viral load attenuated the cost reduction necessary to 38.7%.ConclusionCost-effective CCP scale-up would require reduced costs and/or focused enrollment within NYC, but may be more readily achieved in cities with lower background VLS levels