Effectiveness of JYNNEOS Vaccine Against Diagnosed Mpox Infection - New York, 2022.

In 2022, an international Monkeypox virus outbreak, characterized by transmission primarily through sexual contact among gay, bisexual, and other men who have sex with men (MSM), resulted in 375 monkeypox (mpox) cases in the state of New York outside of New York City (NYC).*,† The JYNNEOS vaccine (Modified Vaccinia Ankara vaccine, Bavarian Nordic), licensed by the U.S. Food and Drug Administration (FDA) against mpox as a 2-dose series, with doses administered 4 weeks apart,§ was deployed in a national vaccination campaign.¶ Before this outbreak, evidence to support vaccine effectiveness (VE) against mpox was based on human immunologic and animal challenge studies (1-3). New York State Department of Health (NYSDOH) conducted a case-control study to estimate JYNNEOS VE against diagnosed mpox in New York residents outside of NYC, using data from systematic surveillance reporting. A case-patient was defined as a man aged ≥18 years who received a diagnosis of mpox during July 24-October 31, 2022. Contemporaneous control patients were men aged ≥18 years with diagnosed rectal gonorrhea or primary syphilis and a history of male-to-male sexual contact, without mpox. Case-patients and control patients were matched to records in state immunization systems. JYNNEOS VE was estimated as 1 - odds ratio (OR) x 100, and JYNNEOS vaccination status (vaccinated versus unvaccinated) at the time of diagnosis was compared, using conditional logistic regression models that adjusted for week of diagnosis, region, patient age, and patient race and ethnicity. Among 252 eligible mpox case-patients and 255 control patients, the adjusted VE of 1 dose (received ≥14 days earlier) or 2 doses combined was 75.7% (95% CI = 48.5%-88.5%); the VE for 1 dose was 68.1% (95% CI = 24.9%-86.5%) and for 2 doses was 88.5% (95% CI = 44.1%-97.6%). These findings support recommended 2-dose JYNNEOS vaccination consistent with CDC and NYSDOH guidance.

Targeted social marketing of PrEP and the stigmatization of black sexual minority men.

Disparities in HIV incidence and PrEP uptake suggest a need to prioritize Black sexual minority men (SMM) in PrEP social marketing initiatives. However, images linking Black SMM to HIV and PrEP may inadvertently reinforce stigma. We examined HIV-negative/status-unknown Black SMM's responses to targeted PrEP advertisements using mixed methods, including an experiment embedded in a longitudinal online survey (Time 1: n = 96; Time 2 [eight weeks]: n = 73) and four focus groups (n = 18). The full factorial experiment included between-groups and within-subjects comparisons. For between-groups comparisons, each participant was randomly assigned to view one of 12 advertisements, which varied by couple composition (Black SMM couple/Black heterosexual couple/multiple diverse couples/no couples) and campaign (PrEPare for the Possibilities/PlaySure/PrEP4Love). We examined couple composition, campaign, and interaction effects on: advertisement judgments (Time 1), PrEP stigma (Time 1), PrEP motivation (Times 1 and 2), and PrEP behavior (Time 2). For within-subjects comparisons, each participant viewed all 12 advertisements, and we examined couple composition, campaign, and interaction effects on advertisement judgments (Time 2). Focus group participants discussed advertising preferences and responded to the same set of advertisements. For between-groups and within-subjects comparisons, we found significant couple composition effects but no or limited campaign and interaction effects on advertisement judgments. Advertisements featuring Black SMM exclusively were judged as more stigmatizing than advertisements without couples. Advertisements with diverse (vs. no) couples were considered more eye-catching and motivating. There were minimal effects of couple composition and campaign on PrEP stigma, motivation, and behavior. Focus group participants corroborated concerns about the potential for PrEP advertisements to be stigmatizing, suggesting advertisements featuring Black SMM exclusively could be alienating and fuel conspiracy theories. Focus group participants generally favored diverse and less sexualized advertisements, particularly for public spaces. Findings collectively highlight the potential for targeted PrEP advertisements to stigmatize Black SMM and support diverse representation.

'There are people like me who will see that, and it will just wash over them': Black sexual minority men's perspectives on messaging in PrEP visual advertisements.

The high incidence of HIV among US Black sexual minority men is a public health crisis that pre-exposure prophylaxis (PrEP) for HIV can help address. Public health campaigns, which often include pictures of Black sexual minority men alongside PrEP-related messaging, have been developed to encourage PrEP awareness and uptake. However, the acceptability of the messaging within these campaigns among Black sexual minority men is unclear. We conducted four focus groups with 18 HIV-negative Black sexual minority men in Washington, DC to explore their perspectives regarding promotional messaging (textual elements) in PrEP visual advertisements, including their reactions to three large-scale public health campaigns. Primary themes included: (1) the need for additional information about PrEP, (2) preference for slogan simplicity, (3) the desire to normalise PrEP use, and (4) mixed views on the inclusion of condoms. Results indicated that the messaging in current PrEP visual advertisements may not sufficiently address Black sexual minority men's questions about PrEP. Providing basic PrEP information and methods to access more information; using simple, unambiguous language; presenting PrEP use in a destigmatising, normalising fashion; and conveying the relevance of condoms if included in the advertisement could help increase the acceptability of future PrEP advertising among Black sexual minority men.

UnPrEPed for HIV prevention services: Hesitancy among US primary care providers.

Provision of HIV prevention services by primary care (PCP) healthcare providers is critical to reduce the number of new HIV infections. We examined the performance of HIV risk assessments and provision of HIV prevention services by PCPs. In our cohort, less than one-half of respondents asked about sex and drug use all or most of the time, and among those that did not routinely ask about sex and drug use only 66% and 59%, respectively, would ask given more time. Less than a quarter of respondents noted that HIV prevention services were part of their clinical practice. These findings demonstrate gaps in the provision of HIV prevention services by a key population of healthcare providers.

HIV Related Stigma among Healthcare Providers: Opportunities for Education and Training.

Background: HIV-stigma can influence engagement in care and viral suppression rates among persons living with HIV (PLWH). Understanding HIV-provider level stigma and its associated factors may aid in development of interventions to improve engagement in care. Methods: We assessed HIV-related stigma, provider knowledge, and practices and beliefs among healthcare providers using an online survey tool. Generalized linear modeling was used to determine factors associated with HIV-stigma score. Results: Among 436 participants, the mean age was 42.3 (SD 12.3), 70% female, 62% white, 65% physicians, and 44% worked at an academic center. The mean HIV Health Care Provider Stigma Scale (HPASS) score was 150.5 (SD 18.9, total = 180 [higher score = less stigma]) with factor subscale scores of 67.1 (SD 8.2, total = 78) prejudice, 51.3 (SD 9.7, total = 66) stereotyping, and 32.1 (SD 5, total = 36) discrimination. Female sex and comfort with talking about sex and drug use had 4.97 (95% CI 0.61, 9.32) and 1.99 (95% CI 0.88, 3.10) estimated higher HPASS scores. Disagreement/strong disagreement versus strong agreement with the statement that PLWH should be allowed to have babies and feeling responsible for talking about HIV prevention associated with -17.05 (95% CI -25.96, -8.15) and -2.16 (95% CI -3.43, -0.88) estimated lower HPASS scores. Conclusions: The modifiable factors we identified as associated with higher HIV related stigma may provide opportunities for education that may ameliorate these negative associations.

Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model.

INTRODUCTION: Social network strategies have been used by health departments to identify undiagnosed cases of HIV. Heterosexual cycle (HET4) of National HIV Behavioral Surveillance (NHBS) is a social network strategy implemented in jurisdictions. The main objectives of this research are to 1) evaluate the utility of the NHBS HET cycle data for network analysis; 2) to apply statistical analysis in support of previous HIV research, as well as to develop new research results focused on demographic variables and prevention/intervention with respect to heterosexual HIV risk; and 3) to employ NHBS data to inform policy with respect to the EHE plan. METHOD: We used data from the 2016 NHBS HET4 (DC). A total of 747 surveys were collected. We used the free social-network analysis package, GEPHI, for all network visualization using adjacency matrix representation. We additionally conducted logistic regression analysis to examine the association of selected variables with HIV status in three models representing 1) demographic and economic effects, 2) behavioral effects, and 3) prevention-intervention effects. RESULTS: The results showed 3% were tested positive. Seed 1 initiated the largest networks with 426 nodes (15 positives); seed 4 with 273 nodes (6 positives). Seed 3 had 35 nodes (2 positives). All 23 HIV diagnoses were recruited from 4 zip-codes across DC. The risk of testing positive was higher among people high-school dropouts (Relative Risk (RR) (25.645); 95 CI% 5.699, 115.987), unemployed ((4.267); 1.295, 14.064), returning citizens ((14.319); 4.593, 44.645). We also found in the final model higher association of pre-exposure prophylaxis (PrEP) awareness among those tested negative ((4.783); 1.042, 21.944) and HIV intervention in the past 12 months with those tested positive ((17.887); 2.350,136.135). CONCLUSION: The network visualization was used to address the primary aim of the analysis-evaluate the success of the implementation of the NHBS as a social network strategy to find new diagnoses. NHBS remains one of the strongest behavioral supplements for DC's HIV planning activities. As part of the evaluation process our analysis helps to understand the impact of demographic, behavioral, and prevention efforts on peoples' HIV status. We strongly recommend other jurisdictions use network visualizations to evaluate the efficacy in reaching hidden populations.

Characterization of HIV Risk Behaviors and Clusters Using HIV-Transmission Cluster Engine Among a Cohort of Persons Living with HIV in Washington, DC.

Molecular epidemiology (ME) is one tool used to end the HIV epidemic in the United States. We combined clinical and behavioral data with HIV sequence data to identify any overlap in clusters generated from different sequence datasets; to characterize HIV transmission clusters; and to identify correlates of clustering among people living with HIV (PLWH) in Washington, District of Columbia (DC). First, Sanger sequences from DC Cohort participants, a longitudinal HIV study, were combined with next-generation sequences (NGS) from participants in a ME substudy to identify clusters. Next, demographic and self-reported behavioral data from ME substudy participants were used to identify risks of secondary transmission. Finally, we combined NGS from ME substudy participants with Sanger sequences in the DC Molecular HIV Surveillance database to identify clusters. Cluster analyses used HIV-Transmission Cluster Engine to identify linked pairs of sequences (defined as distance ≤1.5%). Twenty-eight clusters of ≥3 sequences (size range: 3-12) representing 108 (3%) participants were identified. None of the five largest clusters (size range: 5-12) included newly diagnosed PLWH. Thirty-four percent of ME substudy participants (n = 213) reported condomless sex during their last sexual encounter and 14% reported a Syphilis diagnosis in the past year. Seven transmission clusters (size range: 2-19) were identified in the final analysis, each containing at least one ME substudy participant. Substudy participants in clusters from the third analysis were present in clusters from the first analysis. Combining HIV sequence, clinical and behavioral data provided insights into HIV transmission that may not be identified using traditional epidemiological methods alone. Specifically, the sexual risk behaviors and STI diagnoses reported in the substudy survey may not have been disclosed during Partner Services activities and the survey data complemented clinical data to fully characterize transmission clusters. These findings can be used to enhance local efforts to interrupt transmission and avert new infections.

Highly variable trends in rates of newly diagnosed HIV cases in U.S. hotspots, 2008-2017.

The U.S. Ending the HIV Epidemic (EHE) initiative was announced in early 2019 and rapidly became a focal point for domestic HIV prevention and treatment programs. Using publicly available data from CDC, we examined historical trends in the average annual percent change (AAPC) in HIV diagnosis rates for the 57 EHE high incidence "hotspots" using Joinpoint analysis. We then assessed the ecologic association of various hotspot characteristics with changes in these rates over time using a multivariable regression model. From 2008-2017, the overall rate of newly diagnosed HIV cases in the U.S. declined from 19 to 14 per 100,000 persons, with the AAPC declining significantly in the U.S. overall (-3.1%; 95% CI: -3.7, -2.4) and in the 57 hotspots (-3.3%; 95% CI: -4.6, -2.8). There were large (AAPC <-5.0), moderate (-5.0 to -2.5) and small (-2.5 to 0.0) rates of decline in 14, 19 and 17 hotspots respectively, with increasing trends (AAPC >0.0) noted in seven hotspots. In the multivariable regression analysis, higher initial HIV diagnosis rate and location in the Northeast region were significantly associated with declining AAPC rates whereas no significant differences were found by hotspot gender, age, or race/ethnicity distribution. This analysis demonstrates that the rate of decline in HIV diagnosis rates in hotspots across the U.S. has been highly variable. Further exploration is warranted to assess the correlation between programmatic factors such as HIV testing and antiretroviral therapy and pre-exposure prophylaxis coverage with HIV trends across the hotspots.

Measuring Unmet Needs among Persons Living with HIV at Different Stages of the Care Continuum.

Unmet needs can impede optimal care engagement, impacting the health and well-being of people living with HIV (PLWH); yet, whether unmet needs differ by care engagement status is not well understood. Using surveys and qualitative interviews, we examined and compared unmet needs for PLWH (n = 172) at different levels of care engagement. Unmet needs varied only slightly by care status. Survey findings revealed that provision of housing, emergency financial assistance, employment assistance, and food security were the greatest unmet need; for those in care, housing was the greatest unmet need, whereas for those sporadically in care or out of care, employment assistance was the greatest unmet needs. Qualitative interviews likewise illustrated that a lack of financial resources including insurance, housing, employment, and transportation presented barriers to care engagement across all care groups. Our findings indicate that unmet needs among PLWH are complex and multi-faceted across care engagement status.

Geographic Core Areas of Coinfections in Washington, District of Columbia: Recommendations for Planning Prevention-Intervention to Mitigate Human Immunodeficiency Virus Burden.

BACKGROUND: Research suggests that human immunodeficiency virus (HIV)-positive individuals with a sexually transmitted infection (STI) may be at increased risk of transmitting HIV to someone else through unprotected sex. The primary aim of the analysis is to identify the high-risk geographic areas of transmission of coinfections and factors that may be associated with poor outcomes of viral suppression within these higher-risk geographic areas, thus important in transmission prevention. METHODS: We used surveillance data reported by all providers and laboratories in the District of Columbia (DC). Applied discrete Poisson scan model in SaTScan to identify the geographic areas. The relative risk (RR) for the scan statistic was calculated based on events inside the cluster, and P values evaluated statistical significance. We used multinomial logistical regression to explore care and demographical characteristics associated with being virally unsuppressed within and outside the geographic areas. RESULTS: The coinfected areas (RR, >1; P < .001) were located in the tracts of central and southern DC. Black population (RR, 3.154 [95% confidence interval {CI}, 1.736-5.729]), age 13-19 years (RR, 4.598 [95% CI, 3.176-6.657]), repeat STIs (RR, 1.387 [95% CI, 1.096-1.754]), and not retained in care (RR, 2.546 [95% CI, 1.997-3.245]) were found to be at higher risk of being virally unsuppressed within the coinfected clusters. Those with unknown linkages were found to be at higher risk of being virally unsuppressed outside the coinfected clusters (RR, 5.162 [95% CI, 2.289-11.640]). CONCLUSIONS: This is DC's first effort to identify the geographic core areas of coinfections and factors that may be sustaining them. These results will be used by the health department to plan for prevention-intervention strategies. This model be replicated by any local jurisdiction similar.

A Spatial Approach for Ending the Human Immunodeficiency Virus Epidemic for the United States-A DC Model.

BACKGROUND: Mode of transmission-based hotspots is a smart approach to HIV mitigation, yet remains poorly evaluated and implemented in the United States. The primary aim was to identifying mode of transmission-based hotspots and populations at risk of lower viral suppression to assist in targeted planning and implementation of programs. METHODS: We implemented spatial statistics to identify global-local hotspots and regression analysis to find populations at risk of lower viral suppression within hotspots. Data were obtained from the District of Columbia's (DC's) active surveillance system, which were geocoded based on current residence address. RESULTS: The analysis identified 6001 HIV-positive men who have sex with men (MSM) and 6077 HIV-positive non-MSM (N = 12 078) living in DC at the end of 2018. The hotspots for MSM were central DC and non-MSM in south DC. Trends of viral suppression within MSM hotspots showed plateauing and, among non-MSM, showed decline. Regression analysis showed MSM aged 21-25 (RR: 3.199; 95% CI: 1.832-5.586) and not linked to care (8.592; 2.907-25.398) were at higher risk of being virally unsuppressed within the hotspots. For non-MSM we found those aged 12-18 (9.025; 3.314-2.581) and with unknown linkages (6.087; 3.346-13.848) were at higher risk of being virally unsuppressed within the hotspots. CONCLUSIONS: Our analysis provides a model that may be used by other jurisdictions to identify areas of priority and plan treatment-adherence programs using surveillance data. Attaining viral suppression is crucial in reducing new diagnoses; a spatial approach can be an important tool in Ending the HIV Epidemic.

Comparison of Clinical Outcomes of Persons Living With HIV by Enrollment Status in Washington, DC: Evaluation of a Large Longitudinal HIV Cohort Study.

BACKGROUND: HIV cohort studies have been used to assess health outcomes and inform the care and treatment of people living with HIV disease. However, there may be similarities and differences between cohort participants and the general population from which they are drawn. OBJECTIVE: The objective of this analysis was to compare people living with HIV who have and have not been enrolled in the DC Cohort study and assess whether participants are a representative citywide sample of people living with HIV in the District of Columbia (DC). METHODS: Data from the DC Health (DCDOH) HIV surveillance system and the DC Cohort study were matched to identify people living with HIV who were DC residents and had consented for the study by the end of 2016. Analysis was performed to identify differences between DC Cohort and noncohort participants by demographics and comorbid conditions. HIV disease stage, receipt of care, and viral suppression were evaluated. Adjusted logistic regression assessed correlates of health outcomes between the two groups. RESULTS: There were 12,964 known people living with HIV in DC at the end of 2016, of which 40.1% were DC Cohort participants. Compared with nonparticipants, participants were less likely to be male (68.0% vs 74.9%, P<.001) but more likely to be black (82.3% vs 69.5%, P<.001) and have a heterosexual contact HIV transmission risk (30.3% vs 25.9%, P<.001). DC Cohort participants were also more likely to have ever been diagnosed with stage 3 HIV disease (59.6% vs 47.0%, P<.001), have a CD4 <200 cells/µL in 2017 (6.2% vs 4.6%, P<.001), be retained in any HIV care in 2017 (72.9% vs 59.4%, P<.001), and be virally suppressed in 2017. After adjusting for demographics, DC Cohort participants were significantly more likely to have received care in 2017 (adjusted odds ratio 1.8, 95% CI 1.70-2.00) and to have ever been virally suppressed (adjusted odds ratio 1.3, 95% CI 1.20-1.40). CONCLUSIONS: These data have important implications when assessing the representativeness of patients enrolled in clinic-based cohorts compared with the DC-area general HIV population. As participants continue to enroll in the DC Cohort study, ongoing assessment of representativeness will be required.

Detecting Spatial Cores and Temporal Trends of Repeat STIs to Plan Pre-exposure Prophylaxis (PrEP) Scale-up in DC.

BACKGROUND: Repeat sexually transmitted infections (STIs) in DC primarily results from untreated sexual partners. This analysis aims to identify high-risk areas and temporal trends of repeat STIs for pre-exposure prophylaxis scale-up and STI mitigation in DC. METHODS: We identified repeat infections in the DC Department of Health STI and HIV data management systems, diagnosed from 2014 to 2018. The cases were geocoded and aggregated by census tracts. Poisson discrete scan statistic was implemented in SaTScan software to find clusters. Weighted moving average was used to compare temporal trends of repeat STIs. We used χ analysis to identify association with demographic variables. RESULTS: We identified 8535 repeat STIs from 2014 to 2018. Of these, 61.84% were among men, most cases were among blacks (34.75%) and 47.45% represented gonorrhea cases. The high-risk spatial clusters were identified as those tracts that had relative risk (relative risk > 1; P-value < 0.001). We identified one significant radius of risk covering tracts of wards 7 and 8 and parts of wards 5 and 6. We spotted positive temporal trends in cluster 1 and outside the cluster. We found significant associations of repeat STIs with gender (χ = 317.27, P < 0.001), age (χ = 539.26, P < 0.001), HIV coinfections (χ = 352.06, P < 0.001), and year of diagnoses (χ = 1.5, P < 0.01). CONCLUSIONS: Our findings indicate spatial disparities in DC for repeat STIs. This analysis is critical for pre-exposure prophylaxis planning, STI prevention strategies such as expedited partner therapies and condom distribution strategies in DC should prioritize the high-risk spatial cores.

Knowledge, Attitudes, and Behaviors Related to Hepatitis C Screening and Treatment among Health Care Providers in Washington, DC.

Elimination of chronic hepatitis C (HCV) will require scaling up treatment, including possible HCV treatment by primary care providers. The District of Columbia (DC) has a substantial population living with untreated hepatitis C, and treatment expansion would benefit the resident population. The aim of this study was to assess the knowledge, attitudes, and behaviors of primary care providers and specialists related to hepatitis C screening and treatment. We conducted a prospective, online survey of physicians and nurse practitioners (n = 153) in DC on their knowledge, attitudes, and behaviors related to hepatitis C screening and treatment, as well as referral patterns, interest in learning, and preferred learning modalities. We compared responses by provider type. Key findings indicated that HCV screening and treatment knowledge was higher among specialty physicians as compared to primary care providers. The most common reported facilitators of HCV screening included a prompt in the electronic medical record (63%), patient education (57%), and support staff (41%). While 71% reported that HCV treatment was important in the community they serve, only 26% indicated that access to HCV specialist expertise and consultation was a major area of need. Additionally, 59% reported that they refer all HCV patients to specialists for treatment. Primary care providers in DC had moderate interest in learning how to treat chronic hepatitis C, but they need additional training. Patients are typically referred to gastroenterology, infectious diseases, and hepatology specialists who may have limited capacity to expand treatment.

Longitudinal outcomes of HIV- infected persons re-engaged in care using a community-based re-engagement approach.

Re-engaging people living with HIV (PLWH) who are out of care (OOC) is of utmost importance to ending the HIV epidemic in the U.S. We used DC Department of Health (DCDOH) HIV surveillance data to determine whether re-engaging PLWH results in improved long-term clinical outcomes. PLWH identified as OOC for 6-12 months at both the clinic-level and using DCDOH data were targeted for re-engagement efforts through Recapture Blitz (RB). Uni- and bivariate analyses were conducted comparing engagement in care (EIC), CD4 counts, and viral suppression (VS) at 6, 12, and 18-months post-re-engagement between persons re-engaged through RB and those not re-engaged via RB. Of the 569 PLWH contacted; 57 were re-engaged through RB, 46 were not but may have reengaged on their own. Compared to those not re-engaged via RB, at 18-months of follow-up, more PLWH re-engaged through RB were EIC (71.9% vs. 56.5%) and VS (52.6% vs. 30.4%). Higher proportions of PLWH re-engaged through RB were virally suppressed at 6, 12, and 18-months (p = 0.0238, p = 0.0347, p = 0.0238, respectively). Combining surveillance and clinical data to identify persons OOC allowed for successful re-engagement and improved longer-term outcomes post-re-engagement, underscoring the importance of re-engagement efforts to improve rates of retention and viral suppression.

Thirty-Five Years Later: HIV Stigma in Washington, DC Health Care Workers.

Stigma has negatively influenced the lives of people living with HIV since the beginning of the epidemic. It affects every facet of their lives and can cause mental health problems, loss of human rights, and barriers to care. Studies in developing countries have shown a high prevalence of HIV stigma among health care workers. Few studies have been conducted in the United States. We used a validated instrument to survey 330 health care workers in Washington, DC, a high HIV prevalence area. The goal was to obtain data to assess the severity of the problem. We found that stigmatizing beliefs and attitudes were prevalent as reflected in responses from 66% of the participants. Of clinicians surveyed, 31% reported using double gloves. Participants with stigma training had lower stigma levels, whereas older individuals and support staff were more stigmatizing. Negative attitudes affect access to care and have major public health implications.

Detecting spatial clusters of HIV and hepatitis coinfections.

BACKGROUND: People with HIV infection in the United States are often affected by chronic viral hepatitis. These coinfected people with either HBV or HCV are at increased risk for serious, life-threatening complications. Coinfections with viral hepatitis may also complicate the delivery of anti-retroviral therapy (ART) by escalating the risk of drug-related hepatoxicity. According to the Centers for Disease Control and Prevention (CDC), approximately 10 percent of people with HIV in the United States also have HBV, and 25 percent also have HCV coinfection. With the advent of highly active antiretroviral therapy (HAART) and the increased life-expectancy of HIV patients, clinicians are more likely to be confronted with issues related to co-infection and the management challenges that they present, especially in resource-limited settings. The purpose of this analysis was to identify geographical clusters of HIV- (HBV/HCV) co-infection and compared to the geographical clusters of not co-infected using DC, Department of Health surveillance data. The results of the analysis will be used to target resources to areas at risk. METHODS: HIV and Hepatitis surveillance data were matched among cases diagnosed between 1980 and 2016. HIV-hepatitis co-infected and the not co-infected spatial clusters were detected using discrete Poisson model. Kulldorff's spatial scan statistic method was implemented in the free software tool called SaTScan which has been widely adopted for detecting disease cluster. The analysis was conducted by tracts, but for visualization, ease of interpretation and assist in policy making the tract map was overlaid with the ward map using ArcGIS 10.5.1. RESULTS: Between 1980 and 2016, there were 12,965 diagnosed cases of HIV, of which 2,316 HIV/Hepatitis matches were identified. Of the 2316 co-infected people living in DC, 25 percent (N = 590) of people had HBV, and 75 percent (N = 1,726) had HCV. Out of 12,965 diagnosed cases, remaining 10,649 did not have any co-infections (not co-infected). IDU (27.16 percent) and MSM (32.86 percent) were the highest mode of transmission for co-infected population. African-American were reported 83.64 percent (N = 1,937) among co-infection population. Three clusters were identified for both co-infected population in DC. The largest cluster radius for co-infected analysis covers wards 6, 7 and 8 as well as large parts of 2 and 5 (p < 0.001). Multiple clusters were identified for not co-infected population (p < 0.001). IDU (n = 450) was the highest mode of transmission for the co-infected clusters. For all clusters combined of not co-infected population highest mode of transmission were MSM (n = 2,534). This analysis also showed racial disparity, economic deprivation and lack of education were prominent in the co-infected clusters. CONCLUSION: We identified locations of high risk clusters where enhanced hepatitis and HIV prevention, treatment, and care can help combat the epidemic. The clusters radius expands into the neighboring state of Maryland as well. The findings from this analysis will be used to target area based public health policy and healthcare interventions for HIV-hepatitis. It is recommended based on the analysis that needle exchange programs can successfully control new HIV infections as well as hepatitis co-infections.

Defining Care Patterns and Outcomes Among Persons Living with HIV in Washington, DC: Linkage of Clinical Cohort and Surveillance Data.

BACKGROUND: Triangulation of data from multiple sources such as clinical cohort and surveillance data can help improve our ability to describe care patterns, service utilization, comorbidities, and ultimately measure and monitor clinical outcomes among persons living with HIV infection. OBJECTIVES: The objective of this study was to determine whether linkage of clinical cohort data and routinely collected HIV surveillance data would enhance the completeness and accuracy of each database and improve the understanding of care patterns and clinical outcomes. METHODS: We linked data from the District of Columbia (DC) Cohort, a large HIV observational clinical cohort, with Washington, DC, Department of Health (DOH) surveillance data between January 2011 and June 2015. We determined percent concordance between select variables in the pre- and postlinked databases using kappa test statistics. We compared retention in care (RIC), viral suppression (VS), sexually transmitted diseases (STDs), and non-HIV comorbid conditions (eg, hypertension) and compared HIV clinic visit patterns determined using the prelinked database (DC Cohort) versus the postlinked database (DC Cohort + DOH) using chi-square testing. Additionally, we compared sociodemographic characteristics, RIC, and VS among participants receiving HIV care at ≥3 sites versus <3 sites using chi-square testing. RESULTS: Of the 6054 DC Cohort participants, 5521 (91.19%) were included in the postlinked database and enrolled at a single DC Cohort site. The majority of the participants was male, black, and had men who have sex with men (MSM) as their HIV risk factor. In the postlinked database, 619 STD diagnoses previously unknown to the DC Cohort were identified. Additionally, the proportion of participants with RIC was higher compared with the prelinked database (59.83%, 2678/4476 vs 64.95%, 2907/4476; P<.001) and the proportion with VS was lower (87.85%, 2277/2592 vs 85.15%, 2391/2808; P<.001). Almost a quarter of participants (23.06%, 1279/5521) were identified as receiving HIV care at ≥2 sites (postlinked database). The participants using ≥3 care sites were more likely to achieve RIC (80.7%, 234/290 vs 62.61%, 2197/3509) but less likely to achieve VS (72.3%, 154/213 vs 89.51%, 1869/2088). The participants using ≥3 care sites were more likely to have unstable housing (15.1%, 64/424 vs 8.96%, 380/4242), public insurance (86.1%, 365/424 vs 57.57%, 2442/4242), comorbid conditions (eg, hypertension) (37.7%, 160/424 vs 22.98%, 975/4242), and have acquired immunodeficiency syndrome (77.8%, 330/424 vs 61.20%, 2596/4242) (all P<.001). CONCLUSIONS: Linking surveillance and clinical data resulted in the improved completeness of each database and a larger volume of available data to evaluate HIV outcomes, allowing for refinement of HIV care continuum estimates. The postlinked database also highlighted important differences between participants who sought HIV care at multiple clinical sites. Our findings suggest that combined datasets can enhance evaluation of HIV-related outcomes across an entire metropolitan area. Future research will evaluate how to best utilize this information to improve outcomes in addition to monitoring them.