Public Health Response to Clusters of Rapid HIV Transmission Among Hispanic or Latino Gay, Bisexual, and Other Men Who Have Sex with Men - Metropolitan Atlanta, Georgia, 2021-2022.

During February 2021-June 2022, the Georgia Department of Public Health (GDPH) detected five clusters of rapid HIV transmission concentrated among Hispanic or Latino (Hispanic) gay, bisexual, and other men who have sex with men (MSM) in metropolitan Atlanta. The clusters were detected through routine analysis of HIV-1 nucleotide sequence data obtained through public health surveillance (1,2). Beginning in spring 2021, GDPH partnered with health districts with jurisdiction in four metropolitan Atlanta counties (Cobb, DeKalb, Fulton, and Gwinnett) and CDC to investigate factors contributing to HIV spread, epidemiologic characteristics, and transmission patterns. Activities included review of surveillance and partner services interview data,† medical chart reviews, and qualitative interviews with service providers and Hispanic MSM community members. By June 2022, these clusters included 75 persons, including 56% who identified as Hispanic, 96% who reported male sex at birth, 81% who reported male-to-male sexual contact, and 84% of whom resided in the four metropolitan Atlanta counties. Qualitative interviews identified barriers to accessing HIV prevention and care services, including language barriers, immigration- and deportation-related concerns, and cultural norms regarding sexuality-related stigma. GDPH and the health districts expanded coordination, initiated culturally concordant HIV prevention marketing and educational activities, developed partnerships with organizations serving Hispanic communities to enhance outreach and services, and obtained funding for a bilingual patient navigation program with academic partners to provide staff members to help persons overcome barriers and understand the health care system. HIV molecular cluster detection can identify rapid HIV transmission among sexual networks involving ethnic and sexual minority groups, draw attention to the needs of affected populations, and advance health equity through tailored responses that address those needs.

Clusters of Rapid HIV Transmission Among Gay, Bisexual, and Other Men Who Have Sex with Men - United States, 2018-2021.

Gay, bisexual, and other men who have sex with men (MSM) accounted for 68% of new HIV diagnoses in the United States in 2020* (1). Despite advances in treatment and prevention, HIV transmission among MSM continues, in part because of stigma and barriers to accessing prevention and treatment services (2). HIV cluster detection and response, a core strategy of the Ending the HIV Epidemic in the United States initiative,† is an important tool for early identification and response to rapid HIV transmission, including among MSM. To better understand rapid HIV transmission among this population, CDC characterized large HIV molecular clusters detected using analysis of HIV-1 nucleotide sequence data from the National HIV Surveillance System (NHSS).§ Among 38 such clusters first detected during 2018-2019 that had grown to include more than 25 persons by December 2021, 29 occurred primarily among MSM. Clusters primarily among MSM occurred in all geographic regions, and 97% involved multiple states. Clusters were heterogeneous in age, gender identity, and race and ethnicity and had rapid growth rates (median = nine persons added per year). The overall transmission rate at cluster detection was 22 transmission events per 100 person-years, more than six times that of previously estimated national transmission rates (3). Most clusters of rapid HIV transmission occur among MSM. Swift response to reach diverse persons and communities with early, tailored, and focused interventions is essential to reducing HIV transmission (4).

Genomic Surveillance for SARS-CoV-2 Variants Circulating in the United States, December 2020-May 2021.

SARS-CoV-2, the virus that causes COVID-19, is constantly mutating, leading to new variants (1). Variants have the potential to affect transmission, disease severity, diagnostics, therapeutics, and natural and vaccine-induced immunity. In November 2020, CDC established national surveillance for SARS-CoV-2 variants using genomic sequencing. As of May 6, 2021, sequences from 177,044 SARS-CoV-2-positive specimens collected during December 20, 2020-May 6, 2021, from 55 U.S. jurisdictions had been generated by or reported to CDC. These included 3,275 sequences for the 2-week period ending January 2, 2021, compared with 25,000 sequences for the 2-week period ending April 24, 2021 (0.1% and 3.1% of reported positive SARS-CoV-2 tests, respectively). Because sequences might be generated by multiple laboratories and sequence availability varies both geographically and over time, CDC developed statistical weighting and variance estimation methods to generate population-based estimates of the proportions of identified variants among SARS-CoV-2 infections circulating nationwide and in each of the 10 U.S. Department of Health and Human Services (HHS) geographic regions.* During the 2-week period ending April 24, 2021, the B.1.1.7 and P.1 variants represented an estimated 66.0% and 5.0% of U.S. SARS-CoV-2 infections, respectively, demonstrating the rise to predominance of the B.1.1.7 variant of concern† (VOC) and emergence of the P.1 VOC in the United States. Using SARS-CoV-2 genomic surveillance methods to analyze surveillance data produces timely population-based estimates of the proportions of variants circulating nationally and regionally. Surveillance findings demonstrate the potential for new variants to emerge and become predominant, and the importance of robust genomic surveillance. Along with efforts to characterize the clinical and public health impact of SARS-CoV-2 variants, surveillance can help guide interventions to control the COVID-19 pandemic in the United States.

Novel Method for Rapid Detection of Spatiotemporal HIV Clusters Potentially Warranting Intervention.

Rapid detection of increases in HIV transmission enables targeted outbreak response efforts to reduce the number of new infections. We analyzed US HIV surveillance data and identified spatiotemporal clusters of diagnoses. This systematic method can help target timely investigations and preventive interventions for maximum public health benefit.

Statistical Method to Detect Tuberculosis Outbreaks among Endemic Clusters in a Low-Incidence Setting.

We previously reported use of genotype surveillance data to predict outbreaks among incident tuberculosis clusters. We propose a method to detect possible outbreaks among endemic tuberculosis clusters. We detected 15 possible outbreaks, of which 10 had epidemiologic data or whole-genome sequencing results. Eight outbreaks were corroborated.

Tuberculosis in Jails and Prisons: United States, 2002-2013.

OBJECTIVES: To describe cases and estimate the annual incidence of tuberculosis in correctional facilities. METHODS: We analyzed 2002 to 2013 National Tuberculosis Surveillance System case reports to characterize individuals who were employed or incarcerated in correctional facilities at time they were diagnosed with tuberculosis. Incidence was estimated with Bureau of Justice Statistics denominators. RESULTS: Among 299 correctional employees with tuberculosis, 171 (57%) were US-born and 82 (27%) were female. Among 5579 persons incarcerated at the time of their tuberculosis diagnosis, 2520 (45%) were US-born and 495 (9%) were female. Median estimated annual tuberculosis incidence rates were 29 cases per 100 000 local jail inmates, 8 per 100 000 state prisoners, and 25 per 100 000 federal prisoners. The foreign-born proportion of incarcerated men 18 to 64 years old increased steadily from 33% in 2002 to 56% in 2013. Between 2009 and 2013, tuberculosis screenings were reported as leading to 10% of diagnoses among correctional employees, 47% among female inmates, and 42% among male inmates. CONCLUSIONS: Systematic screening and treatment of tuberculosis infection and disease among correctional employees and incarcerated individuals remain essential to tuberculosis prevention and control.

A field-validated approach using surveillance and genotyping data to estimate tuberculosis attributable to recent transmission in the United States.

Tuberculosis genotyping data are frequently used to estimate the proportion of tuberculosis cases in a population that are attributable to recent transmission (RT). Multiple factors influence genotype-based estimates of RT and limit the comparison of estimates over time and across geographic units. Additionally, methods used for these estimates have not been validated against field-based epidemiologic assessments of RT. Here we describe a novel genotype-based approach to estimation of RT based on the identification of plausible-source cases, which facilitates systematic comparisons over time and across geographic areas. We compared this and other genotype-based RT estimation approaches with the gold standard of field-based assessment of RT based on epidemiologic investigation in Arkansas, Maryland, and Massachusetts during 1996-2000. We calculated the sensitivity and specificity of each approach for epidemiologic evidence of RT and calculated the accuracy of each approach across a range of hypothetical RT prevalence rates plausible for the United States. The sensitivity, specificity, and accuracy of genotype-based RT estimates varied by approach. At an RT prevalence of 10%, accuracy ranged from 88.5% for state-based clustering to 94.4% with our novel approach. Our novel, field-validated approach allows for systematic assessments over time and across public health jurisdictions of varying geographic size, with an established level of accuracy.

Simulation of Full HIV Cluster Networks in a Nationally Representative Model Indicates Intervention Opportunities.

BACKGROUND: Clusters of rapid HIV transmission in the United States are increasingly recognized through analysis of HIV molecular sequence data reported to the National HIV Surveillance System. Understanding the full extent of cluster networks is important to assess intervention opportunities. However, full cluster networks include undiagnosed and other infections that cannot be systematically observed in real life. METHODS: We replicated HIV molecular cluster networks during 2015-2017 in the United States using a stochastic dynamic network simulation model of sexual transmission of HIV. Clusters were defined at the 0.5% genetic distance threshold. Ongoing priority clusters had growth of ≥3 diagnoses/year in multiple years; new priority clusters first had ≥3 diagnoses/year in 2017. We assessed the full extent, composition, and transmission rates of new and ongoing priority clusters. RESULTS: Full clusters were 3-9 times larger than detected clusters, with median detected cluster sizes in new and ongoing priority clusters of 4 (range 3-9) and 11 (range 3-33), respectively, corresponding to full cluster sizes with a median of 14 (3-74) and 94 (7-318), respectively. A median of 36.3% (range 11.1%-72.6%) of infections in the full new priority clusters were undiagnosed. HIV transmission rates in these clusters were >4 times the overall rate observed in the entire simulation. CONCLUSIONS: Priority clusters reflect networks with rapid HIV transmission. The substantially larger full extent of these clusters, high proportion of undiagnosed infections, and high transmission rates indicate opportunities for public health intervention and impact.

Effectiveness of 1 dose of 2009 influenza A (H1N1) vaccine at preventing hospitalization with pandemic H1N1 influenza in children aged 7 months-9 years.

The availability of a well-established immunization registry to provide vaccination information, a school-located vaccination campaign followed by continued 2009 influenza A (H1N1) (pH1N1) activity, and a requirement to report hospitalized influenza cases provided an opportunity to estimate vaccine effectiveness (VE) of an initial dose of pH1N1 monovalent vaccine in children aged 7 months-9 years. Seventy-eight case children and 729 date-of-birth- and zipcode-matched controls were studied. The VE of a single vaccine dose in preventing pH1N1 hospitalization ≥ 14 days after vaccination was 82% (95% confidence interval [CI], 0%-100%; P = .04) in children aged 3-9 years but was zero (-3%; 95% CI, <0%-75%) in children aged 7-35 months. These findings are consistent with those from prelicensure immunogenicity studies and have implications for interpretation of immunogenicity studies and setting priorities for vaccination of young children in future pandemics. Immunization registries can provide a simple, rapid assessment of VE to evaluate and inform vaccination policy.

Estimating the prevalence of chronic hepatitis B virus infection--New York City, 2008.

Chronic hepatitis B virus (HBV) infection is a preventable cause of liver failure, cirrhosis, and liver cancer; estimated chronic HBV infection prevalence is 0.3-0.5% in the U.S.A. Prevalence in New York City (NYC) is likely higher because foreign-born persons, who represent 36% of NYC's population versus 11% nationwide, bear a disproportionate burden of chronic HBV infection. However, because no comprehensive, population-based survey of chronic HBV infection has been conducted in NYC, a reliable prevalence estimate is unavailable. We used two approaches to estimate chronic HBV infection prevalence in NYC: (1) a census-based estimate, combining local and national prevalence data for specific populations, and (2) a surveillance-based estimate, using data from NYC's Department of Health and Mental Hygiene Hepatitis B Surveillance Registry and adjusting for out-migration and deaths. Results from both the census-based estimate and the surveillance-based estimate were similar, with an estimated prevalence of chronic HBV in NYC of 1.2%. This estimate is two to four times the estimated prevalence for the U.S.A. as a whole. According to the census-based estimate, >93% of all cases in NYC are among persons who are foreign-born, and approximately half of those are among persons born in China. These findings underscore the importance of local data for tailoring programmatic efforts to specific foreign-born populations in NYC. In particular, Chinese-language programs and health education materials are critical. Reliable estimates are important for policymakers in local jurisdictions to better understand their own population's needs and can help target primary care services, prevention materials, and education.

Baseline HIV drug-resistance testing: 12 US jurisdictions, 2014-2019.

OBJECTIVE: To understand recent patterns in reported baseline HIV drug-resistance testing over time in the United States. DESIGN: Data from the National HIV Surveillance System for persons who were aged at least 13 years at the time of HIV diagnosis during 2014-2019 and resided in one of 12 US jurisdictions with high levels of reporting in 2014 and 2015. METHODS: Among persons included in the analysis, we calculated the total proportion of HIV diagnoses occurring during 2014-2019 with a reported baseline sequence by year of diagnosis and sequence type. A baseline sequence was defined as any protease/ reverse transcriptase (PR/RT) or integrase sequence generated from a specimen collected 90 days or less after diagnosis. RESULTS: During 2014-2019, reported levels of baseline PR/RT (with or without integrase) testing varied by year from 46.9% to 51.8% without any clear pattern over time. PR/RT with integrase testing increased (8.3-19.4%) and integrase-only testing remained low (1.9-1.3%). CONCLUSION: While reported levels of baseline PR/RT (with or without integrase) testing have remained sufficiently high for the purposes of molecular cluster detection, higher levels would strengthen jurisdictions' and the Centers for Disease Control and Prevention's ability to monitor trends in HIV drug-resistance and detect and respond to HIV molecular clusters. Efforts to increase levels of reported baseline testing likely need to address both gaps in testing as well as reporting.

The CDC HIV Outbreak Coordination Unit: Developing a Standardized, Collaborative Approach to HIV Outbreak Assessment and Response.

The Centers for Disease Control and Prevention (CDC) and state, territorial, and local health departments have expanded efforts to detect and respond to HIV clusters and outbreaks in the United States. In July 2017, CDC created the HIV Outbreak Coordination Unit (OCU) to ensure consistent and collaborative assessment of requests from health departments for consultation or support on possible HIV clusters and outbreaks of elevated concern. The HIV OCU is a multidisciplinary, cross-organization functional unit within CDC's Division of HIV/AIDS Prevention. HIV OCU members have expertise in areas such as outbreak detection and investigation, prevention, laboratory services, surveillance and epidemiology, policy, communication, and operations. HIV OCU discussions facilitate problem solving, coordination, and situational awareness. Between HIV OCU meetings, designated CDC staff members communicate regularly with health departments to provide support and assessment. During July 2017-December 2019, the HIV OCU reviewed 31 possible HIV clusters and outbreaks (ie, events) in 22 states that were detected by CDC, health departments, or local partners; 17 events involved HIV transmission associated with injection drug use, and other events typically involved sexual transmission or overall increases in HIV diagnoses. CDC supported health departments remotely or on site with planning and prioritization; data collection, management, and analysis; communications; laboratory support; multistate coordination; and expansion of HIV prevention services. The HIV OCU has augmented CDC's support of HIV cluster and outbreak assessment and response at health departments and had important internal organizational benefits. Health departments may benefit from developing or strengthening similar units to coordinate detection and response efforts within and across public health agencies and advance the national Ending the HIV Epidemic initiative.

Molecular surveillance for large outbreaks of tuberculosis in the United States, 2014-2018.

OBJECTIVE: This study describes characteristics of large tuberculosis (TB) outbreaks in the United States detected using novel molecular surveillance methods during 2014-2016 and followed for 2 years through 2018. METHODS: We developed 4 genotype-based detection algorithms to identify large TB outbreaks of ≥10 cases related by recent transmission during a 3-year period. We used whole-genome sequencing and epidemiologic data to assess evidence of recent transmission among cases. RESULTS: There were 24 large outbreaks involving 518 cases; patients were primarily U.S.-born (85.1%) racial/ethnic minorities (84.1%). Compared with all other TB patients, patients associated with large outbreaks were more likely to report substance use, homelessness, and having been diagnosed while incarcerated. Most large outbreaks primarily occurred within residences among families and nonfamilial social contacts. A source case with a prolonged infectious period and difficulties in eliciting contacts were commonly reported contributors to transmission. CONCLUSION: Large outbreak surveillance can inform targeted interventions to decrease outbreak-associated TB morbidity.

Investigating 2009 pandemic influenza A (H1N1) in US schools: what have we learned?

US investigations of school-based outbreaks of 2009 pandemic influenza A (H1N1) virus infection characterized influenza-like illness (ILI) attack rates, transmission risk factors, and adherence to nonpharmaceutical interventions. We summarize seven school-based investigations conducted during April-June 2009 to determine what questions might be answered by future investigations. Surveys were administered 5-28 days after identification of the outbreaks, and participation rates varied among households (39-86%) and individuals (24-49%). Compared with adults (4%-10%) and children aged <4 years (2%-7%), elementary through university students had higher ILI attack rates (4%-32%). Large gatherings or close contact with sick persons were identified as transmission risk factors. More participants reported adherence to hygiene measures, but fewer reported adherence to isolation measures. Challenges included low participation and delays in survey initiation that potentially introduced bias. Although school-based investigations can increase our understanding of epidemiology and prevention strategy effectiveness, investigators should decide which objectives are most feasible, given timing and design constraints.

Household transmission of 2009 influenza A (H1N1) virus after a school-based outbreak in New York City, April-May 2009.

In April 2009, an outbreak due to infection with the 2009 pandemic influenza A (H1N1) virus (pH1N1) was investigated in a New York City high school. We surveyed household contacts of ill students to characterize the extent of transmission within households, identify contact groups at highest risk for illness, and assess the potential for preventing household transmission. Influenza-like illness (ILI) was reported by 79 of 702 household contacts (11.3% attack rate). Multivariate analysis showed that older age was protective: for each increasing year of age, the risk of ILI was reduced 5%. Additional protective factors included antiviral prophylaxis and having had a household discussion about influenza. Providing care for the index case patient and watching television with the index case patient were risk factors among parents and siblings, respectively. Fifty percent of cases occurred within 3 days of onset of illness in the student. These factors have implications for mitigating the impact of pH1N1 transmission.

Progression and transmission of HIV (PATH 4.0)-A new agent-based evolving network simulation for modeling HIV transmission clusters.

We present the Progression and Transmission of HIV (PATH 4.0), a simulation tool for analyses of cluster detection and intervention strategies. Molecular clusters are groups of HIV infections that are genetically similar, indicating rapid HIV transmission where HIV prevention resources are needed to improve health outcomes and prevent new infections. PATH 4.0 was constructed using a newly developed agent-based evolving network modeling (ABENM) technique and evolving contact network algorithm (ECNA) for generating scale-free networks. ABENM and ECNA were developed to facilitate simulation of transmission networks for low-prevalence diseases, such as HIV, which creates computational challenges for current network simulation techniques. Simulating transmission networks is essential for studying network dynamics, including clusters. We validated PATH 4.0 by comparing simulated projections of HIV diagnoses with estimates from the National HIV Surveillance System (NHSS) for 2010-2017. We also applied a cluster generation algorithm to PATH 4.0 to estimate cluster features, including the distribution of persons with diagnosed HIV infection by cluster status and size and the size distribution of clusters. Simulated features matched well with NHSS estimates, which used molecular methods to detect clusters among HIV nucleotide sequences of persons with HIV diagnosed during 2015-2017. Cluster detection and response is a component of the U.S. Ending the HIV Epidemic strategy. While surveillance is critical for detecting clusters, a model in conjunction with surveillance can allow us to refine cluster detection methods, understand factors associated with cluster growth, and assess interventions to inform effective response strategies. As surveillance data are only available for cases that are diagnosed and reported, a model is a critical tool to understand the true size of clusters and assess key questions, such as the relative contributions of clusters to onward transmissions. We believe PATH 4.0 is the first modeling tool available to assess cluster detection and response at the national-level and could help inform the national strategic plan.

HIV Cluster and Outbreak Detection and Response: The Science and Experience.

The Respond pillar of the Ending the HIV Epidemic in the U.S. initiative, which consists of activities also known as cluster and outbreak detection and response, offers a framework to guide tailored implementation of proven HIV prevention strategies where transmission is occurring most rapidly. Cluster and outbreak response involves understanding the networks in which rapid transmission is occurring; linking people in the network to essential services; and identifying and addressing gaps in programs and services such as testing, HIV and other medical care, pre-exposure prophylaxis, and syringe services programs. This article reviews the experience gained through 30 HIV cluster and outbreak responses in North America during 2000-2020 to describe approaches for implementing these core response strategies. Numerous jurisdictions that have implemented these response strategies have demonstrated success in improving outcomes related to HIV care and viral suppression, testing, use of prevention services, and reductions in transmission or new diagnoses. Efforts to address important gaps in service delivery revealed by cluster and outbreak detection and response can strengthen prevention efforts broadly through multidisciplinary, multisector collaboration. In this way, the Respond pillar embodies the collaborative, data-guided approach that is critical to the overall success of the Ending the HIV Epidemic in the U.S. initiative.