Prevalence of Repeat Prenatal HIV Screening in New York State.

Description: New York State Department of Health (NYSDOH) recommends that all pregnant patients receive human immunodeficiency virus (HIV) screening during pregnancy. This study assessed the prevalence of repeat prenatal HIV testing and factors associated with receipt of the recommended tests. Methods: Data from the NYSDOH newborn screening program were used to randomly select pregnant persons without HIV who delivered a liveborn infant in 2017. Receipt of repeat testing was defined as an initial HIV test in the first or second trimesters and the final in the third trimester (relaxed); or an initial test in the first trimester and the final in the third trimester (strict). Relative risks (RRs) and 95% confidence intervals were calculated in bivariate analyses. Adjusted RRs were calculated to determine associations between demographic and clinical factors and receipt of repeat HIV testing. Results: The cohort included 2,225 individuals. Roughly one quarter (24%) received the recommended tests in the first or second and third trimesters and 17% received them in the first and third trimesters. Individuals who reported Hispanic or Asian race/ethnicities, had government-funded insurance, started prenatal care in the first trimester, delivered in New York City, or received prenatal hepatitis C virus screening were significantly more likely to receive repeat testing using either definition. Conclusions: Despite the benefits and cost-effectiveness, the prevalence of repeat prenatal HIV screening during the third trimester remains persistently low. Improved messaging and targeted education and resources to assist prenatal providers could reinforce the importance of repeat testing and reduce residual perinatal HIV transmission.

Computational multigene interactions in virus growth and infection spread.

Viruses persist in nature owing to their extreme genetic heterogeneity and large population sizes, which enable them to evade host immune defenses, escape antiviral drugs, and adapt to new hosts. The persistence of viruses is challenging to study because mutations affect multiple virus genes, interactions among genes in their impacts on virus growth are seldom known, and measures of viral fitness are yet to be standardized. To address these challenges, we employed a data-driven computational model of cell infection by a virus. The infection model accounted for the kinetics of viral gene expression, functional gene-gene interactions, genome replication, and allocation of host cellular resources to produce progeny of vesicular stomatitis virus, a prototype RNA virus. We used this model to computationally probe how interactions among genes carrying up to eleven deleterious mutations affect different measures of virus fitness: single-cycle growth yields and multicycle rates of infection spread. Individual mutations were implemented by perturbing biophysical parameters associated with individual gene functions of the wild-type model. Our analysis revealed synergistic epistasis among deleterious mutations in their effects on virus yield; so adverse effects of single deleterious mutations were amplified by interaction. For the same mutations, multicycle infection spread indicated weak or negligible epistasis, where single mutations act alone in their effects on infection spread. These results were robust to simulation in high- and low-host resource environments. Our work highlights how different types and magnitudes of epistasis can arise for genetically identical virus variants, depending on the fitness measure. More broadly, gene-gene interactions can differently affect how viruses grow and spread.

Astrovirology: how viruses enhance our understanding of life in the Universe.

Viruses are the most numerically abundant biological entities on Earth. As ubiquitous replicators of molecular information and agents of community change, viruses have potent effects on the life on Earth, and may play a critical role in human spaceflight, for life-detection missions to other planetary bodies and planetary protection. However, major knowledge gaps constrain our understanding of the Earth's virosphere: (1) the role viruses play in biogeochemical cycles, (2) the origin(s) of viruses and (3) the involvement of viruses in the evolution, distribution and persistence of life. As viruses are the only replicators that span all known types of nucleic acids, an expanded experimental and theoretical toolbox built for Earth's viruses will be pivotal for detecting and understanding life on Earth and beyond. Only by filling in these knowledge and technical gaps we will obtain an inclusive assessment of how to distinguish and detect life on other planetary surfaces. Meanwhile, space exploration requires life-support systems for the needs of humans, plants and their microbial inhabitants. Viral effects on microbes and plants are essential for Earth's biosphere and human health, but virus-host interactions in spaceflight are poorly understood. Viral relationships with their hosts respond to environmental changes in complex ways which are difficult to predict by extrapolating from Earth-based proxies. These relationships should be studied in space to fully understand how spaceflight will modulate viral impacts on human health and life-support systems, including microbiomes. In this review, we address key questions that must be examined to incorporate viruses into Earth system models, life-support systems and life detection. Tackling these questions will benefit our efforts to develop planetary protection protocols and further our understanding of viruses in astrobiology.

Kinetic Modeling and Parameter Estimation of a Prebiotic Peptide Reaction Network.

Although our understanding of how life emerged on Earth from simple organic precursors is speculative, early precursors likely included amino acids. The polymerization of amino acids into peptides and interactions between peptides are of interest because peptides and proteins participate in complex interaction networks in extant biology. However, peptide reaction networks can be challenging to study because of the potential for multiple species and systems-level interactions between species. We developed and employed a computational network model to describe reactions between amino acids to form di-, tri-, and tetra-peptides. Our experiments were initiated with two of the simplest amino acids, glycine and alanine, mediated by trimetaphosphate-activation and drying to promote peptide bond formation. The parameter estimates for bond formation and hydrolysis reactions in the system were found to be poorly constrained due to a network property known as sloppiness. In a sloppy model, the behavior mostly depends on only a subset of parameter combinations, but there is no straightforward way to determine which parameters should be included or excluded. Despite our inability to determine the exact values of specific kinetic parameters, we could make reasonably accurate predictions of model behavior. In short, our modeling has highlighted challenges and opportunities toward understanding the behaviors of complex prebiotic chemical experiments.

Enhancement of Prebiotic Peptide Formation in Cyclic Environments.

The dynamic behaviors of prebiotic reaction networks may be critically important to understanding how larger biopolymers could emerge, despite being unfavorable to form in water. We focus on understanding the dynamics of simple systems, prior to the emergence of replication mechanisms, and what role they may have played in biopolymer formation. We specifically consider the dynamics in cyclic environments using both model and experimental data. Cyclic environmental conditions prevent a system from reaching thermodynamic equilibrium, improving the chance of observing interesting kinetic behaviors. We used an approximate kinetic model to simulate the dynamics of trimetaphosphate (TP)-activated peptide formation from glycine in cyclic wet-dry conditions. The model predicts that environmental cycling allows trimer and tetramer peptides to sustain concentrations above the predicted fixed points of the model due to overshoot, a dynamic phenomenon. Our experiments demonstrate that oscillatory environments can shift product distributions in favor of longer peptides. However, experimental validation of certain behaviors in the kinetic model is challenging, considering that open systems with cyclic environmental conditions break many of the common assumptions in classical chemical kinetics. Overall, our results suggest that the dynamics of simple peptide reaction networks in cyclic environments may have been important for the formation of longer polymers on the early Earth. Similar phenomena may have also contributed to the emergence of reaction networks with product distributions determined not by thermodynamics, but rather by kinetics.

Left Atrial Appendage Occlusion Device Placement Aborted Because of Coronary Artery Bypass Graft.

Left atrial appendage occlusion device (LAAO) implantation among patients who have had coronary artery bypass grafting can be challenging. We report a case of scheduled LAAO device implantation that was aborted due to the anomalous course of a bypass graft that appeared to be adherent to the left atrial appendage. (Level of Difficulty: Intermediate.).

"It's just another tool on my toolbelt": New York state law enforcement officer experiences administering naloxone.

BACKGROUND: Although naloxone is widely acknowledged as a life-saving intervention and a critical tool for first responders, there remains a need to explore how law enforcement officers have adapted to a shifting scope of work. Past research has focused mainly on officer training, their abilities to administer naloxone, and to a lesser extent on their experiences and interactions working with people who use drugs (PWUD). METHODS: A qualitative approach was used to explore officer perspectives and behaviors surrounding responses to incidents of suspected opioid overdose. Between the months of March and September 2017, semi-structured interviews were conducted with 38 officers from 17 counties across New York state (NYS). RESULTS: Analysis of in-depth interviews revealed that officers generally considered the additional responsibility of administering naloxone to have become "part of the job". Many officers reported feeling as though they are expected to wear multiple hats, functioning as both law enforcement and medical personnel and at times juggling contradictory roles. Evolving views on drugs and drug use defined many interviews, as well as the recognition that a punitive approach to working with PWUD is not the solution, emphasizing the need for cohesive, community-wide support strategies. Notable differences in attitudes toward PWUD appeared to be influenced by an officer's connection to someone who uses drugs and/or due to a background in emergency medical services. CONCLUSION: Law enforcement officers in NYS are emerging as an integral part of the continuum of care for PWUD. Our findings are capturing a time of transition as more traditional approaches to law enforcement appear to be shifting toward those prioritizing prevention and diversion. Widespread adoption of naloxone administration by law enforcement officers in NYS is a powerful example of the successful integration of a public health intervention into police work.

Glycine to Oligoglycine via Sequential Trimetaphosphate Activation Steps in Drying Environments.

Polyphosphate-mediated peptide bond formation is central to protein synthesis in modern organisms, but a simpler form of activation likely preceded the emergence of proteins and RNA. One suggested scenario involves trimetaphosphate (TP), an inorganic phosphate that promotes peptide condensation. Peptide bond formation can also be promoted by high pH and drying, but the interaction of these factors with TP has yet to be characterized kinetically. We studied the formation of glycine oligomers formed under initially alkaline conditions in the presence of TP during the process of drying. Oligopeptide products sampled over 24 h were analyzed by functionalization and high-performance liquid chromatography with ultraviolet absorption (UV-HPLC). As they dried, two different pH-dependent mechanisms dominated during different stages of the process. The first mechanism occurs in alkaline solutions and activates monomer amino acids to form dimers while reducing the pH. Our results then become consistent with a second mechanism that proceeds at neutral pH and consumes dimers to form longer products. The possibility that a series of reactions might occur where the first reaction changes the environment to favor the second, and so on, may have broader implications for prebiotic polymerization. Studying how the environment changes during time-varying conditions, like drying, could help us understand how organic polymers formed during the origin of life.

Naloxone administration by law enforcement officers in New York State (2015-2020).

BACKGROUND: The COVID-19 pandemic has amplified the need for wide deployment of effective harm reduction strategies in preventing opioid overdose mortality. Placing naloxone in the hands of key responders, including law enforcement officers who are often first on the scene of a suspected overdose, is one such strategy. New York State (NYS) was one of the first states to implement a statewide law enforcement naloxone administration program. This article provides an overview of the law enforcement administration of naloxone in NYS between 2015 and 2020 and highlights key characteristics of over 9000 opioid overdose reversal events. METHODS: Data in naloxone usage report forms completed by police officers were compiled and analyzed. Data included 9133 naloxone administration reports by 5835 unique officers located in 60 counties across NYS. Descriptive statistics were used to examine attributes of the aided individuals, including differences between fatal and non-fatal incidents. Additional descriptive analyses were conducted for incidents in which law enforcement officers arrived first at the scene of suspected overdose. Comparisons were made to examine year-over-year trends in administration as naloxone formulations were changed. Quantitative analysis was supplemented by content analysis of officers' notes (n = 2192). RESULTS: In 85.9% of cases, law enforcement officers arrived at the scene of a suspected overdose prior to emergency medical services (EMS) personnel. These officers assessed the likelihood of an opioid overdose having occurred based on the aided person's breathing status and other information obtained on the scene. They administered an average of 2 doses of naloxone to aided individuals. In 36.8% of cases, they reported additional administration of naloxone by other responders including EMS, fire departments, and laypersons. Data indicated the aided survived the suspected overdose in 87.4% of cases. CONCLUSIONS: With appropriate training, law enforcement personnel were able to recognize opioid overdoses and prevent fatalities by administering naloxone and carrying out time-sensitive medical interventions. These officers provided life-saving services to aided individuals alongside other responders including EMS, fire departments, and bystanders. Further expansion of law enforcement naloxone administration nationally and internationally could help decrease opioid overdose mortality.

Reliance of Host-Encoded Regulators of Retromobility on Ty1 Promoter Activity or Architecture.

The Ty1 retrotransposon family is maintained in a functional but dormant state by its host, Saccharomyces cerevisiae. Several hundred RHF and RTT genes encoding co-factors and restrictors of Ty1 retromobility, respectively, have been identified. Well-characterized examples include MED3 and MED15, encoding subunits of the Mediator transcriptional co-activator complex; control of retromobility by Med3 and Med15 requires the Ty1 promoter in the U3 region of the long terminal repeat. To characterize the U3-dependence of other Ty1 regulators, we screened a library of 188 known rhf and rtt mutants for altered retromobility of Ty1his3AI expressed from the strong, TATA-less TEF1 promoter or the weak, TATA-containing U3 promoter. Two classes of genes, each including both RHFs and RTTs, were identified. The first class comprising 82 genes that regulated Ty1his3AI retromobility independently of U3 is enriched for RHF genes that restrict the G1 phase of the cell cycle and those involved in transcriptional elongation and mRNA catabolism. The second class of 51 genes regulated retromobility of Ty1his3AI driven only from the U3 promoter. Nineteen U3-dependent regulators (U3DRs) also controlled retromobility of Ty1his3AI driven by the weak, TATA-less PSP2 promoter, suggesting reliance on the low activity of U3. Thirty-one U3DRs failed to modulate P PSP2 -Ty1his3AI retromobility, suggesting dependence on the architecture of U3. To further investigate the U3-dependency of Ty1 regulators, we developed a novel fluorescence-based assay to monitor expression of p22-Gag, a restriction factor expressed from the internal Ty1i promoter. Many U3DRs had minimal effects on levels of Ty1 RNA, Ty1i RNA or p22-Gag. These findings uncover a role for the Ty1 promoter in integrating signals from diverse host factors to modulate Ty1 RNA biogenesis or fate.

Mathematical modeling of the lower urinary tract: A review.

AIMS: Understand what progress has been made toward a functionally predictive lower urinary tract (LUT) model, identify knowledge gaps, and develop from them a path forward. METHODS: We surveyed prominent mathematical models of the basic LUT components (bladder, urethra, and their neural control) and categorized the common modeling strategies and theoretical assumptions associated with each component. Given that LUT function emerges from the interaction of these components, we emphasized attempts to model their connections, and highlighted unmodeled aspects of LUT function. RESULTS: There is currently no satisfactory model of the LUT in its entirety that can predict its function in response to disease, treatment, or other perturbations. In particular, there is a lack of physiologically based mathematical descriptions of the neural control of the LUT. CONCLUSIONS: Based on our survey of the work to date, a potential path to a predictive LUT model is a modular effort in which models are initially built of individual tissue-level components using methods that are extensible and interoperable, allowing them to be connected and tested in a common framework. A modular approach will allow the larger goal of a comprehensive LUT model to be in sight while keeping individual efforts manageable, ensure new models can straightforwardly build on prior research, respect potential interactions between components, and incentivize efforts to model absent components. Using a modular framework and developing models based on physiological principles, to create a functionally predictive model is a challenge that the field is ready to undertake.

Virus-like Particles: Measures and Biological Functions.

Virus-like particles resemble infectious virus particles in size, shape, and molecular composition; however, they fail to productively infect host cells. Historically, the presence of virus-like particles has been inferred from total particle counts by microscopy, and infectious particle counts or plaque-forming-units (PFUs) by plaque assay; the resulting ratio of particles-to-PFUs is often greater than one, easily 10 or 100, indicating that most particles are non-infectious. Despite their inability to hijack cells for their reproduction, virus-like particles and the defective genomes they carry can exhibit a broad range of behaviors: interference with normal virus growth during co-infections, cell killing, and activation or inhibition of innate immune signaling. In addition, some virus-like particles become productive as their multiplicities of infection increase, a sign of cooperation between particles. Here, we review established and emerging methods to count virus-like particles and characterize their biological functions. We take a critical look at evidence for defective interfering virus genomes in natural and clinical isolates, and we review their potential as antiviral therapeutics. In short, we highlight an urgent need to better understand how virus-like genomes and particles interact with intact functional viruses during co-infection of their hosts, and their impacts on the transmission, severity, and persistence of virus-associated diseases.

Reducing Disparities: A Virtual Quality Improvement Collaborative Resulted in Better Health Outcomes for 4 Target Populations Disproportionately Affected by HIV.

CONTEXT: Although viral suppression rates have recently increased among people with HIV, specific populations still experience disparities in health outcomes, a priority in the national response to end the HIV epidemic. PURPOSE: The end+disparities ECHO Collaborative, a quality improvement initiative among HIV providers in the United States from June 2018 to December 2019, created virtual communities of practice to measurably increase viral suppression rates in populations disproportionately affected by HIV: men who have sex with men of color, Black/African American and Latina women, youth aged 13 to 24 years, and transgender people. METHODS: Participating Ryan White HIV/AIDS Program-funded providers prioritized their improvement efforts to focus on one target population and joined virtual affinity sessions with other providers focused on that population for guidance by subject matter experts and exchanges with peer providers. During 9 submission cycles, providers reported their viral suppression data for the preceding 12 months. MAIN OUTCOME MEASURES: The principal outcome measures were changes in viral suppression rates among 4 target populations and changes in viral suppression gaps compared with the rest of HIV-infected patients served by the same agency. RESULTS: A total of 90 providers were included in the data analyses with an average of 110 775 reported patients, out of which 19 442 represented the targeted populations. The average viral suppression rates for agency-selected populations increased from 79.2% to 82.3% (a 3.9% increase), while the remaining caseload increased at a lower rate from 84.9% to 86.1% (a 1.4% increase). The viral suppression gap was reduced from 5.7% to 3.8%, a 33.5% reduction. Improvements were found across all target populations. CONCLUSIONS: The collaborative demonstrated improved health outcomes and reductions in HIV-related health disparities, moving toward ending the HIV epidemic. The model of utilizing low-cost videoconferencing technologies to create virtual communities of learning is well suited to mitigate other disease-related disparities, nationally and abroad.

Resolving the Rules of Robustness and Resilience in Biology Across Scales.

Why do some biological systems and communities persist while others fail? Robustness, a system's stability, and resilience, the ability to return to a stable state, are key concepts that span multiple disciplines within and outside the biological sciences. Discovering and applying common rules that govern the robustness and resilience of biological systems is a critical step toward creating solutions for species survival in the face of climate change, as well as the for the ever-increasing need for food, health, and energy for human populations. We propose that network theory provides a framework for universal scalable mathematical models to describe robustness and resilience and the relationship between them, and hypothesize that resilience at lower organization levels contribute to robust systems. Insightful models of biological systems can be generated by quantifying the mechanisms of redundancy, diversity, and connectivity of networks, from biochemical processes to ecosystems. These models provide pathways towards understanding how evolvability can both contribute to and result from robustness and resilience under dynamic conditions. We now have an abundance of data from model and non-model systems and the technological and computational advances for studying complex systems. Several conceptual and policy advances will allow the research community to elucidate the rules of robustness and resilience. Conceptually, a common language and data structure that can be applied across levels of biological organization needs to be developed. Policy advances such as cross-disciplinary funding mechanisms, access to affordable computational capacity, and the integration of network theory and computer science within the standard biological science curriculum will provide the needed research environments. This new understanding of biological systems will allow us to derive ever more useful forecasts of biological behaviors and revolutionize the engineering of biological systems that can survive changing environments or disease, navigate the deepest oceans, or sustain life throughout the solar system.

Kinetics of Asian and African Zika virus lineages over single-cycle and multi-cycle growth in culture: Gene expression, cell killing, virus production, and mathematical modeling.

Since 2014, an Asian lineage of Zika virus has caused outbreaks, and it has been associated with neurological disorders in adults and congenital defects in newborns. The resulting threat of the Zika virus to human health has prompted the development of new vaccines, which have yet to be approved for human use. Vaccines based on the attenuated or chemically inactivated virus will require large-scale production of the intact virus to meet potential global demands. Intact viruses are produced by infecting cultures of susceptible cells, a dynamic process that spans from hours to days and has yet to be optimized. Here, we infected Vero cells adhesively cultured in well-plates with two Zika virus strains: a recently isolated strain from the Asian lineage, and a cell-culture-adapted strain from the African lineage. At different time points post-infection, virus particles in the supernatant were quantified; further, microscopy images were used to quantify cell density and the proportion of cells expressing viral protein. These measurements were performed across multiple replicate samples of one-step infections every four hours over 60 h and for multi-step infections every four to 24 h over 144 h, generating a rich data set. For each set of data, mathematical models were developed to estimate parameters associated with cell infection and virus production. The African-lineage strain was found to produce a 14-fold higher yield than the Asian-lineage strain in one-step growth and a sevenfold higher titer in multi-step growth, suggesting a benefit of cell-culture adaptation for developing a vaccine strain. We found that image-based measurements were critical for discriminating among different models, and different parameters for the two strains could account for the experimentally observed differences. An exponential-distributed delay model performed best in accounting for multi-step infection of the Asian strain, and it highlighted the significant sensitivity of virus titer to the rate of viral degradation, with implications for optimization of vaccine production. More broadly, this study highlights how image-based measurements can contribute to the discrimination of virus-culture models for the optimal production of inactivated and attenuated whole-virus vaccines.

Toward Molecular Cooperation by De Novo Peptides.

Theoretical models of the chemical origins of life depend on self-replication or autocatalysis, processes that arise from molecular interactions, recruitment, and cooperation. Such models often lack details about the molecules and reactions involved, giving little guidance to those seeking to detect signs of interaction, recruitment, or cooperation in the laboratory. Here, we develop minimal mathematical models of reactions involving specific chemical entities: amino acids and their condensation reactions to form de novo peptides. Reactions between two amino acids form a dipeptide product, which enriches linearly in time; subsequent recruitment of such products to form longer peptides exhibit super-linear growth. Such recruitment can be reciprocated: a peptide contributes to and benefits from the formation of one or more other peptides; in this manner, peptides can cooperate and thereby exhibit autocatalytic or exponential growth. We have started to test these predictions by quantitative analysis of de novo peptide synthesis conducted by wet-dry cycling of a five-amino acid mixture over 21 days. Using high-performance liquid chromatography, we tracked abundance changes for >60 unique peptide species. Some species were highly transient, with the emergence of up to 17 new species and the extinction of nine species between samplings, while other species persisted across many cycles. Of the persisting species, most exhibited super-linear growth, a sign of recruitment anticipated by our models. This work shows how mathematical modeling and quantitative analysis of kinetic data can guide the search for prebiotic chemistries that have the potential to cooperate and replicate.

Patterns of virus growth across the diversity of life.

Although viruses in their natural habitats add up to less than 10% of the biomass, they contribute more than 90% of the genome sequences [1]. These viral sequences or 'viromes' encode viruses that populate the Earth's oceans [2, 3] and terrestrial environments [4, 5], where their infections impact life across diverse ecological niches and scales [6, 7], including humans [8-10]. Most viruses have yet to be isolated and cultured [11-13], and surprisingly few efforts have explored what analysis of available data might reveal about their nature. Here, we compiled and analyzed seven decades of one-step growth and other data for viruses from six major families, including their infections of archaeal, bacterial and eukaryotic hosts [14-191]. We found that the use of host cell biomass for virus production was highest for archaea at 10%, followed by bacteria at 1% and eukarya at 0.01%, highlighting the degree to which viruses of archaea and bacteria exploit their host cells. For individual host cells, the yield of virus progeny spanned a relatively narrow range (10-1000 infectious particles per cell) compared with the million-fold difference in size between the smallest and largest cells. Furthermore, healthy and infected host cells were remarkably similar in the time they needed to multiply themselves or their virus progeny. Specifically, the doubling time of healthy cells and the delay time for virus release from infected cells were not only correlated (r = 0.71, p < 10-10, n = 101); they also spanned the same range from tens of minutes to about a week. These results have implications for better understanding the growth, spread and persistence of viruses in complex natural habitats that abound with diverse hosts, including humans and their associated microbes.

COVID-19 Outcomes Among Persons Living With or Without Diagnosed HIV Infection in New York State.

Importance: New York State has been an epicenter for both the US coronavirus disease 2019 (COVID-19) and HIV/AIDS epidemics. Persons living with diagnosed HIV may be more prone to COVID-19 infection and severe outcomes, yet few studies have assessed this possibility at a population level. Objective: To evaluate the association between HIV diagnosis and COVID-19 diagnosis, hospitalization, and in-hospital death in New York State. Design, Setting, and Participants: This cohort study, conducted in New York State, including New York City, between March 1 and June 15, 2020, matched data from HIV surveillance, COVID-19 laboratory-confirmed diagnoses, and hospitalization databases to provide a full population-level comparison of COVID-19 outcomes between persons living with diagnosed HIV and persons living without diagnosed HIV. Exposures: Diagnosis of HIV infection through December 31, 2019. Main Outcomes and Measures: The main outcomes were COVID-19 diagnosis, hospitalization, and in-hospital death. COVID-19 diagnoses, hospitalizations, and in-hospital death rates comparing persons living with diagnosed HIV with persons living without dianosed HIV were computed, with unadjusted rate ratios and indirect standardized rate ratios (sRR), adjusting for sex, age, and region. Adjusted rate ratios (aRRs) for outcomes specific to persons living with diagnosed HIV were assessed by age, sex, region, race/ethnicity, transmission risk, and CD4+ T-cell count-defined HIV disease stage, using Poisson regression models. Results: A total of 2988 persons living with diagnosed HIV (2109 men [70.6%]; 2409 living in New York City [80.6%]; mean [SD] age, 54.0 [13.3] years) received a diagnosis of COVID-19. Of these persons living with diagnosed HIV, 896 were hospitalized and 207 died in the hospital through June 15, 2020. After standardization, persons living with diagnosed HIV and persons living without diagnosed HIV had similar diagnosis rates (sRR, 0.94 [95% CI, 0.91-0.97]), but persons living with diagnosed HIV were hospitalized more than persons living without diagnosed HIV, per population (sRR, 1.38 [95% CI, 1.29-1.47]) and among those diagnosed (sRR, 1.47 [95% CI, 1.37-1.56]). Elevated mortality among persons living with diagnosed HIV was observed per population (sRR, 1.23 [95% CI, 1.07-1.40]) and among those diagnosed (sRR, 1.30 [95% CI, 1.13-1.48]) but not among those hospitalized (sRR, 0.96 [95% CI, 0.83-1.09]). Among persons living with diagnosed HIV, non-Hispanic Black individuals (aRR, 1.59 [95% CI, 1.40-1.81]) and Hispanic individuals (aRR, 2.08 [95% CI, 1.83-2.37]) were more likely to receive a diagnosis of COVID-19 than White individuals, but they were not more likely to be hospitalized once they received a diagnosis or to die once hospitalized. Hospitalization risk increased with disease progression to HIV stage 2 (aRR, 1.29 [95% CI, 1.11-1.49]) and stage 3 (aRR, 1.69 [95% CI, 1.38-2.07]) relative to stage 1. Conclusions and Relevance: In this cohort study, persons living with diagnosed HIV experienced poorer COVID-related outcomes relative to persons living without diagnosed HIV; Previous HIV diagnosis was associated with higher rates of severe disease requiring hospitalization, and hospitalization risk increased with progression of HIV disease stage.

Elevated COVID-19 outcomes among persons living with diagnosed HIV infection in New York State: Results from a population-level match of HIV, COVID-19, and hospitalization databases.

BACKGROUND: New York State (NYS) has been an epicenter for both COVID-19 and HIV/AIDS epidemics. Persons Living with diagnosed HIV (PLWDH) may be more prone to COVID-19 infection and severe outcomes, yet few population-based studies have assessed the extent to which PLWDH are diagnosed, hospitalized, and have died with COVID-19, relative to non-PLWDH. METHODS: NYS HIV surveillance, COVID-19 laboratory confirmed diagnoses, and hospitalization databases were matched. COVID-19 diagnoses, hospitalization, and in-hospital death rates comparing PLWDH to non-PLWDH were computed, with unadjusted rate ratios (RR) and indirect standardized RR (sRR), adjusting for sex, age, and region. Adjusted RR (aRR) for outcomes among PLWDH were assessed by age/CD4-defined HIV disease stage, and viral load suppression, using Poisson regression models. RESULTS: From March 1-June 7, 2020, PLWDH were more frequently diagnosed with COVID-19 than non-PLWDH in unadjusted (RR [95% confidence interval (CI)]: 1.43[1.38-1.48), 2,988 PLWDH], but not in adjusted comparisons (sRR [95% CI]: 0.94[0.91-0.97]). Per-population COVID-19 hospitalization was higher among PLWDH (RR [95% CI]: 2.61[2.45-2.79], sRR [95% CI]: 1.38[1.29-1.47], 896 PLWDH), as was in-hospital death (RR [95% CI]: 2.55[2.22-2.93], sRR [95%CI]: 1.23 [1.07-1.40], 207 PLWDH), albeit not among those hospitalized (sRR [95% CI]: 0.96[0.83-1.09]). Among PLWDH, hospitalization risk increased with disease progression from HIV Stage 1 to Stage 2 (aRR [95% CI]:1.27[1.09-1.47]) and Stage 3 (aRR [95% CI]: 1.54[1.24-1.91]), and for those virally unsuppressed (aRR [95% CI]: 1.54[1.24-1.91]). CONCLUSION: PLWDH experienced poorer COVID-related outcomes relative to non-PLWDH, with 1-in-522 PLWDH dying with COVID-19, seemingly driven by higher rates of severe disease requiring hospitalization.