The global mpox epidemic in 2022 was likely caused by transmission of mpox virus (MPXV) through sexual contact networks, with New York City (NYC) experiencing the first and largest outbreak in the United States. By performing a phylogeographic and epidemiological analysis of MPXV, we identify at least 200 introductions of MPXV into NYC and 84 leading to onward transmission. Through a comparative analysis with human immunodeficiency virus (HIV) in NYC, we find that both MPXV and HIV genomic cluster sizes are best fit by scale-free distributions and that people in MPXV clusters are more likely to have previously received an HIV diagnosis (odds ratio=1.58; p=0.012) and be a member of a recently growing HIV transmission cluster, indicating overlapping sexual contact networks. We then model the transmission of MPXV through sexual contact networks and show that highly connected individuals would be disproportionately infected at the start of an epidemic, thereby likely resulting in the exhaustion of the most densely connected parts of the sexual network. This dynamic explains the rapid expansion and decline of the NYC outbreak, as well as the estimated cumulative incidence of less than 2% within high-risk populations. By synthesizing the genomic epidemiology of MPXV and HIV with epidemic modeling, we demonstrate that MPXV transmission dynamics can be understood by general principles of sexually transmitted pathogens.

With the rapid spread and evolution of SARS-CoV-2, the ability to monitor its transmission and distinguish among viral lineages is critical for pandemic response efforts. The most commonly used software for the lineage assignment of newly isolated SARS-CoV-2 genomes is pangolin, which offers two methods of assignment, pangoLEARN and pUShER. PangoLEARN rapidly assigns lineages using a machine learning algorithm, while pUShER performs a phylogenetic placement to identify the lineage corresponding to a newly sequenced genome. In a preliminary study, we observed that pangoLEARN (decision tree model), while substantially faster than pUShER, offered less consistency across different versions of pangolin v3. Here, we expand upon this analysis to include v3 and v4 of pangolin, which moved the default algorithm for lineage assignment from pangoLEARN in v3 to pUShER in v4, and perform a thorough analysis confirming that pUShER is not only more stable across versions but also more accurate. Our findings suggest that future lineage assignment algorithms for various pathogens should consider the value of phylogenetic placement.

New York City (NYC) was one of the hotspots of monkeypox virus (MPXV) infections in the United States during the multi-country mpox outbreak in 2022. This study used the most comprehensive dataset to date to investigate the genomic characteristics of MPXV in NYC. We performed Nextclade lineage assignment, phylogenetic and mutational analyses on 1,138 specimens from 748 individuals at the NYC Public Health Lab in the context of 2,968 MPXV sequences sampled globally. Nextclade lineage assignment showed B.1.12 as a NYC specific lineage and phylogenetic analysis showed NYC and North America specific clades. The majority of mutations showed signatures of APOBEC3 activity. When looking at the intra-host genomic diversity for MPXV, distinct MPXV genomic profiles were observed in 6.4% of individuals with multiple sampled specimens, with at least 4.2% of NYC cases due to multiple MPXV infections from distinct viral strains. Further, 13% of the sequences in infected patients had a lack of concordance between epidemiologic and genetic linkages. This study identified NYC-specific MPXV genomic profiles and provided a conservative estimate of simultaneous infections with multiple MPXV variants, likely due to behavioral risk factors during the peak of the outbreak in July 2022. Improving concordance between genomic and epidemiological clusters for mpox investigations may require expanding partnerships with testing labs, clinics, and community groups to enhance the representativeness of MPXV samples that are available for sequencing. ### Competing Interest Statement The authors have declared no competing interest.

Socio-economic disparities were associated with disproportionate viral incidence between neighborhoods of New York City (NYC) during the first wave of SARS-CoV-2. We investigated how these disparities affected the co-circulation of SARS-CoV-2 variants during the second wave in NYC. We tested for correlation between the prevalence, in late 2020/early 2021, of Alpha, Iota, Iota with E484K mutation (Iota-E484K), and B.1-like genomes and pre-existing immunity (seropositivity) in NYC neighborhoods. In the context of varying seroprevalence we described socio-economic profiles of neighborhoods and performed migration and lineage persistence analyses using a Bayesian phylogeographical framework. Seropositivity was greater in areas with high poverty and a larger proportion of Black and Hispanic or Latino residents. Seropositivity was positively correlated with the proportion of Iota-E484K and Iota genomes, and negatively correlated with the proportion of Alpha and B.1-like genomes. The proportion of persisting Alpha lineages declined over time in locations with high seroprevalence, whereas the proportion of persisting Iota-E484K lineages remained the same in high seroprevalence areas. During the second wave, the geographic variation of standing immunity, due to disproportionate disease burden during the first wave of SARS-CoV-2 in NYC, allowed for the immune evasive Iota-E484K variant, but not the more transmissible Alpha variant, to circulate in locations with high pre-existing immunity.

Severe mpox has been observed in people with advanced human immunodeficiency virus (HIV). We describe clinical outcomes of 13 patients with advanced HIV (CD4 <200 cells/mu L), severe mpox, and multiorgan involvement. Despite extended tecovirimat courses and additional agents, including vaccinia immune globulin, cidofovir, and brincidofovir, this group experienced prolonged hospitalizations and high mortality.

Severe mpox has been observed in people with advanced human immunodeficiency virus (HIV). We describe clinical outcomes of 13 patients with advanced HIV (CD4 <200 cells/μL), severe mpox, and multiorgan involvement. Despite extended tecovirimat courses and additional agents, including vaccinia immune globulin, cidofovir, and brincidofovir, this group experienced prolonged hospitalizations and high mortality.

AbstractGenomic surveillance data are used to detect communicable disease clusters, typically by applying rule-based signaling criteria, which can be arbitrary. We applied the prospective tree-temporal scan statistic (TreeScan) to genomic data with a hierarchical nomenclature to search for recent case increases at any granularity, from large phylogenetic branches to small groups of indistinguishable isolates. Using COVID-19 and salmonellosis cases diagnosed among New York City (NYC) residents and reported to the NYC Health Department, we conducted weekly analyses to detect emerging SARS-CoV-2 variants based on Pango lineages and clusters ofSalmonellaisolates based on allele codes. The SARS-CoV-2 Omicron subvariant EG.5.1 first signaled as locally emerging on June 22, 2023, seven weeks before the World Health Organization designated it as a variant of interest. During one year of salmonellosis analyses, TreeScan detected fifteen credible clusters worth investigating for common exposures and two data quality issues for correction. A challenge was maintaining timely and specific lineage assignments, and a limitation was that genetic distances between tree nodes were not considered. By automatically sifting through genomic data and generating ranked shortlists of nodes with statistically unusual recent case increases, TreeScan assisted in detecting emerging communicable disease clusters and in prioritizing them for investigation.

Surveillance systems that monitor pathogen genome sequences are critical for rapidly detecting the introduction and emergence of pathogen variants. To evaluate how interactions between surveillance capacity, variant properties, and the epidemiological context influence the timeliness of pathogen variant detection, we developed a geographically explicit stochastic compartmental model to simulate the transmission of a novel SARS-CoV-2 variant in New York City. We measured the impact of (1) testing and sequencing volume, (2) geographic targeting of testing, (3) the timing and location of variant emergence, and (4) the relative variant transmissibility on detection speed and on the undetected disease burden. Improvements in detection times and reduction of undetected infections were driven primarily by increases in the number of sequenced samples. The relative transmissibility of the new variant and the epidemic context of variant emergence also influenced detection times, showing that individual surveillance strategies can result in a wide range of detection outcomes, depending on the underlying dynamics of the circulating variants. These findings help contextualize the design, interpretation, and trade-offs of genomic surveillance strategies of pandemic respiratory pathogens.

The first three SARS-CoV-2 phylogenetic lineages classified as variants of concern (VOCs) in the United States (U.S.) from December 15, 2020 to February 28, 2021, Alpha (B.1.1.7), Beta (B.1.351), and Gamma (P.1) lineages, were initially detected internationally. This investigation examined available travel history of coronavirus disease 2019 (COVID-19) cases reported in the U.S. in whom laboratory testing showed one of these initial VOCs. Travel history, demographics, and health outcomes for a convenience sample of persons infected with a SARS-CoV-2 VOC from December 15, 2020 through February 28, 2021 were provided by 35 state and city health departments, and proportion reporting travel was calculated. Of 1,761 confirmed VOC cases analyzed, 1,368 had available data on travel history. Of those with data on travel history, 1,168 (85%) reported no travel preceding laboratory confirmation of SARS-CoV-2 and only 105 (8%) reported international travel during the 30 days preceding a positive SARS-CoV-2 test or symptom onset. International travel was reported by 92/1,304 (7%) of persons infected with the Alpha variant, 7/55 (22%) with Beta, and 5/9 (56%) with Gamma. Of the first three SARS-CoV-2 lineages designated as VOCs in the U.S., international travel was common only among the few Gamma cases. Most persons infected with Alpha and Beta variant reported no travel history, therefore, community transmission of these VOCs was likely common in the U.S. by March 2021. These findings underscore the importance of global surveillance using whole genome sequencing to detect and inform mitigation strategies for emerging SARS-CoV-2 VOCs.

Abstract Background Rapid identification of new SARS-CoV-2 variants is a critical component of the public health response to the COVID-19 pandemic. However, we lack a quantitative framework to assess the expected performance of sampling strategies in varying epidemic contexts. Methods To address this gap, we used a multi-patch stochastic model of SARS-CoV-2 spread in New York City to evaluate the impact of the volume of testing and sequencing, geographic representativeness of sampling, location and timing of variant emergence, and relative variant transmissibility on the time to first detection of a new variant. Results The strategy of targeted sampling of likely emergence locations offered the most improvement in detection speed. Increasing sequencing capacity reduced detection time more than increasing testing volumes. The relative transmissibility of the new variant and the epidemic context of variant emergence also influenced detection times, showing that individual surveillance strategies can result in a wide range of detection outcomes, depending on the underlying dynamics of the circulating variants. Detection time by test volume and fixed sequencing capacity. Lines depict the mean duration between variant introduction and detection in days as a function of daily testing volume, colored by the maximum sequencing volume (A), and as a function of daily maximum sequencing volume, colored by the test volume (B) (at variant introduction 50 days after the prior variant and baseline sampling strategy). Detection time by proportion of tests allocated in a single location. Lines depict the average detection time for scenarios where between 20% and 100% of tests are sampled from a single location, and the remaining tests are evenly distributed across the remaining locations by population size. The lines distinguish between scenarios where the variant emerged in the primary allocation location, i.e., test over-sampling and emergence occurred in the same location (blue), and scenarios where the variant emerged in one of the other locations, i.e., test over-sampling and emergence occurred in different locations (red). Ribbons depict the 95% confidence interval for the detection time. Conclusion These findings help contextualize the design, interpretation, and trade-offs of genomic surveillance strategies. Disclosures Stephen M. Kissler, PhD, ModernaTx: Advisor/Consultant Yonatan H. Grad, MD, PhD, Day Zero Diagnostics: Board Member|GSK: Advisor/Consultant

Bivalent booster vaccination data were

Recombination is an evolutionary process by which many pathogens generate diversity and acquire novel functions. Although a common occurrence during coronavirus replication, detection of recombination is only feasible when genetically distinct viruses contemporaneously infect the same host. Here, we identify an instance of SARS-CoV-2 superinfection, whereby an individual was infected with two distinct viral variants: Alpha (B.1.1.7) and Epsilon (B.1.429). This superinfection was first noted when an Alpha genome sequence failed to exhibit the classic S gene target failure behavior used to track this variant. Full genome sequencing from four independent extracts reveals that Alpha variant alleles comprise around 75% of the genomes, whereas the Epsilon variant alleles comprise around 20% of the sample. Further investigation reveals the presence of numerous recombinant haplotypes spanning the genome, specifically in the spike, nucleocapsid, and ORF 8 coding regions. These findings support the potential for recombination to reshape SARS-CoV-2 genetic diversity.

To characterize the epidemiological properties of the B.1.526 SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) variant of interest, here we used nine epidemiological and population datasets and model-inference methods to reconstruct SARS-CoV-2 transmission dynamics in New York City, where B.1.526 emerged. We estimated that B.1.526 had a moderate increase (15 to 25%) in transmissibility, could escape immunity in 0 to 10% of previously infected individuals, and substantially increased the infection fatality risk (IFR) among adults 65 or older by >60% during November 2020 to April 2021, compared to estimates for preexisting variants. Overall, findings suggest that new variants like B.1.526 likely spread in the population weeks before detection and that partial immune escape (e.g., resistance to therapeutic antibodies) could offset prior medical advances and increase IFR. Early preparedness for and close monitoring of SARS-CoV-2 variants, their epidemiological characteristics, and disease severity are thus crucial to COVID-19 (coronavirus disease 2019) response.

ABSTRACTBackgroundMonitoring the emergence and spread of SARS-CoV-2 variants is an important public health objective. Travel restrictions, aimed to prevent viral spread, have major economic consequences and unclear effectiveness despite considerable research. We investigated the introduction and establishment of the Gamma variant in New York City (NYC) in 2021.MethodsWe performed phylogeographic analysis on 15,967 Gamma sequences available on GISAID and sampled between March 10th through May 1st, 2021, to identify geographic sources of Gamma lineages introduced into NYC. We identified locally circulating Gamma transmission clusters and inferred the timing of their establishment in NYC.FindingsWe identified 16 phylogenetically-distinct Gamma clusters established in NYC (cluster sizes ranged 2-108 genomes). Most of the NYC clusters were introduced from Florida and Illinois; only one was introduced from outside the United States (US). By the time the first Gamma case was reported by genomic surveillance in NYC on March 10th, the majority (57%) of circulating Gamma lineages had already been established in the city for at least two weeks.InterpretationDespite the expansion of SARS-CoV-2 genomic surveillance in NYC, there was a substantial gap between Gamma variant introduction and establishment in January/February 2021, and its identification by genomic surveillance in March 2021. Although travel from Brazil to the US was restricted from May 2020 through the end of the study period, this restriction did not prevent Gamma from becoming established in NYC as most introductions occurred from domestic locations.

Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B." Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October to 8 December), and the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans before November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events.

BACKGROUND:Monitoring the emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is an important public health objective. We investigated how the Gamma variant was established in New York City (NYC) in early 2021 in the presence of travel restrictions that aimed to prevent viral spread from Brazil, the country where the variant was first identified. METHODS:We performed phylogeographic analysis on 15 967 Gamma sequences sampled between 10 March and 1 May 2021, to identify geographic sources of Gamma lineages introduced into NYC. We identified locally circulating Gamma transmission clusters and inferred the timing of their establishment in NYC. RESULTS:We identified 16 phylogenetically distinct Gamma clusters established in NYC (cluster sizes ranged 2-108 genomes); most of them were introduced from Florida and Illinois and only 1 directly from Brazil. By the time the first Gamma case was reported by genomic surveillance in NYC on 10 March, the majority (57%) of circulating Gamma lineages had already been established in the city for at least 2 weeks. CONCLUSIONS:Although travel from Brazil to the United States was restricted from May 2020 through the end of the study period, this restriction did not prevent Gamma from becoming established in NYC as most introductions occurred from domestic locations.

This study investigated prevalence of Legionella in the New York City (NYC) water distribution system using International Organization for Standardization 11731:2017 and Legiolert (IDEXX, USA) culture‐based methods and polymerase chain reaction. All water samples met applicable Environmental Protection Agency and New York State water quality guidelines. Eighty‐five percent (448/528) of water samples were positive for Legionella DNA. Despite this, Legionella bacteria were detected in only 2.8% (15/544) of water samples using culture methods. All Legionella pneumophila culture‐positive samples were recovered from a single distribution site, which was undergoing a street reconstruction project. The site had conditions indicative of stagnation, and an adjacent building's service line was periodically backflowing. These factors indicate that L. pneumophila may have been introduced from an external source. The lack of culturable Legionella in samples with detectable Legionella DNA suggests that NYC practices are sufficient to protect against culturable Legionella in NYC's water distribution system.

Wide-scale SARS-CoV-2 genome sequencing is critical to tracking viral evolution during the ongoing pandemic. We develop the software tool, Variant Database (VDB), for quickly examining the changing landscape of spike mutations. Using VDB, we detect an emerging lineage of SARS-CoV-2 in the New York region that shares mutations with previously reported variants. The most common sets of spike mutations in this lineage (now designated as B.1.526) are L5F, T95I, D253G, E484K or S477N, D614G, and A701V. This lineage was first sequenced in late November 2020. Phylodynamic inference confirmed the rapid growth of the B.1.526 lineage. In concert with other variants, like B.1.1.7, the rise of B.1.526 appears to have extended the duration of the second wave of COVID-19 cases in NYC in early 2021. Pseudovirus neutralization experiments demonstrated that B.1.526 spike mutations adversely affect the neutralization titer of convalescent and vaccinee plasma, supporting the public health relevance of this lineage.

Recent studies have documented the emergence and rapid growth of B.1.526, a novel variant of interest (VOI) of SARS-CoV-2, the virus that causes COVID-19, in the New York City (NYC) area after its identification in NYC in November 2020 (1-3). Two predominant subclades within the B.1.526 lineage have been identified, one containing the E484K mutation in the receptor-binding domain (1,2), which attenuates in vitro neutralization by multiple SARS-CoV-2 antibodies and is present in variants of concern (VOCs) first identified in South Africa (B.1.351) (4) and Brazil (P.1).* The NYC Department of Health and Mental Hygiene (DOHMH) analyzed laboratory and epidemiologic data to characterize cases of B.1.526 infection, including illness severity, transmission to close contacts, rates of possible reinfection, and laboratory-diagnosed breakthrough infections among vaccinated persons. Preliminary data suggest that the B.1.526 variant does not lead to more severe disease and is not associated with increased risk for infection after vaccination (breakthrough infection) or reinfection. Because relatively few specimens were sequenced over the study period, the statistical power might have been insufficient to detect modest differences in rates of uncommon outcomes such as breakthrough infection or reinfection. Collection of timely viral genomic data for a larger proportion of citywide cases and rapid integration with population-based surveillance data would enable improved understanding of the impact of emerging SARS-CoV-2 variants and specific mutations to help guide public health intervention efforts.