Model design for nonparametric phylodynamic inference and applications to pathogen surveillance.

Inference of effective population size from genomic data can provide unique information about demographic history and, when applied to pathogen genetic data, can also provide insights into epidemiological dynamics. The combination of nonparametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for nonparametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on nonparametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. Our methodology is implemented in a new R package entitled mlesky. We demonstrate the flexibility and speed of this approach in a series of simulation experiments and apply the methodology to a dataset of HIV-1 in the USA. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number.

The importance of equally accessible genomic surveillance in the age of pandemics.

Genomic epidemiology is now a core component in investigating the spread of a disease during an outbreak and for future preparedness to tackle emerging zoonoses. During the last decades, several viral diseases arose and emphasized the importance of molecular epidemiology in tracking the dispersal route, supporting proper mitigation measures, and appropriate vaccine development. In this perspective article, we summarized what has been done so far in the genomic epidemiology field and what should be considered in the future. We traced back the methods and protocols employed over time for zoonotic disease response. Either to small outbreaks such as the severe acute respiratory syndrome (SARS) outbreak identified first in 2002 in Guangdong, China, or to a global pandemic like the one that we are experiencing now since 2019 when the severe acute respiratory syndrome 2 (SARS-CoV-2) virus emerged in Wuhan, China, following several pneumonia cases, and subsequently spread worldwide. We explored both the benefits and shortages encountered when relying on genomic epidemiology, and we clearly present the disadvantages of inequity in accessing these tools around the world, especially in countries with less developed economies. For effectively addressing future pandemics, it is crucial to work for better sequencing equity around the globe.

Phylodynamics of SARS-CoV-2 in France, Europe, and the world in 2020.

Although France was one of the most affected European countries by the COVID-19 pandemic in 2020, the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) movement within France, but also involving France in Europe and in the world, remain only partially characterized in this timeframe. Here, we analyzed GISAID deposited sequences from January 1 to December 31, 2020 (n = 638,706 sequences at the time of writing). To tackle the challenging number of sequences without the bias of analyzing a single subsample of sequences, we produced 100 subsamples of sequences and related phylogenetic trees from the whole dataset for different geographic scales (worldwide, European countries, and French administrative regions) and time periods (from January 1 to July 25, 2020, and from July 26 to December 31, 2020). We applied a maximum likelihood discrete trait phylogeographic method to date exchange events (i.e., a transition from one location to another one), to estimate the geographic spread of SARS-CoV-2 transmissions and lineages into, from and within France, Europe, and the world. The results unraveled two different patterns of exchange events between the first and second half of 2020. Throughout the year, Europe was systematically associated with most of the intercontinental exchanges. SARS-CoV-2 was mainly introduced into France from North America and Europe (mostly by Italy, Spain, the United Kingdom, Belgium, and Germany) during the first European epidemic wave. During the second wave, exchange events were limited to neighboring countries without strong intercontinental movement, but Russia widely exported the virus into Europe during the summer of 2020. France mostly exported B.1 and B.1.160 lineages, respectively, during the first and second European epidemic waves. At the level of French administrative regions, the Paris area was the main exporter during the first wave. But, for the second epidemic wave, it equally contributed to virus spread with Lyon area, the second most populated urban area after Paris in France. The main circulating lineages were similarly distributed among the French regions. To conclude, by enabling the inclusion of tens of thousands of viral sequences, this original phylodynamic method enabled us to robustly describe SARS-CoV-2 geographic spread through France, Europe, and worldwide in 2020.

Invasive meningococcal disease in Norway in the two decades before the COVID-19 pandemic.

OBJECTIVES: Disease caused by the bacterium Neisseria meningitidis remains a worldwide public health challenge, despite the steadily decreasing incidence in Western countries. The objective of this study was to explore the epidemiology of invasive meningococcal disease in Norway over the last two decades. DESIGN: All isolates sent to the National Reference Laboratory from patients with invasive meningococcal disease between the years 2000 and 2019 were analyzed using whole genome sequencing (total: 625). RESULTS: A five-fold decrease in case numbers occurred over this period, and the situation has gone from being dominated by serogroup B to one where serogroups Y and W are more prevalent. Concurrently, the mean age at infection has increased from 18 to 33 years. Among the 350 serogroup B isolates, 87% were an exact match or cross-reactive with one or both the currently available serogroup B vaccines, but the proportion decreased in the past decade. Core genome analyses revealed a high variation in the number of allelic differences accumulated in epidemiologically linked isolates to the point that near-identical isolates were found several years apart. CONCLUSION: Allelic distance is an imprecise metric for the degree of epidemiologic linkage between isolates in N. meningitidis.

Transmission of SARS-CoV-2 Omicron Variant under a Dynamic Clearance Strategy in Shandong, China.

SARS-CoV-2 Omicron caused a large wave of COVID-19 cases in China in spring 2022. Shandong was one of the most affected regions during this epidemic yet was also among those areas that were able to quickly contain the transmission. We aimed to investigate the origin, genetic diversity, and transmission patterns of the Omicron epidemic in Shandong under a dynamic clearance strategy. We generated 1,149 Omicron sequences, performed phylogenetic analysis, and interpreted results in the context of available epidemiological information. We observed that there were multiple introductions of distinct Omicron sublineages into Shandong from foreign countries and other regions in China, while a small number of introductions led to majority of local cases. We found evidence suggesting that some local clusters were potentially associated with foreign imported cases. Superspreading events and cryptic transmissions contributed to the rapid spread of this epidemic. We identified a BA.1.1 genome with the R493Q reversion mutation in the spike receptor binding domain, potentially associated with an escape from vaccine and Omicron infection elicited neutralizing immunity. Our findings illustrated how the dynamic clearance strategy constrained this epidemic's size, duration, and geographical distribution. IMPORTANCE Starting in March 2022, the Omicron epidemic caused a large wave of COVID-19 cases in China. Shandong was one of the most affected regions during this epidemic but was also among those areas that were able to quickly contain the transmission. We investigated the origin, genetic diversity, and transmission patterns of Omicron epidemic in Shandong under a dynamic clearance strategy. We found that there were multiple introductions of distinct Omicron sublineages into Shandong from foreign countries and other regions in China, while a small number of introductions led to most local cases. We found evidence suggesting that some local clusters were associated with foreign imported cases. Superspreading events and cryptic transmissions contributed to the rapid spread of this epidemic. Our study illustrated the transmission patterns of Omicron epidemic in Shandong and provided a looking glass onto this epidemic in China.

Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a generalist virus, infecting and evolving in numerous mammals, including captive and companion animals, free-ranging wildlife, and humans. Transmission among non-human species poses a risk for the establishment of SARS-CoV-2 reservoirs, makes eradication difficult, and provides the virus with opportunities for new evolutionary trajectories, including the selection of adaptive mutations and the emergence of new variant lineages. Here, we use publicly available viral genome sequences and phylogenetic analysis to systematically investigate the transmission of SARS-CoV-2 between human and non-human species and to identify mutations associated with each species. We found the highest frequency of animal-to-human transmission from mink, compared with lower transmission from other sampled species (cat, dog, and deer). Although inferred transmission events could be limited by sampling biases, our results provide a useful baseline for further studies. Using genome-wide association studies, no single nucleotide variants (SNVs) were significantly associated with cats and dogs, potentially due to small sample sizes. However, we identified three SNVs statistically associated with mink and 26 with deer. Of these SNVs, ~⅔ were plausibly introduced into these animal species from local human populations, while the remaining ~⅓ were more likely derived in animal populations and are thus top candidates for experimental studies of species-specific adaptation. Together, our results highlight the importance of studying animal-associated SARS-CoV-2 mutations to assess their potential impact on human and animal health.

Primary assessment of the diversity of Omicron sublineages and the epidemiologic features of autumn/winter 2022 COVID-19 wave in Chinese mainland.

With the recent ongoing autumn/winter 2022 COVID-19 wave and the adjustment of public health control measures, there have been widespread SARS-CoV-2 infections in Chinese mainland. Here we have analyzed 369 viral genomes from recently diagnosed COVID-19 patients in Shanghai, identifying a large number of sublineages of the SARS-CoV-2 Omicron family. Phylogenetic analysis, coupled with contact history tracing, revealed simultaneous community transmission of two Omicron sublineages dominating the infections in some areas of China (BA.5.2 mainly in Guangzhou and Shanghai, and BF.7 mainly in Beijing) and two highly infectious sublineages recently imported from abroad (XBB and BQ.1). Publicly available data from August 31 to November 29, 2022 indicated an overall severe/critical case rate of 0.035% nationwide, while analysis of 5706 symptomatic patients treated at the Shanghai Public Health Center between September 1 and December 26, 2022 showed that 20 cases (0.35%) without comorbidities progressed into severe/critical conditions and 153 cases (2.68%) with COVID-19-exacerbated comorbidities progressed into severe/critical conditions. These observations shall alert healthcare providers to place more resources for the treatment of severe/critical cases. Furthermore, mathematical modeling predicts this autumn/winter wave might pass through major cities in China by the end of the year, whereas some middle and western provinces and rural areas would be hit by the upcoming infection wave in mid-to-late January 2023, and the duration and magnitude of upcoming outbreak could be dramatically enhanced by the extensive travels during the Spring Festival (January 21, 2023). Altogether, these preliminary data highlight the needs to allocate resources to early diagnosis and effective treatment of severe cases and the protection of vulnerable population, especially in the rural areas, to ensure the country's smooth exit from the ongoing pandemic and accelerate socio-economic recovery.

Unique Genomic Epidemiology of COVID-19 in the White Mountain Apache Tribe, April to August 2020, Arizona.

The first case of coronavirus disease 2019 (COVID-19) within the White Mountain Apache Tribe (WMAT) in Arizona was diagnosed almost 1 month after community transmission was recognized in the state. Aggressive contact tracing allowed for robust genomic epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and subsequent phylogenetic analyses implicated only two virus introductions, which resulted in the spread of two unique viral lineages on the reservation. The phylogenies of these lineages reflect the nature of the introductions, the remoteness of the community, and the extraordinarily high attack rates. The timing and space-limited nature of the outbreaks validate the public health tracing efforts involved, which were illustrated by multiple short transmission chains over a period of several weeks, eventually resulting in extinction of the lineages. Comprehensive sampling and successful infection control efforts are illustrated in both the effective population size analyses and the limited mortality outcomes. The rapid spread and high attack rates of the two lineages may be due to a combination of sociological determinants of the WMAT and a seemingly enhanced transmissibility. The SARS-CoV-2 genomic epidemiology of the WMAT demonstrates a unique local history of the pandemic and highlights the extraordinary and successful efforts of their public health response. IMPORTANCE This article discusses the introduction and spread of two unique viral lineages of SARS-CoV-2 within the White Mountain Apache Tribe in Arizona. Both genomic sequencing and traditional epidemiological strategies (e.g., contract tracing) were used to understand the nature of the spread of both lineages. Beyond providing a robust genomic analysis of the epidemiology of the outbreaks, this work also highlights the successful efforts of the local public health response.

Occurrence of SARS-CoV-2 reinfections at regular intervals in Ecuador.

SARS-CoV-2 reinfection is defined as a new infection with a different virus variant in an individual who has already recovered from a previous episode of COVID-19. The first case of reinfection in the world was described in August 2020, since then, reinfections have increased over time and their incidence has fluctuated with specific SARS-CoV-2 variant waves. Initially, reinfections were estimated to represent less than 1% of total COVID-19 infections. With the advent of the Omicron variant, reinfections became more frequent, representing up to 10% of cases (based on data from developed countries). The frequency of reinfections in Latin America has been scarcely reported. The current study shows that in Ecuador, the frequency of reinfections has increased 10-fold following the introduction of Omicron, after 22 months of surveillance in a single center of COVID-19 diagnostics. Suspected reinfections were identified retrospectively from a database of RT-qPCR-positive patients. Cases were confirmed by sequencing viral genomes from the first and second infections using the ONT MinION platform. Monthly surveillance showed that the main incidence peaks of reinfections were reached within four to five months, coinciding with the increase of COVID-19 cases in the country, suggesting that the emergence of reinfections is related to higher exposure to the virus during outbreaks. This study performed the longest monitoring of SARS-CoV-2 reinfections, showing an occurrence at regular intervals of 4-5 months and confirming a greater propensity of Omicron to cause reinfections.

Deciphering the Tangible Spatio-Temporal Spread of a 25-Year Tuberculosis Outbreak Boosted by Social Determinants.

Outbreak strains of Mycobacterium tuberculosis are promising candidates as targets in the search for intrinsic determinants of transmissibility, as they are responsible for many cases with sustained transmission; however, the use of low-resolution typing methods and restricted geographical investigations represent flaws in assessing the success of long-lived outbreak strains. We can now address the nature of outbreak strains by combining large genomic data sets and phylodynamic approaches. We retrospectively sequenced the whole genome of representative samples assigned to an outbreak circulating in the Canary Islands (the GC strain) since 1993, which accounts for ~20% of local tuberculosis cases. We selected a panel of specific single nucleotide polymorphism (SNP) markers for an in-silico search for additional outbreak-related sequences within publicly available tuberculosis genomic data. Using this information, we inferred the origin, spread, and epidemiological parameters of the GC strain. Our approach allowed us to accurately trace the historical and more recent dispersion of the GC strain. We provide evidence of a highly successful nature within the Canarian archipelago but limited expansion abroad. Estimation of epidemiological parameters from genomic data disagree with a distinctive biology of the GC strain. With the increasing availability of genomic data allowing for the accurate inference of strain spread and critical epidemiological parameters, we can now revisit the link between Mycobacterium tuberculosis genotypes and transmission, as is routinely carried out for SARS-CoV-2 variants of concern. We demonstrate that social determinants rather than intrinsically higher bacterial transmissibility better explain the success of the GC strain. Importantly, our approach can be used to trace and characterize strains of interest worldwide. IMPORTANCE Infectious disease outbreaks represent a significant problem for public health. Tracing outbreak expansion and understanding the main factors behind emergence and persistence remain critical to effective disease control. Our study allows researchers and public health authorities to use Whole-Genome Sequencing-based methods to trace outbreaks, and shows how available epidemiological information helps to evaluate the factors underpinning outbreak persistence. Taking advantage of all the freely available information placed in public repositories, researchers can accurately establish the expansion of an outbreak beyond original boundaries, and determine the potential risk of a strain to inform health authorities which, in turn, can define target strategies to mitigate expansion and persistence. Finally, we show the need to evaluate strain transmissibility in different geographic contexts to unequivocally associate spread to local or pathogenic factors, an important lesson taken from genomic surveillance of SARS-CoV-2.

Public health interventions successfully mitigated multiple incursions of SARS-CoV-2 Delta variant in the Australian Capital Territory.

The COVID-19 pandemic has presented a unique opportunity to understand how real-time pathogen genomics can be used for large-scale outbreak investigations. On 12 August 2021, the Australian Capital Territory (ACT) detected an incursion of the SARS-CoV-2 Delta (B.1.617.2) variant. Prior to this date, SARS-CoV-2 had been eliminated locally since 7 July 2020. Several public health interventions were rapidly implemented in response to the incursion, including a territory-wide lockdown and comprehensive contact tracing. The ACT has not previously used pathogen genomics at a population level in an outbreak response; therefore, this incursion also presented an opportunity to investigate the utility of genomic sequencing to support contact tracing efforts in the ACT. Sequencing of >75% of the 1793 laboratory-confirmed cases during the 3 months following the initial notification identified at least 13 independent incursions with onwards spread in the community. Stratification of cases by genomic cluster revealed that distinct cohorts were affected by the different incursions. Two incursions resulted in most of the community transmission during the study period, with persistent transmission in vulnerable sections of the community. Ultimately, both major incursions were successfully mitigated through public health interventions, including COVID-19 vaccines. The high rates of SARS-CoV-2 sequencing in the ACT and the relatively small population size facilitated detailed investigations of the patterns of virus transmission, revealing insights beyond those gathered from traditional contact tracing alone. Genomic sequencing was critical to disentangling complex transmission chains to target interventions appropriately.

Lessons learned: use of WGS in real-time investigation of suspected intrahospital SARS-CoV-2 outbreaks.

BACKGROUND: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been a continuing source of hospital-acquired infection and outbreaks. At Akershus University Hospital in Norway, traditional contact tracing has been combined with whole-genome sequencing (WGS) surveillance in real-time to investigate potential hospital outbreaks. AIM: To describe the advantages and challenges encountered when using WGS as a real-time tool in hospital outbreak investigation and surveillance during the SARS-CoV-2 pandemic. METHODS: Routine contact tracing in the hospital was performed for all healthcare workers (HCWs) who tested positive for SARS-CoV-2. Viral RNA from all positive patient and HCW samples was sequenced in real-time using nanopore sequencing and the ARTIC Network protocol. Suspected outbreaks involving five or more individuals with viral sequences were described. FINDINGS: Nine outbreaks were suspected based on contact tracing, and one outbreak was suspected based on WGS results. Five outbreaks were confirmed; of these, two outbreaks were supported but could not be confirmed by WGS with high confidence, one outbreak was found to consist of two different lineages, and two outbreaks were refuted. CONCLUSIONS: WGS is a valuable tool in hospital outbreak investigations when combined with traditional contact tracing. Inclusion of WGS data improved outbreak demarcation, identified unknown transmission chains, and highlighted weaknesses in existing infection control measures.

Combined epidemiology and genetic sequencing surveillance in the era of COVID-19 pandemic; Abu Dhabi experience, United Arab Emirates.

BACKGROUND: United Arab Emirates, has reported the first case of COVID-19 in January 2020 and by October 2022, a total of 1 Million cases and 2348 deaths due to COVID-19 have been reported. The Abu Dhabi Public Health Center, has led a novel initiative to conduct a large scale genomic surveillance project. The aim of this surveillance project is to generate data to guide public health pandemic response decision making. METHODS: Samples mainly from the community, points of entry to the emirate and healthcare facilities were collected for surveillance using both targeted PCR and/or Genome sequence analysis. Sample criteria were defined and specific metadata were collected in parallel. Using the unique identifiers and through the available datasets, epidemiological and clinical data were integrated. RESULTS: A total of 385,191 sample undertake analysis (from January 2021 to October 2022) either genotyping and/or sequence analysis. The most frequently encountered lineages in the community and among severe cases were reported. CONCLUSIONS: Genomic surveillance is a major tool essential for guiding public health measures throughout the pandemic.

Low Viral Diversity Limits the Effectiveness of Sequence-Based Transmission Inference for SARS-CoV-2.

Tracking the spread of infection amongst individuals within and between communities has been a major challenge during viral outbreaks. With the unprecedented scale of viral sequence data collection during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the possibility of using phylogenetics to reconstruct past transmission events has been explored as a more rigorous alternative to traditional contact tracing; however, the reliability of sequence-based inference of transmission networks has yet to be directly evaluated. E. E. Bendall, G. Paz-Bailey, G. A. Santiago, C. A. Porucznik, et al. (mSphere 7:e00400-22, 2022, https://doi.org/10.1128/mSphere.00400-22) evaluate the potential of this technique by applying best practices sequence comparison methods to three geographically distinct cohorts that include known transmission pairs and demonstrate that linked pairs are often indistinguishable from unrelated samples. This study clearly establishes how low viral diversity limits the utility of genomic methods of epidemiological inference for SARS-CoV-2.

Omicron-BA.1 Dispersion Rates in Mexico Varied According to the Regional Epidemic Patterns and the Diversity of Local Delta Subvariants.

PURPOSE: The Omicron subvariant BA.1 of SARS-CoV-2 was first detected in November 2021 and quickly spread worldwide, displacing the Delta variant. In this work, a characterization of the spread of this variant in Mexico is presented. METHODS: The time to fixation of BA.1, the diversity of Delta sublineages, the population density, and the level of virus circulation during the inter-wave interval were determined to analyze differences in BA.1 spread. RESULTS: BA.1 began spreading during the first week of December 2021 and became dominant in the next three weeks, causing the fourth COVID-19 epidemiological surge in Mexico. Unlike previous variants, BA.1 did not exhibit a geographically distinct circulation pattern. However, a regional difference in the speed of the replacement of the Delta variant was observed. CONCLUSIONS: Viral diversity and the relative abundance of the virus in a particular area around the time of the introduction of a new lineage seem to have influenced the spread dynamics, in addition to population density. Nonetheless, if there is a significant difference in the fitness of the variants, or if the time allowed for the competition is sufficiently long, it seems the fitter virus will eventually become dominant, as observed in the eventual dominance of the BA.1.x variant in Mexico.

A Repeat Pattern of Founder Events for SARS-CoV-2 Variants in Alaska.

Alaska is a unique US state because of its large size, geographically disparate population density, and physical distance from the contiguous United States. Here, we describe a pattern of SARS-CoV-2 variant emergence across Alaska reflective of these differences. Using genomic data, we found that in Alaska, the Omicron sublineage BA.2.3 overtook BA.1.1 by the week of 27 February 2022, reaching 48.5% of sequenced cases. On the contrary, in the contiguous United States, BA.1.1 dominated cases for longer, eventually being displaced by BA.2 sublineages other than BA.2.3. BA.2.3 only reached a prevalence of 10.9% in the contiguous United States. Using phylogenetics, we found evidence of potential origins of the two major clades of BA.2.3 in Alaska and with logistic regression estimated how it emerged and spread throughout the state. The combined evidence is suggestive of founder events in Alaska and is reflective of how Alaska's unique dynamics influence the emergence of SARS-CoV-2 variants.

Genomic Epidemiology of SARS-CoV-2 in Western Burkina Faso, West Africa.

BACKGROUND: After its initial detection in Wuhan, China, in December 2019, SARS-CoV-2 has spread rapidly, causing successive epidemic waves worldwide. This study aims to provide a genomic epidemiology of SARS-CoV-2 in Burkina Faso. METHODS: Three hundred and seventy-seven SARS-CoV-2 genomes obtained from PCR-positive nasopharyngeal samples (PCR cycle threshold score < 35) collected between 5 May 2020, and 31 January 2022 were analyzed. Genomic sequences were assigned to phylogenetic clades using NextClade and to Pango lineages using pangolin. Phylogenetic and phylogeographic analyses were performed to determine the geographical sources and time of virus introduction in Burkina Faso. RESULTS: The analyzed SARS-CoV-2 genomes can be assigned to 10 phylogenetic clades and 27 Pango lineages already described worldwide. Our analyses revealed the important role of cross-border human mobility in the successive SARS-CoV-2 introductions in Burkina Faso from neighboring countries. CONCLUSIONS: This study provides additional insights into the genomic epidemiology of SARS-CoV-2 in West Africa. It highlights the importance of land travel in the spread of the virus and the need to rapidly implement preventive policies. Regional cross-border collaborations and the adherence of the general population to government policies are key to prevent new epidemic waves.

SARS-CoV-2 Genomic Diversity in Households Highlights the Challenges of Sequence-Based Transmission Inference.

The reliability of sequence-based inference of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is not clear. Sequence data from infections among household members can define the expected genomic diversity of a virus along a defined transmission chain. SARS-CoV-2 cases were identified prospectively among 2,369 participants in 706 households. Specimens with a reverse transcription-PCR cycle threshold of ≤30 underwent whole-genome sequencing. Intrahost single-nucleotide variants (iSNV) were identified at a ≥5% frequency. Phylogenetic trees were used to evaluate the relationship of household and community sequences. There were 178 SARS-CoV-2 cases in 706 households. Among 147 specimens sequenced, 106 yielded a whole-genome consensus with coverage suitable for identifying iSNV. Twenty-six households had sequences from multiple cases within 14 days. Consensus sequences were indistinguishable among cases in 15 households, while 11 had ≥1 consensus sequence that differed by 1 to 2 mutations. Sequences from households and the community were often interspersed on phylogenetic trees. Identification of iSNV improved inference in 2 of 15 households with indistinguishable consensus sequences and in 6 of 11 with distinct ones. In multiple-infection households, whole-genome consensus sequences differed by 0 to 1 mutations. Identification of shared iSNV occasionally resolved linkage, but the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. IMPORTANCE We performed whole-genome sequencing of SARS-CoV-2 from prospectively identified cases in three longitudinal household cohorts. In a majority of multi-infection households, SARS-CoV-2 consensus sequences were indistinguishable, and they differed by 1 to 2 mutations in the rest. Importantly, even with modest genomic surveillance of the community (3 to 5% of cases sequenced), it was not uncommon to find community sequences interspersed with household sequences on phylogenetic trees. Identification of shared minority variants only occasionally resolved these ambiguities in transmission linkage. Overall, the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. Our work highlights the need to carefully consider both epidemiologic linkage and sequence data to define transmission chains in households, hospitals, and other transmission settings.

Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias.

BACKGROUND: Throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, healthcare workers (HCWs) have faced risk of infection from within the workplace via patients and staff as well as from the outside community, complicating our ability to resolve transmission chains in order to inform hospital infection control policy. Here we show how the incorporation of sequences from public genomic databases aided genomic surveillance early in the pandemic when circulating viral diversity was limited. METHODS: We sequenced a subset of discarded, diagnostic SARS-CoV-2 isolates between March and May 2020 from Boston Medical Center HCWs and combined this data set with publicly available sequences from the surrounding community deposited in GISAID with the goal of inferring specific transmission routes. RESULTS: Contextualizing our data with publicly available sequences reveals that 73% (95% confidence interval, 63%-84%) of coronavirus disease 2019 cases in HCWs are likely novel introductions rather than nosocomial spread. CONCLUSIONS: We argue that introductions of SARS-CoV-2 into the hospital environment are frequent and that expanding public genomic surveillance can better aid infection control when determining routes of transmission.

Clinical and genomic characterization of hypervirulent Klebsiella pneumoniae (hvKp) infections via passive surveillance in Southern California, 2020-2022.

Hypervirulent Klebsiella pneumoniae (hvKp) is more invasive and virulent than classical K. pneumoniae, and requires specialized treatment. To raise clinical awareness, this study determined the prevalence, clinical characteristics, and genomic epidemiology of hvKp infections in Southern California (SoCal) by conducting a passive surveillance in a single large academic medical center. We report here that hvKp infections were more common than expected, accounting for 2.6% of invasive K. pneumoniae infections, and presented with a wide disease spectrum, occasionally mimicking tumors, even co-infecting a COVID-19 patient. Most infections were community acquired with no recent international travel, suggesting hvKp strains are circulating in the community. Genomic analysis revealed genetic diversity, with the K1-ST23 lineage predominating but not clonal, and multiple sequence types of K2 including a SoCal unique K2-ST66 sublineage that had been unrecognized. Our findings highlight the urgency of heightened awareness of hvKp infection in the US, the need for rapid diagnosis of hvKp, and the necessity of implementing robust surveillance programs for hvKp at the institutional or local level.