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BACKGROUND: Homeless shelters are a high-risk setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission because of crowding and shared hygiene facilities. OBJECTIVE: To investigate SARS-CoV-2 case counts across several adult and family homeless shelters in a major metropolitan area. DESIGN: Cross-sectional, community-based surveillance study. (ClinicalTrials.gov: NCT04141917). SETTING: 14 homeless shelters in King County, Washington. PARTICIPANTS: A total of 1434 study encounters were done in shelter residents and staff, regardless of symptoms. INTERVENTION: 2 strategies were used for SARS-CoV-2 testing: routine surveillance and contact tracing ("surge testing") events. MEASUREMENTS: The primary outcome measure was test positivity rate of SARS-CoV-2 infection at shelters, determined by dividing the number of positive cases by the total number of participant encounters, regardless of symptoms. Sociodemographic, clinical, and virologic variables were assessed as correlates of viral positivity. RESULTS: Among 1434 encounters, 29 (2% [95% CI, 1.4% to 2.9%]) cases of SARS-CoV-2 infection were detected across 5 shelters. Most (n = 21 [72.4%]) were detected during surge testing events rather than routine surveillance, and most (n = 21 [72.4% {CI, 52.8% to 87.3%}]) were asymptomatic at the time of sample collection. Persons who were positive for SARS-CoV-2 were more frequently aged 60 years or older than those without SARS-CoV-2 (44.8% vs. 15.9%). Eighty-six percent of persons with positive test results slept in a communal space rather than in a private or shared room. LIMITATION: Selection bias due to voluntary participation and a relatively small case count. CONCLUSION: Active surveillance and surge testing were used to detect multiple cases of asymptomatic and symptomatic SARS-CoV-2 infection in homeless shelters. The findings suggest an unmet need for routine viral testing outside of clinical settings for homeless populations. PRIMARY FUNDING SOURCE: Gates Ventures.
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COVID-19/epidemiologia , COVID-19/transmissão , Pessoas Mal Alojadas , Adolescente , Adulto , Criança , Busca de Comunicante , Estudos Transversais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Vigilância da População , SARS-CoV-2 , Washington/epidemiologiaRESUMO
While influenza and other respiratory pathogens cause significant morbidity and mortality, the community-based burden of these infections remains incompletely understood. The development of novel methods to detect respiratory infections is essential for mitigating epidemics and developing pandemic-preparedness infrastructure. From October 2019 to March 2020, we conducted a home-based cross-sectional study in the greater Seattle, WA, area, utilizing electronic consent and data collection instruments. Participants received nasal swab collection kits via rapid delivery within 24 hours of self-reporting respiratory symptoms. Samples were returned to the laboratory and were screened for 26 respiratory pathogens and a housekeeping gene. Participant data were recorded via online survey at the time of sample collection and 1 week later. Of the 4,572 consented participants, 4,359 (95.3%) received a home swab kit and 3,648 (83.7%) returned a nasal specimen for respiratory pathogen screening. The 3,638 testable samples had a mean RNase P relative cycle threshold (Crt ) value of 19.0 (SD, 3.4), and 1,232 (33.9%) samples had positive results for one or more pathogens, including 645 (17.7%) influenza-positive specimens. Among the testable samples, the median time between shipment of the home swab kit and completion of laboratory testing was 8.0 days (interquartile range [IQR], 7.0 to 14.0). A single adverse event occurred and did not cause long-term effects or require medical attention. Home-based surveillance using online participant enrollment and specimen self-collection is a safe and feasible method for community-level monitoring of influenza and other respiratory pathogens, which can readily be adapted for use during pandemics.
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Influenza Humana , Infecções Respiratórias , Estudos Transversais , Humanos , Influenza Humana/diagnóstico , Influenza Humana/epidemiologia , Pandemias , Infecções Respiratórias/diagnóstico , Infecções Respiratórias/epidemiologia , Manejo de EspécimesRESUMO
BACKGROUND: Unusually high snowfall in western Washington State in February 2019 led to widespread school and workplace closures. We assessed the impact of social distancing caused by this extreme weather event on the transmission of respiratory viruses. METHODS: Residual specimens from patients evaluated for acute respiratory illness at hospitals in the Seattle metropolitan area were screened for a panel of respiratory viruses. Transmission models were fit to each virus to estimate the magnitude reduction in transmission due to weather-related disruptions. Changes in contact rates and care-seeking were informed by data on local traffic volumes and hospital visits. RESULTS: Disruption in contact patterns reduced effective contact rates during the intervention period by 16 to 95%, and cumulative disease incidence through the remainder of the season by 3 to 9%. Incidence reductions were greatest for viruses that were peaking when the disruption occurred and least for viruses in an early epidemic phase. CONCLUSION: High-intensity, short-duration social distancing measures may substantially reduce total incidence in a respiratory virus epidemic if implemented near the epidemic peak. For SARS-CoV-2, this suggests that, even when SARS-CoV-2 spread is out of control, implementing short-term disruptions can prevent COVID-19 deaths.
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Epidemias/prevenção & controle , Distanciamento Físico , Infecções Respiratórias/transmissão , Infecções Respiratórias/virologia , Tempo (Meteorologia) , COVID-19 , Cidades , Humanos , Incidência , Modelos Teóricos , Estudos Retrospectivos , WashingtonRESUMO
SUMMARY: We introduce ISDB, a set of software tools for the creation and administration of relational databases of viral integration site (IS) data. Using ISDB, investigators can curate a private database from any heterogeneous set of data sources, including previously-published datasets and internal, work-in-progress data. To make data visible and accessible to collaborators with varying degrees of computational expertise, ISDB automatically generates web sites describing database contents and data exports in several common formats. Compared to a public depository database, the ability to build local, private databases makes ISDB suitable for use in testing hypotheses and developing analyses in the long pre-publication phase of most research. AVAILABILITY AND IMPLEMENTATION: Installation and usage documentation for ISDB are provided on our website https://mullinslab.microbiol.washington.edu/isdb/. Source code is available under the open source MIT license from https://github.com/MullinsLab/ISDB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Genoma , Software , Bases de Dados Factuais , Integração ViralRESUMO
Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.
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COVID-19 , SARS-CoV-2 , Humanos , COVID-19/transmissão , COVID-19/epidemiologia , SARS-CoV-2/isolamento & purificação , Washington/epidemiologia , Pandemias , Cidades/epidemiologia , Estações do Ano , Viagem/estatística & dados numéricosRESUMO
Seasonal influenza vaccines must be updated regularly to account for mutations that allow influenza viruses to escape our existing immunity. A successful vaccine should represent the genetic diversity of recently circulating viruses and induce antibodies that effectively prevent infection by those recent viruses. Thus, linking the genetic composition of circulating viruses and the serological experimental results measuring antibody efficacy is crucial to the vaccine design decision. Historically, genetic and serological data have been presented separately in the form of static visualizations of phylogenetic trees and tabular serological results to identify vaccine candidates. To simplify this decision-making process, we have created an interactive tool for visualizing serological data that has been integrated into Nextstrain's real-time phylogenetic visualization framework, Auspice. We show how the combined interactive visualizations may be used by decision makers to explore the relationships between complex data sets for both prospective vaccine virus selection and retrospectively exploring the performance of vaccine viruses.
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Background: Respiratory viruses might influence Streptococcus pneumoniae nasal carriage and subsequent disease risk. We estimated the association between common respiratory viruses and semiquantitative S. pneumoniae nasal carriage density in a household setting before and during the COVID-19 pandemic. Methods: From November 2019-June 2021, we enrolled participants in a remote household surveillance study of respiratory pathogens. Participants submitted weekly reports of acute respiratory illness (ARI) symptoms. Mid-turbinate or anterior nasal swabs were self-collected at enrollment, when ARI occurred, and, in the second year of the study only, from household contacts after SARS-CoV-2 was detected in a household member. Specimens were tested using multiplex reverse-transcription PCR for respiratory pathogens, including S. pneumoniae, rhinovirus, adenovirus, common human coronavirus, influenza A/B virus, respiratory syncytial virus (RSV) A/B, human metapneumovirus, enterovirus, and human parainfluenza virus. We estimated differences in semiquantitative S. pneumoniae nasal carriage density, estimated by the inverse of S. pneumoniae relative cycle threshold (Crt) values, with and without viral detection for any virus and for specific respiratory viruses using linear generalized estimating equations of S. pneumoniae Crt values on virus detection adjusted for age and swab type and accounting for clustering of swabs within households. Results: We collected 346 swabs from 239 individuals in 151 households that tested positive for S. pneumoniae (n = 157 with and 189 without ≥1 viruses co-detected). Difficulty breathing, cough, and runny nose were more commonly reported among individuals with specimens with viral co-detection compared to without (15%, 80% and 93% vs. 8%, 57%, and 51%, respectively) and ear pain and headache were less commonly reported (3% and 26% vs. 16% and 41%, respectively). For specific viruses among all ages, semiquantitative S. pneumoniae nasal carriage density was greater with viral co-detection for enterovirus, RSV A/B, adenovirus, rhinovirus, and common human coronavirus (P < 0.01 for each). When stratified by age, semiquantitative S. pneumoniae nasal carriage density was significantly greater with viral co-detection among children aged <5 (P = 0.002) and 5-17 years (P = 0.005), but not among adults aged 18-64 years (P = 0.29). Conclusion: Detection of common respiratory viruses was associated with greater concurrent S. pneumoniae semiquantitative nasal carriage density in a household setting among children, but not adults.
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Importance: Few US studies have reexamined risk factors for SARS-CoV-2 positivity in the context of widespread vaccination and new variants or considered risk factors for cocirculating endemic viruses, such as rhinovirus. Objectives: To evaluate how risk factors and symptoms associated with SARS-CoV-2 test positivity changed over the course of the pandemic and to compare these with the risk factors associated with rhinovirus test positivity. Design, Setting, and Participants: This case-control study used a test-negative design with multivariable logistic regression to assess associations between SARS-CoV-2 and rhinovirus test positivity and self-reported demographic and symptom variables over a 25-month period. The study was conducted among symptomatic individuals of all ages enrolled in a cross-sectional community surveillance study in King County, Washington, from June 2020 to July 2022. Exposures: Self-reported data for 15 demographic and health behavior variables and 16 symptoms. Main Outcomes and Measures: Reverse transcription-polymerase chain reaction-confirmed SARS-CoV-2 or rhinovirus infection. Results: Analyses included data from 23â¯498 individuals. The median (IQR) age of participants was 34.33 (22.42-45.08) years, 13â¯878 (59.06%) were female, 4018 (17.10%) identified as Asian, 654 (2.78%) identified as Black, and 2193 (9.33%) identified as Hispanic. Close contact with an individual with SARS-CoV-2 (adjusted odds ratio [aOR], 3.89; 95% CI, 3.34-4.57) and loss of smell or taste (aOR, 3.49; 95% CI, 2.77-4.41) were the variables most associated with SARS-CoV-2 test positivity, but both attenuated during the Omicron period. Contact with a vaccinated individual with SARS-CoV-2 (aOR, 2.03; 95% CI, 1.56-2.79) was associated with lower odds of testing positive than contact with an unvaccinated individual with SARS-CoV-2 (aOR, 4.04; 95% CI, 2.39-7.23). Sore throat was associated with Omicron infection (aOR, 2.27; 95% CI, 1.68-3.20) but not Delta infection. Vaccine effectiveness for participants fully vaccinated with a booster dose was 93% (95% CI, 73%-100%) for Delta, but not significant for Omicron. Variables associated with rhinovirus test positivity included being younger than 12 years (aOR, 3.92; 95% CI, 3.42-4.51) and experiencing a runny or stuffy nose (aOR, 4.58; 95% CI, 4.07-5.21). Black race, residing in south King County, and households with 5 or more people were significantly associated with both SARS-CoV-2 and rhinovirus test positivity. Conclusions and Relevance: In this case-control study of 23â¯498 symptomatic individuals, estimated risk factors and symptoms associated with SARS-CoV-2 infection changed over time. There was a shift in reported symptoms between the Delta and Omicron variants as well as reductions in the protection provided by vaccines. Racial and sociodemographic disparities persisted in the third year of SARS-CoV-2 circulation and were also present in rhinovirus infection. Trends in testing behavior and availability may influence these results.
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COVID-19 , SARS-CoV-2 , Feminino , Humanos , Adulto , Pessoa de Meia-Idade , Masculino , Rhinovirus , Estudos de Casos e Controles , COVID-19/diagnóstico , COVID-19/epidemiologia , Estudos Transversais , Fatores de RiscoRESUMO
Background: Co-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates. Methods: We conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel. Results: 21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33·5%), Streptococcus pneumoniae (SPn, 29·0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9·6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load. Conclusions: Viral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.
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The analysis of human pathogens requires a diverse collection of bioinformatics tools. These tools include standard genomic and phylogenetic software and custom software developed to handle the relatively numerous and short genomes of viruses and bacteria. Researchers increasingly depend on the outputs of these tools to infer transmission dynamics of human diseases and make actionable recommendations to public health officials (Black et al., 2020; Gardy et al., 2015). In order to enable real-time analyses of pathogen evolution, bioinformatics tools must scale rapidly with the number of samples and be flexible enough to adapt to a variety of questions and organisms. To meet these needs, we developed Augur, a bioinformatics toolkit designed for phylogenetic analyses of human pathogens.
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The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has gravely affected societies around the world. Outbreaks in different parts of the globe have been shaped by repeated introductions of new viral lineages and subsequent local transmission of those lineages. Here, we sequenced 3940 SARS-CoV-2 viral genomes from Washington State (USA) to characterize how the spread of SARS-CoV-2 in Washington State in early 2020 was shaped by differences in timing of mitigation strategies across counties and by repeated introductions of viral lineages into the state. In addition, we show that the increase in frequency of a potentially more transmissible viral variant (614G) over time can potentially be explained by regional mobility differences and multiple introductions of 614G but not the other variant (614D) into the state. At an individual level, we observed evidence of higher viral loads in patients infected with the 614G variant. However, using clinical records data, we did not find any evidence that the 614G variant affects clinical severity or patient outcomes. Overall, this suggests that with regard to D614G, the behavior of individuals has been more important in shaping the course of the pandemic in Washington State than this variant of the virus.
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COVID-19 , Genoma Viral , SARS-CoV-2 , COVID-19/virologia , Surtos de Doenças , Humanos , Filogenia , SARS-CoV-2/genética , Washington/epidemiologiaRESUMO
BACKGROUND: We aimed to evaluate a testing program to facilitate control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission at a large university and measure spread in the university community using viral genome sequencing. METHODS: Our prospective longitudinal study used remote contactless enrollment, daily mobile symptom and exposure tracking, and self-swab sample collection. Individuals were tested if the participant was exposed to a known SARS-CoV-2-infected person, developed new symptoms, or reported high-risk behavior (such as attending an indoor gathering without masking or social distancing), if a member of a group experiencing an outbreak, or at enrollment. Study participants included students, staff, and faculty at an urban public university during the Autumn quarter of 2020. RESULTS: We enrolled 16 476 individuals, performed 29 783 SARS-CoV-2 tests, and detected 236 infections. Seventy-five percent of positive cases reported at least 1 of the following: symptoms (60.8%), exposure (34.7%), or high-risk behaviors (21.5%). Greek community affiliation was the strongest risk factor for testing positive, and molecular epidemiology results suggest that specific large gatherings were responsible for several outbreaks. CONCLUSIONS: A testing program focused on individuals with symptoms and unvaccinated persons who participate in large campus gatherings may be effective as part of a comprehensive university-wide mitigation strategy to control the spread of SARS-CoV-2.
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Increasingly, public-health agencies are using pathogen genomic sequence data to support surveillance and epidemiological investigations. As access to whole-genome sequencing has grown, greater amounts of molecular data have helped improve the ability to detect and track outbreaks of diseases such as COVID-19, investigate transmission chains and explore large-scale population dynamics, such as the spread of antibiotic resistance. However, the wide adoption of whole-genome sequencing also poses new challenges for public-health agencies that must adapt to support a new set of expertise, which means that the capacity to perform genomic data assembly and analysis has not expanded as widely as the adoption of sequencing itself. In this Perspective, we make recommendations for developing an accessible, unified informatic ecosystem to support pathogen genomic analysis in public-health agencies across income settings. We hope that the creation of this ecosystem will allow agencies to effectively and efficiently share data, workflows and analyses and thereby increase the reproducibility, accessibility and auditability of pathogen genomic analysis while also supporting agency autonomy.
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Infecções por Coronavirus/genética , Genômica , Pneumonia Viral/genética , Dinâmica Populacional , Betacoronavirus/genética , Betacoronavirus/patogenicidade , COVID-19 , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Infecções por Coronavirus/virologia , Surtos de Doenças , Resistência Microbiana a Medicamentos/genética , Humanos , Pandemias , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Pneumonia Viral/virologia , SARS-CoV-2 , Sequenciamento Completo do GenomaRESUMO
INTRODUCTION: Influenza epidemics and pandemics cause significant morbidity and mortality. An effective response to a potential pandemic requires the infrastructure to rapidly detect, characterise, and potentially contain new and emerging influenza strains at both an individual and population level. The objective of this study is to use data gathered simultaneously from community and hospital sites to develop a model of how influenza enters and spreads in a population. METHODS AND ANALYSIS: Starting in the 2018-2019 season, we have been enrolling individuals with acute respiratory illness from community sites throughout the Seattle metropolitan area, including clinics, childcare facilities, Seattle-Tacoma International Airport, workplaces, college campuses and homeless shelters. At these sites, we collect clinical data and mid-nasal swabs from individuals with at least two acute respiratory symptoms. Additionally, we collect residual nasal swabs and data from individuals who seek care for respiratory symptoms at four regional hospitals. Samples are tested using a multiplex molecular assay, and influenza whole genome sequencing is performed for samples with influenza detected. Geospatial mapping and computational modelling platforms are in development to characterise the regional spread of influenza and other respiratory pathogens. ETHICS AND DISSEMINATION: The study was approved by the University of Washington's Institutional Review Board (STUDY00006181). Results will be disseminated through talks at conferences, peer-reviewed publications and on the study website (www.seattleflu.org).
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Influenza Humana , Genômica , Humanos , Influenza Humana/epidemiologia , Prevalência , Estudos Prospectivos , Estações do AnoRESUMO
After its emergence in Wuhan, China, in late November or early December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus rapidly spread globally. Genome sequencing of SARS-CoV-2 allows the reconstruction of its transmission history, although this is contingent on sampling. We analyzed 453 SARS-CoV-2 genomes collected between 20 February and 15 March 2020 from infected patients in Washington state in the United States. We find that most SARS-CoV-2 infections sampled during this time derive from a single introduction in late January or early February 2020, which subsequently spread locally before active community surveillance was implemented.
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Betacoronavirus/genética , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Genoma Viral , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Teorema de Bayes , COVID-19 , Humanos , Funções Verossimilhança , Pandemias , Filogenia , SARS-CoV-2 , Washington/epidemiologiaRESUMO
The rapid spread of SARS-CoV-2 has gravely impacted societies around the world. Outbreaks in different parts of the globe are shaped by repeated introductions of new lineages and subsequent local transmission of those lineages. Here, we sequenced 3940 SARS-CoV-2 viral genomes from Washington State to characterize how the spread of SARS-CoV-2 in Washington State (USA) was shaped by differences in timing of mitigation strategies across counties, as well as by repeated introductions of viral lineages into the state. Additionally, we show that the increase in frequency of a potentially more transmissible viral variant (614G) over time can potentially be explained by regional mobility differences and multiple introductions of 614G, but not the other variant (614D) into the state. At an individual level, we see evidence of higher viral loads in patients infected with the 614G variant. However, using clinical records data, we do not find any evidence that the 614G variant impacts clinical severity or patient outcomes. Overall, this suggests that at least to date, the behavior of individuals has been more important in shaping the course of the pandemic than changes in the virus.
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Following its emergence in Wuhan, China, in late November or early December 2019, the SARS-CoV-2 virus has rapidly spread throughout the world. On March 11, 2020, the World Health Organization declared Coronavirus Disease 2019 (COVID-19) a pandemic. Genome sequencing of SARS-CoV-2 strains allows for the reconstruction of transmission history connecting these infections. Here, we analyze 346 SARS-CoV-2 genomes from samples collected between 20 February and 15 March 2020 from infected patients in Washington State, USA. We found that the large majority of SARS-CoV-2 infections sampled during this time frame appeared to have derived from a single introduction event into the state in late January or early February 2020 and subsequent local spread, strongly suggesting cryptic spread of COVID-19 during the months of January and February 2020, before active community surveillance was implemented. We estimate a common ancestor of this outbreak clade as occurring between 18 January and 9 February 2020. From genomic data, we estimate an exponential doubling between 2.4 and 5.1 days. These results highlight the need for large-scale community surveillance for SARS-CoV-2 introductions and spread and the power of pathogen genomics to inform epidemiological understanding.
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OBJECTIVES: Among women initiating first-line nonnucleoside reverse-transcriptase inhibitor (NNRTI)-based-ART with and without a history of single-dose nevirapine (sdNVP) with or without zidovudine with or without lamivudine (ZDV with and without 3TC) for prevention of mother-to-child HIV transmission (PMTCT), we hypothesized that pre-ART HIV-drug resistance would be associated with virologic failure DESIGN/METHODS:: In a prospectively enrolled study, three genotypic drug-resistance assays [oligonucleotide-ligation-assay (OLA), consensus sequencing, and next-generation sequencing by Illumina] were retrospectively performed to detect pre-ART drug resistance. Minority or majority drug-resistant variants identified in pre-ART RNA and/or DNA, a history of antiretrovirals for PMTCT, and other risk factors were assessed for association with virologic failure. RESULTS: Failure occurred in 38/169 (22.5%) women, and was associated with pre-ART drug resistance detected by any assay (OLA of plasma or PBMC, consensus sequencing of PBMC and/or plasma, and next-generation sequencing of PBMC at frequencies of at least 10% and as minority variants; all Pâ<â0.0001). Failure was also associated with PMTCT using sdNVP and ZDV with or without 3TC, but not sdNVP only; however, the longer time-interval between PMTCT and ART initiation observed for sdNVP-only women showed no interaction with failure. Viral loads and OLA of PBMC in longitudinal specimens demonstrated rapid failure and emergence of drug resistance, particularly among sdNVP and ZDV with or without 3TC-experienced women with pre-ART drug-resistant minority variants by next-generation sequencing but without drug resistance by OLA or consensus sequencing. CONCLUSION: Pre-ART drug resistance was detected similarly by OLA of PBMC or plasma and by consensus sequencing, and was associated with virologic failure soon after initiation of first-line NVP-based ART. A history of sdNVP and ZDV with or without 3TC for PMTCT or minority variants detected by next-generation sequencing identified additional women with failure. These findings emphasize the value of assessing individual antiretroviral history, particularly nonsuppressive antiretrovirals with at least two drug classes, and testing for pre-ART drug resistance, including minority variants.