Following its emergence in Wuhan, China, in late November or early December 2019, the SARS-CoV-2 virus has rapidly spread globally. Genome sequencing of SARS-CoV-2 allows reconstruction of its transmission history, although this is contingent on sampling. We have analyzed 453 SARS-CoV-2 genomes collected between 20 February and 15 March 2020 from infected patients in Washington State, USA. 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.

Following its emergence in Wuhan,

Summary and statement of need 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.

We describe projections for the burden of infections and deaths in King and Snohomish Counties through April 7, as projections further out are strongly sensitive to assumptions about the scale of the local outbreak and importation dynamics from other regions that are not yet known. For the projections, we considered four scenarios for the increasingly effective impact of social distancing on COVID-19 incidence: • A baseline scenario assuming no change since January 15. • Scenarios with 25, 50, and 75 percent reductions in the rate of transmission assumed to take place starting March 10. The scenarios describe the generalized impacts of social distancing policies but do not currently speak to specific policy recommendations on issues like school closures, event cancellation, and work policies. We estimate that in the baseline scenario, on average across multiple simulations, there will have been roughly 25,000 people infected by April 7. Assuming mortality statistics will be like those seen in China, we expect that roughly 80 deaths will have occurred by April 7 and that roughly 400 total deaths will have been destined but not yet occurred. Effective social distancing slows the growth rate of the epidemic, and very effective interventions may stop the continued exponential growth. The table below illustrates the reductions in infections and deaths we expect with social distancing interventions. Social distancing intervention Estimated infections Destined deaths Business as usual 25,000 400 25% reduction 9,700 160 50% reduction 4,800 100 75% reduction 1,700 30 We do not yet know which scenario best represents current conditions in King and Snohomish counties, but previous experience in the region with weather-related social distancing and in other countries suggests to us that current efforts will likely land between baseline and 25% reduction scenarios. While we are not yet confident in our ability to estimate when the volume of new infections will overwhelm the health system, we discuss the issue below and believe it will be a critically important issue to address in the weeks to come. Thus, we believe more comprehensive non-pharmaceutical intervention policies in the region as soon as possible will be necessary to slow the onslaught of the disease, and we hope these are accompanied by policies to mitigate the broader societal impacts on the healthcare workforce and vulnerable populations.

Congregate living situations, such as homeless shelters, are high-risk settings for transmission of SARS-CoV-2 among residents and staff. This article describes findings from a study using active surveillance for SARS-CoV-2 that took place in 14 homeless shelters in King County, Washington, between 1 January and 24 April 2020.

The urgent need for massively scaled clinical or surveillance testing for SARS-CoV-2 has necessitated a reconsideration of the methods by which respiratory samples are collected, transported, processed and tested. Conventional testing for SARS-CoV-2 involves collection of a clinical specimen with a nasopharyngeal swab, storage of the swab during transport in universal transport medium (UTM), extraction of RNA, and quantitative reverse transcription PCR (RT-qPCR). As testing has scaled across the world, supply chain challenges have emerged across this entire workflow. Here we sought to evaluate how eliminating the UTM storage and RNA extraction steps would impact the results of molecular testing. Using paired mid-turbinate swabs self-collected by 11 individuals with previously established SARS-CoV-2 positivity, we performed a comparison of conventional (swab → UTM → RNA extraction → RT-qPCR) vs. simplified (direct elution from dry swab → RT-qPCR) protocols. Our results suggest that dry swabs eluted directly into a simple buffered solution (TE) can support molecular detection of SARS-CoV-2 via endpoint RT-qPCR without substantially compromising sensitivity. Although further confirmation with a larger sample size and variation of other parameters is necessary, these results are encouraging for the possibility of a simplified workflow that could support massively scaled testing for COVID-19 control. ResultsBased on prior literature ( 1 , 2 ) and the fact that dry swabs are employed for SARS-CoV-2 testing outside of the United States , we know that swabs collected and transported without transport media are amenable to subsequent nucleic acid detection-based diagnostics. We hypothesized that elution of dry swabs directly into a Tris-EDTA (TE) buffer would be compatible with RT-qPCR, i.e. skipping conventional RNA extraction altogether. TE's lower salt Seattle Flu Study Investigators Principal Investigators:

The rapid spread of SARS-CoV-2 has gravely impacted 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 to characterize how the spread of SARS-CoV-2 in Washington State (USA) in early 2020 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 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 impacts clinical severity or patient outcomes. Overall, this suggests that with regards 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.

BackgroundThe theory of fundamental causes explains why health disparities persist over time, even as risk factors, mechanisms, and diseases change. Using an intersectional framework, we evaluated multifactorial discrimination as a fundamental cause of mental health disparities.MethodsUsing baseline data from the Project STRIDE: Stress, Identity, and Mental Health study, we examined the health effects of discrimination among individuals who self-identified as lesbian, gay, or bisexual. We used logistic and linear regression to assess whether multifactorial discrimination met the four criteria designating a fundamental cause, namely that the cause: 1) influences multiple health outcomes, 2) affects multiple risk factors, 3) involves access to resources that can be leveraged to reduce consequences of disease, and 4) reproduces itself in varied contexts through changing mechanisms.ResultsMultifactorial discrimination predicted high depression scores, psychological well-being, and substance use disorder diagnosis. Discrimination was positively associated with risk factors for high depression scores: chronic strain and total number of stressful life events. Discrimination was associated with significantly lower levels of mastery and self-esteem, protective factors for depressive symptomatology. Even after controlling for risk factors, discrimination remained a significant predictor for high depression scores. Among subjects with low depression scores, multifactorial discrimination also predicted anxiety and aggregate mental health scores.ConclusionsMultifactorial discrimination should be considered a fundamental cause of mental health inequities and may be an important cause of broad health disparities among populations with intersecting social identities.