BACKGROUND: Institutions of higher education (IHE) have been a focus of SARS-CoV-2 transmission studies but there is limited information on how viral diversity and transmission at IHE changed as the pandemic progressed. METHODS: Here we analyze 3606 viral genomes from unique COVID-19 episodes collected at a public university in Seattle, Washington from September 2020 to September 2022. RESULTS: Across the study period, we found evidence of frequent viral transmission among university affiliates with 60% (n = 2153) of viral genomes from campus specimens genetically identical to at least one other campus specimen. Moreover, viruses from students were observed in transmission clusters at a higher frequency than in the overall dataset while viruses from symptomatic infections were observed in transmission clusters at a lower frequency. Although only a small percentage of community viruses were identified as possible descendants of viruses isolated in university study specimens, phylodynamic modeling suggested a high rate of transmission events from campus into the local community, particularly during the 2021-2022 academic year. CONCLUSIONS: We conclude that viral transmission was common within the university population throughout the study period but that not all university affiliates were equally likely to be involved. In addition, the transmission rate from campus into the surrounding community may have increased during the second year of the study, possibly due to return to in-person instruction.

Congregate homeless shelters are disproportionately affected by infectious disease outbreaks. We describe enterovirus epidemiology across 23 adult and family shelters in King County, Washington, USA, during October 2019-May 2021, by using repeated cross-sectional respiratory illness and environmental surveillance and viral genome sequencing. Among 3,281 participants >3 months of age, we identified coxsackievirus A21 (CVA21) in 39 adult residents (3.0% [95% CI 1.9%-4.8%] detection) across 7 shelters during October 2019-February 2020. We identified enterovirus D68 (EV-D68) in 5 adult residents in 2 shelters during October-November 2019. Of 812 environmental samples, 1 was EV-D68-positive and 5 were CVA21-positive. Other enteroviruses detected among residents, but not in environmental samples, included coxsackievirus A6/A4 in 3 children. No enteroviruses were detected during April 2020-May 2021. Phylogenetically clustered CVA21 and EV-D68 cases occurred in some shelters. Some shelters also hosted multiple CVA21 lineages.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity. | Seasonal influenza (flu) viruses cause outbreaks every winter. People infected with influenza typically develop mild respiratory symptoms. But flu infections can cause serious illness in young children, older adults and people with chronic medical conditions. Infected or vaccinated individuals develop some immunity, but the viruses evolve quickly to evade these defenses in a process called antigenic drift. As the viruses change, they can re-infect previously immune people. Scientists update the flu vaccine yearly to keep up with this antigenic drift. The immune system fights flu infections by recognizing two proteins, known as antigens, on the virus’s surface, called hemagglutinin (HA) and neuraminidase (NA). However, mutations in the genes encoding these proteins can make them unrecognizable, letting the virus slip past the immune system. Scientists would like to know how these changes affect the size, severity and timing of annual influenza outbreaks. Perofsky et al. show that tracking genetic changes in HA and NA may help improve flu season predictions. The experiments compared the severity of 22 flu seasons caused by the A(H3N2) subtype in the United States with how much HA and NA had evolved since the previous year. The A(H3N2) subtype experiences the fastest rates of antigenic drift and causes more cases and deaths than other seasonal flu viruses. Genetic changes in HA and NA were a better predictor of A(H3N2) outbreak severity than the blood tests for protective antibodies that epidemiologists traditionally use to track flu evolution. However, the prevalence of another subtype of influenza A circulating in the population, called A(H1N1), was an even better predictor of how severe A(H3N2) outbreaks would be. Perofsky et al. are the first to show that genetic changes in NA contribute to the severity of flu seasons. Previous studies suggested a link between genetic changes in HA and flu season severity, and flu vaccines include the HA protein to help the body recognize new influenza strains. The results suggest that adding the NA protein to flu vaccines may improve their effectiveness. In the future, flu forecasters may want to analyze genetic changes in both NA and HA to make their outbreak predictions. Tracking how much of the A(H1N1) subtype is circulating may also be useful for predicting the severity of A(H3N2) outbreaks. | eng

INTRODUCTION: Although dolutegravir (DTG) is deemed stable, safe, cost-effective, and clinically beneficial, it also carries the risk of side effects, including observed weight gain among patients on DTG-based antiretroviral therapy (ART) regimens. We compared weight changes among adults (≥18 years) initiating tenofovir disoproxil fumarate, lamivudine, and dolutegravir (TLD) or tenofovir disoproxil fumarate, emtricitabine, and efavirenz (TEE) regimens and those switching from TEE to TLD (TEE-to-TLD switchers) in three large primary care facilities in South Africa METHODS: We conducted a retrospective longitudinal record review using patient medical records, extracting relevant demographic and clinical data from October 2018 to June 2021 from randomly selected adults who initiated TLD or TEE (initiators) and adult TEE-to-TLD switchers. We assessed weight, body mass index (BMI), and percentage weight changes for both groups and fitted linear regression and generalized linear models to determine factors associated with weight and BMI change and percentage weight change ≥10%, respectively, among treatment initiators. We fitted linear mixed-effect models among TEE-to-TLD switchers to consider repeated measures. RESULTS: Of 860 initiators, 450 (52.3%) initiated on TEE and 410 (47.7%) on TLD, with median follow-up of 1.4 years and 1.0 year, respectively. At initiation, 43.3% on TEE and 40.8% on TLD were overweight or obese. TLD initiators had an adjusted higher mean weight gain of 1.6 kg (p < 0.001) and mean BMI gain of 0.51 kg/m(2) (p < 0.001) than TEE initiators. Independent risk factors for higher mean weight and BMI included age ≥50 years, male, on ART for >12 months, initial BMI of <18.5 kg/m(2), and CD4 counts <200 cells/μL. Of 298 TEE-to-TLD switchers, 36.6% were overweight or obese at TEE initiation. Comparing before and after TLD switch, TEE-to-TLD switchers had an adjusted mean weight of 1.2 kg less while on TLD (p = 0.026). Being overweight and CD4 counts >350 cells/μL were independent risk factors for lower weight gain after TLD switch. CONCLUSIONS: We report more weight gain among TLD than among TEE initiators, although to a lesser extent than previously reported. TEE-to-TLD switchers experienced less weight gain after TLD switch; return to health before receiving TLD may be a contributory factor. The current findings are reassuring for those switching to a DTG-based regimen.

BACKGROUND: SARS-CoV-2 antigen-detection rapid diagnostic tests (Ag-RDTs) have become widely utilized but longitudinal characterization of their community-based performance remains incompletely understood. METHODS: This prospective longitudinal study at a large public university in Seattle, WA utilized remote enrollment, online surveys, and self-collected nasal swab specimens to evaluate Ag-RDT performance against real-time reverse transcription polymerase chain reaction (rRT-PCR) in the context of SARS-CoV-2 Omicron. Ag-RDT sensitivity and specificity within 1 day of rRT-PCR were evaluated by symptom status throughout the illness episode and Orf1b cycle threshold (Ct). RESULTS: From February to December 2022, 5,757 participants reported 17,572 Ag-RDT results and completed 12,674 rRT-PCR tests, of which 995 (7.9%) were rRT-PCR-positive. Overall sensitivity and specificity were 53.0% (95% CI: 49.6-56.4%) and 98.8% (98.5-99.0%), respectively. Sensitivity was comparatively higher for Ag-RDTs used 1 day after rRT-PCR (69.0%), 4 to 7 days post-symptom onset (70.1%), and Orf1b Ct ≤20 (82.7%). Serial Ag-RDT sensitivity increased with repeat testing ≥2 (68.5%) and ≥4 (75.8%) days after an initial Ag-RDT-negative result. CONCLUSION: Ag-RDT performance varied by clinical characteristics and temporal testing patterns. Our findings support recommendations for serial testing following an initial Ag-RDT-negative result, especially among recently symptomatic persons or those at high-risk for SARS-CoV-2 infection.

The 2017-2018 North American influenza season caused more hospitalizations and deaths than any year since the 2009 H1N1 pandemic. The majority of recorded influenza infections were caused by A(H3N2) viruses, with most of the virus’s North American diversity falling into the A2 clade. Within A2, we observe a subclade which we call A2/re that rose to comprise almost 70% of A(H3N2) viruses circulating in North America by early 2018. Unlike most fast-growing clades, however, A2/re contains no amino acid substitutions in the hemagglutinin (HA) segment. Moreover, HI assays did not suggest substantial antigenic differences between A2/re viruses and viruses sampled during the 2016-2017 season. Rather, we observe that the A2/re clade was the result of a reassortment event that occurred in late 2016 or early 2017 and involved the combination of the HA and PB1 segments of an A2 virus with neuraminidase (NA) and other segments a virus from the clade A1b. The success of this clade shows the need for antigenic analysis that targets NA in addition to HA. Our results illustrate the potential for non-HA drivers of viral success and necessitate the need for more thorough tracking of full viral genomes to better understand the dynamics of influenza epidemics.

Background Households represent important settings for transmission of influenza and other respiratory viruses. Current influenza diagnosis and treatment relies upon patient visits to healthcare facilities, which may lead to under-diagnosis and treatment delays. This study aimed to assess the feasibility of an at-home approach to influenza diagnosis and treatment via home testing, telehealth care, and rapid antiviral home delivery.Methods We conducted a pilot interventional study of remote influenza diagnosis and treatment in Seattle-area households with children during the 2019-2020 influenza season using pre-positioned nasal swabs and home influenza tests. Home monitoring for respiratory symptoms occurred weekly; if symptoms were reported within 48 hours of onset, participants collected mid-nasal swabs and used a rapid home-based influenza immunoassay. An additional home-collected swab was returned to a laboratory for confirmatory influenza RT-PCR testing. Baloxavir antiviral treatment was prescribed and delivered to symptomatic and age-eligible participants, following a telehealth encounter.Results 124 households comprising 481 individuals self-monitored for respiratory symptoms, with 58 home tests administered. 12 home tests were positive for influenza, of which 8 were true positives confirmed by RT-PCR. The sensitivity and specificity of the home influenza test was 72.7% and 96.2%, respectively. There were 8 home deliveries of baloxavir, with 7 (87.5%) occurring within 3 hours of prescription, and all within 48 hours of symptom onset.Conclusions We demonstrate the feasibility of self-testing combined with rapid home delivery of influenza antiviral treatment. This approach may be an important control strategy for influenza epidemics and pandemics.Summary In this pilot study, 481 individuals self-monitored for respiratory symptoms. Of 58 home tests, 12 were influenza-positive. There were 8 baloxavir home deliveries within 48 hours of illness onset. A home-based approach to influenza diagnosis and treatment could be feasible.Competing Interest StatementH.Y.C. has received research support from GlaxoSmithKline, Novavax, and Sanofi Pasteur; J.A.E. has received research support from AstraZeneca, GlaxoSmithKine, Merck, and Pfizer and served as a consultant for Sanofi Pasteur and Meissa Vaccines. M.L.J. has received research support from Sanofi Pasteur. M.B. receives research support and serves as a consultant for Ansun Biopharma, Gilead Sciences, Janssen, and Vir Biotechnology; and serves as a consultant to GlaxoSmithKline, ReViral, ADMA, Pulmocdie and ModernaClinical TrialNCT04141930Funding StatementThe Seattle Flu Study is funded by Gates Ventures. The funder was not involved in the design of the study, does not have any ownership over the management and conduct of the study, the data, or the rights to publish.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:University of Washington Institutional Review Board (STUDY00008200)All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesData and code used for analyses may be available upon request.

Introduction Influenza epidemics and pandemics cause significant morbidity and mortality. An effective response to a potential pandemic requires the infrastructure to rapidly detect, characterize, and potentially contain new and emerging influenza strains at a 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 2018-19 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 modeling platforms are in development to characterize 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. Results will be disseminated through talks at conferences, peer-reviewed publications, and on the study website (www.seattleflu.org).Strengths and limitations of this study- Large-scale multiple-arm study of respiratory illness characterization with collection of samples from individuals in the community as well as in ambulatory care and hospital settings- Integration of sociodemographic, clinical, and geospatial data on a regional level- Multiplex molecular testing for multiple viral and bacterial pathogens and whole genome sequencing of influenza for detailed molecular epidemiologic characterization and transmission mapping- Geographically and socioeconomically diverse sampling of community-based acute respiratory illnessesCompeting Interest StatementAmanda Adler, Elisabeth Brandstetter, Michael Famulare, Chris D. Frazar, Peter D. Han, Reena K. Gulati, James Hadfield, Michael L. Jackson, Anahita Kiavand, Louise E. Kimball, Kirsten Lacombe, Jennifer Logue, Victoria Lyon, Kira L. Newman, Thomas R. Sibley, Jay Shendure, Lea Starita, Monica L. Zigman Suchsland, and Caitlin Wolf declare no competing interests. Helen Y Chu receives research support from Sanofi, Cepheid, and Genentech/Roche and is a consultant for Merck. Janet Englund receives research support to her institution from Astrazeneca, GlaxoSmithKline, Merck, and Novavax and is a consultant for Sanofi Pasteur and Meissa Vaccines.Funding StatementThe Seattle Flu Study is funded through the Brotman Baty Institute. The funder was not involved in the design of the study, does not have any ownership over the management and conduct of the study, the data, or the rights to publishAuthor DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable YesThe data will be accessed only by authorized individuals on the study team. Access to deidentified, aggregated data and analysis code will be publicly available on the study web page (www.seattleflu.org). http://www.seattleflu.org

Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth.Competing Interest StatementThe authors have declared no competing interest.

Introduction Pre-exposure prophylaxis (PrEP) is an effective prevention intervention that can be used to control HIV incidence especially among people who are at increased risk for HIV such as adolescent girls and young women (AGYW) and adolescent boys and young men (ABYM). In South Africa, various approaches of delivering PrEP have been adopted at different service delivery points (facility-based only, school-based only, community-based only and hybrid school-facility and community-facility models) to overcome challenges associated with individual, structural, and health systems related barriers that may hinder access to and uptake of PrEP among these populations. However, little is known about how to optimize PrEP implementation and operational strategies to achieve high sustained uptake of good quality services for AGYW and ABYM. This study aims to identify effective and feasible PrEP models of care for improving PrEP uptake, continuation, and adherence among AGYW and ABYM. Methods and analysis A sequential explanatory mixed-methods study will be conducted in 22 service delivery points (SDPs) in uMgungundlovu district, KwaZulu-Natal, South Africa. We will recruit 600 HIV negative, sexually active, high risk, AGYW (aged 15-24 years) and ABYM (aged 15-35 years). Enrolled participants will be followed up at 1-, 4- and 7-months to determine continuation and adherence to PrEP. We will conduct two focus group discussions (with 8 participants in each group) across four groups (i. Initiated PrEP within 1 month, ii. Did not initiate PrEP within 1 month, iii. Continued PrEP at 4/7 months and iv. Did not continue PrEP at 4/7 months) and 48 in-depth interviews from each of the four groups (12 per group). Twelve key informant interviews with stakeholders working in HIV programs will also be conducted. Associations between demographic characteristics stratified by PrEP initiation and by various service-delivery models will be assessed using Chi-square/Fishers exact tests or t-test/Mann Whitney test. A general inductive approach will be used to analyze the qualitative data. Ethics and dissemination The protocol was approved by the South African Medical Research Council Health Research Ethics Committee (EC051-11/2020). This project was reviewed by the U.S. Centers for Disease Control and Prevention (Atlanta, GA), Centers for Global Health Associate Director for Science in accordance with CDC human research protection procedures and was determined to be research, but CDC investigators did not interact with human subjects or have access to identifiable data or specimens for research purposes. Provincial and district level approval has been granted. Findings from the study will be communicated to the study population and results will be presented to stakeholders and at appropriate local and international conferences. Outputs will also include a policy brief, peer-reviewed journal articles and research capacity building through research degrees. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Introduction: Although South Africa adopted the World Health Organization's Test and Treat strategy for HIV epidemic control in 2016, antiretroviral therapy (ART) treatment initiation and retention remain below target. In 2017, an estimated 56.3% of men living with HIV were on ART. We aimed to investigate factors associated with non-use of ART among men in South Africa. Method(s): Utilizing data from the fifth South African National HIV Prevalence, Incidence, Behavior and Communication (SABSSM V) cross-sectional survey conducted in 2017, a subset of data from HIV-positive men was stratified based on presence/absence of antiretroviral drugs (ARVs) detected in dried blood spot samples. Data were weighted to be representative of the national population and analyzed using multivariable logistic regression to assess predictors of non-use of ART; p<0.05 was considered significant. Result(s): A total of 6,920 men aged >=15 years old were enrolled in the study, of whom 953 (13.8%) tested HIV-positive. Among those HIV-positive, 810 (85%) had a known ARV test result: 470 (58%) had ARVs detected, and 340 (42%) did not have ARVs detected. Non-use of ART in men was associated with high-risk alcohol use (adjusted odds ratio (AOR)=3.68, 95% confidence interval (CI): 1.03-13.23), being a widower compared to being unmarried (AOR=6.99, 95%CI: 1.46-33.42), and having drug-resistant HIV (AOR=28.12, 95%CI: 13.89-56.94). Per year increase in age (AOR=0.67, 95%CI: 0.47-0.96), residence in rural tribal localities compared to urban localities (AOR=0.38, 95%CI: 0.18-0.78), or having a comorbidity such as tuberculosis or diabetes (AOR=0.06, 95%CI: 0.03-0.14) were positively associated with ART use. Conclusion(s): Non-use of ART was strongly associated with HIV drug resistance. Young men who are living with HIV, those with high-risk alcohol use, and widowers, should be a priority for HIV programming and linkage to care. Identifying interventions that are effective at linking these men to ART will help reduce the burden of HIV in South Africa. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Introduction In South Africa, HIV prevalence among adolescent girls and young women (AGYW) was 5.8% (15-19 years) and 15.6% (20-24 years) respectively in 2017. Amongst South African males, HIV prevalence in 2017 was 4.7% (15-19 years), 4.8% (20-24 years), 12.4% (25-29 years) and 18.4% (30-34 years). The National Department of Health adopted the universal test and treat (UTT) strategy in 2016, resulting in increases in same-day antiretroviral therapy initiations and linkage to care. Monitoring progress towards attainment of South Africa's 95-95-95 targets amongst AGYW and adolescent boys and young men (ABYM) relies on high quality data to identify and address gaps in linkage to care. The purpose of this study is to provide evidence to guide efforts to improve linkage to, and retention in, HIV care among AGYW and ABYM in KwaZulu-Natal, in the context of the UTT strategy. Methods and analysis This is a mixed methods study, which will be conducted in uMgungundlovu district of KwaZulu-Natal, over a 24-month period, in 22 purposively selected HIV testing and treatment service delivery points (SDPs). For the quantitative component, a sample size of 1100 participants will be recruited into the study. The qualitative component will include 30 participating patients who were successfully linked to care, 30 who were not, and 30 who have never tested for HIV. The questionnaire study population comprises of 231 healthcare providers and AGYW aged 15-24 years and ABYM aged 15-35 years old. Primary outcomes will be evaluated using a logistic regression model. A time to event analysis will also be conducted taking the study design into account. Quantitative data for outcome variables and process indicators will be summarized by domain evaluated with logistic regression to account for potential confounders. For qualitative data, manual thematic content analysis will be conducted. Ethics and dissemination The protocol was approved by the South African Medical Research Council Health Research Ethics Committee (EC052-11/2020). Findings from the study will be communicated to the study population and results will be presented to stakeholders and at appropriate local and international conferences. Outputs will also include a policy brief, peer reviewed journal articles and research capacity building through research degrees. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has spread globally, resulting in >300,000 reported cases worldwide as of March 21st, 2020. Here we investigate the genetic diversity and genomic epidemiology of SARS-CoV-2 in Northern California using samples from returning travelers, cruise ship passengers, and cases of community transmission with unclear infection sources. Virus genomes were sampled from 29 patients diagnosed with COVID-19 infection from Feb 3rd through Mar 15th. Phylogenetic analyses revealed at least 8 different SARS-CoV-2 lineages, suggesting multiple independent introductions of the virus into the state. Virus genomes from passengers on two consecutive excursions of the Grand Princess cruise ship clustered with those from an established epidemic in Washington State, including the WA1 genome representing the first reported case in the United States on January 19th. We also detected evidence for presumptive transmission of SARS-CoV-2 lineages from one community to another. These findings suggest that cryptic transmission of SARS-CoV-2 in Northern California to date is characterized by multiple transmission chains that originate via distinct introductions from international and interstate travel, rather than widespread community transmission of a single predominant lineage. Rapid testing and contact tracing, social distancing, and travel restrictions are measures that will help to slow SARS-CoV-2 spread in California and other regions of the USA.

BACKGROUND: Epidemiologic studies support associations of exposure to endocrine disrupting chemicals (EDCs), such as some phthalates, phenols, and parabens with a wide range of cognitive and behavioral traits. While many of these traits are associated with academic achievement, the relationship of EDC exposure specifically with academic achievement in adolescence has not yet been studied. OBJECTIVE: We assessed the association of urinary biomarker concentrations of EDCs with academic achievement in adolescents as well as the potential for psychosocial factors to modify associations. METHODS: We quantified urinary concentrations of select EDCs in 205 adolescent participants from the New Bedford Cohort (NBC), a prospective birth cohort of children born to mothers residing near the New Bedford Harbor Superfund site in Massachusetts, and estimated associations between EDCs and adolescent academic achievement assessed with the Wide Range Achievement Test (WRAT). Measures of socioeconomic status and the home environment were used to estimate psychosocial stress. RESULTS: Urinary concentrations of antiandrogenic phthalates were inversely associated with Math Computation scores. For example, each doubling of the concentration of antiandrogenic phthalate metabolites in urine was associated with a 1.94 point decrease (95% CI: 3.84, -0.05) in Math Computation scores, indicating poorer performance. For the most part, associations were stronger in adolescents with more, as compared to less, social disadvantage, but most of these differences did not achieve statistical significance. CONCLUSION: Our findings support the potential for adolescents' exposure to antiandrogenic phthalates to correlate with poorer academic achievement in math, particularly among participants with greater psychosocial stress.

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.

INTRODUCTION: Adolescent girls and young women (AGYW) aged 15-24 years and adolescent boys and young men (ABYM) aged 15-34 years represent one of the populations at highest risk for HIV-infection in South Africa. The National Department of Health adopted the universal test and treat (UTT) strategy in 2016, resulting in increases in same-day antiretroviral therapy initiations and linkage to care. Monitoring progress towards attainment of South Africa's 95-95-95 targets amongst AGYW and ABYM relies on high quality data to identify and address gaps in linkage to care. The aim of this study is to describe the current approaches for engaging AGYW and ABYM in the treatment continuum to generate knowledge that can guide efforts to improve linkage to, and retention in, HIV care among these populations in KwaZulu-Natal, South Africa. METHODS AND ANALYSIS: This is a mixed methods study, which will be conducted in uMgungundlovu district of KwaZulu-Natal, over a 24-month period, in 22 purposively selected HIV testing and treatment service delivery points (SDPs). For the quantitative component, a sample of 1100 AGYW aged 15-24 years and ABYM aged 15-35 years old will be recruited into the study, in addition to 231 healthcare providers (HCPs) involved in the implementation of the UTT program. The qualitative component will include 30 participating patients who were successfully linked to care, 30 who were not, and 30 who have never tested for HIV. Key informant interviews will also be conducted with 24 HCPs. Logistic regression will be used to model the primary outcomes on SDP types, while a time to event analysis will be conducted using a Cox regression model and adjusting the standard errors of the hazard ratio for the clustering of participants within SDPs. For qualitative data, a general inductive approach of analysis will be used. DISSEMINATION: Findings from the study will be communicated to the study population and results will be presented to stakeholders and at appropriate local and international conferences. Outputs will also include a policy brief, peer reviewed journal articles and research capacity building through research degrees.

INTRODUCTION: Pre-exposure prophylaxis (PrEP) is an effective prevention intervention that can be used to control HIV incidence especially among people who are at increased risk for HIV such as adolescent girls and young women (AGYW) and adolescent boys and young men (ABYM). In South Africa, various approaches of delivering PrEP have been adopted at different service delivery points (facility-based only, school-based only, community-based only and hybrid school-facility and community-facility models) to overcome challenges associated with individual, structural, and health systems related barriers that may hinder access to and uptake of PrEP among these populations. However, little is known about how to optimize PrEP implementation and operational strategies to achieve high sustained uptake of good quality services for AGYW and ABYM. This study aims to identify effective and feasible PrEP models of care for improving PrEP uptake, continuation, and adherence among AGYW and ABYM. METHODS AND ANALYSIS: A sequential explanatory mixed-methods study will be conducted in 22 service delivery points (SDPs) in uMgungundlovu district, KwaZulu-Natal, South Africa. We will recruit 600 HIV negative, sexually active, high risk, AGYW (aged 15-24 years) and ABYM (aged 15-35 years). Enrolled participants will be followed up at 1-, 4- and 7-months to determine continuation and adherence to PrEP. We will conduct two focus group discussions (with 8 participants in each group) across four groups (i. Initiated PrEP within 1 month, ii. Did not initiate PrEP within 1 month, iii. Continued PrEP at 4/7 months and iv. Did not continue PrEP at 4/7 months) and 48 in-depth interviews from each of the four groups (12 per group). Twelve key informant interviews with stakeholders working in HIV programs will also be conducted. Associations between demographic characteristics stratified by PrEP initiation and by various service-delivery models will be assessed using Chi-square/Fishers exact tests or t-test/Mann Whitney test. A general inductive approach will be used to analyze the qualitative data. ETHICS AND DISSEMINATION: The protocol was approved by the South African Medical Research Council Health Research Ethics Committee (EC051-11/2020). Findings from the study will be communicated to the study population and results will be presented to stakeholders and at appropriate local and international conferences. Outputs will also include a policy brief, peer-reviewed journal articles and research capacity building through research degrees.

We reconstructed the 2016-2017 Zika virus epidemic in Puerto Rico by using complete genomes to uncover the epidemic's origin, spread, and evolutionary dynamics. Our study revealed that the epidemic was propelled by multiple introductions that spread across the island, intricate evolutionary patterns, and ≈10 months of cryptic transmission.

A group convened and led by the Virus Evolution Working Group of the World Health Organization reports on its deliberations and announces a naming scheme that will enable clear communication about SARS-CoV-2 variants of interest and concern. | | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has a linear, unsegmented, positive-sense RNA genome. As with all viruses, SARS-CoV-2 continuously adapts to changing environments in real time via random genome mutations that are subject to natural selection. Most mutations are neutral or detrimental to the virus; however, a small number of mutations may provide a selective advantage, such as escape from the host immune system or resistance to antiviral drugs. Such mutations may also lead to increased fitness for transmissibility. As mutated forms of viruses or variants spread from person to person, they will eventually be detected at the population level.

IMPORTANCE: The association between COVID-19 symptoms and SARS-CoV-2 viral levels in children living in the community is not well understood. OBJECTIVE: To characterize symptoms of pediatric COVID-19 in the community and analyze the association between symptoms and SARS-CoV-2 RNA levels, as approximated by cycle threshold (Ct) values, in children and adults. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used a respiratory virus surveillance platform in persons of all ages to detect community COVID-19 cases from March 23 to November 9, 2020. A population-based convenience sample of children younger than 18 years and adults in King County, Washington, who enrolled online for home self-collection of upper respiratory samples for SARS-CoV-2 testing were included. EXPOSURES: Detection of SARS-CoV-2 RNA by reverse transcription-polymerase chain reaction (RT-PCR) from participant-collected samples. MAIN OUTCOMES AND MEASURES: RT-PCR-confirmed SARS-CoV-2 infection, with Ct values stratified by age and symptoms. RESULTS: Among 555 SARS-CoV-2-positive participants (mean [SD] age, 33.7 [20.1] years; 320 were female [57.7%]), 47 of 123 children (38.2%) were asymptomatic compared with 31 of 432 adults (7.2%). When symptomatic, fewer symptoms were reported in children compared with adults (mean [SD], 1.6 [2.0] vs 4.5 [3.1]). Symptomatic individuals had lower Ct values (which corresponded to higher viral RNA levels) than asymptomatic individuals (adjusted estimate for children, -3.0; 95% CI, -5.5 to -0.6; P = .02; adjusted estimate for adults, -2.9; 95% CI, -5.2 to -0.6; P = .01). The difference in mean Ct values was neither statistically significant between symptomatic children and symptomatic adults (adjusted estimate, -0.7; 95% CI, -2.2 to 0.9; P = .41) nor between asymptomatic children and asymptomatic adults (adjusted estimate, -0.6; 95% CI, -4.0 to 2.8; P = .74). CONCLUSIONS AND RELEVANCE: In this community-based cross-sectional study, SARS-CoV-2 RNA levels, as determined by Ct values, were significantly higher in symptomatic individuals than in asymptomatic individuals and no significant age-related differences were found. Further research is needed to understand the role of SARS-CoV-2 RNA levels and viral transmission.

BACKGROUND: Households represent important settings for transmission of influenza and other respiratory viruses. Current influenza diagnosis and treatment relies upon patient visits to healthcare facilities, which may lead to under-diagnosis and treatment delays. This study aimed to assess the feasibility of an at-home approach to influenza diagnosis and treatment via home testing, telehealth care, and rapid antiviral home delivery. METHODS: We conducted a pilot interventional study of remote influenza diagnosis and treatment in Seattle-area households with children during the 2019-2020 influenza season using pre-positioned nasal swabs and home influenza tests. Home monitoring for respiratory symptoms occurred weekly; if symptoms were reported within 48 hours of onset, participants collected mid-nasal swabs and used a rapid home-based influenza immunoassay. An additional home-collected swab was returned to a laboratory for confirmatory influenza RT-PCR testing. Baloxavir antiviral treatment was prescribed and delivered to symptomatic and age-eligible participants, following a telehealth encounter. RESULTS: 124 households comprising 481 individuals self-monitored for respiratory symptoms, with 58 home tests administered. 12 home tests were positive for influenza, of which eight were true positives confirmed by RT-PCR. The sensitivity and specificity of the home influenza test were 72.7% and 96.2%, respectively. There were eight home deliveries of baloxavir, with 7 (87.5%) occurring within 3 hours of prescription and all within 48 hours of symptom onset. CONCLUSIONS: We demonstrate the feasibility of self-testing combined with rapid home delivery of influenza antiviral treatment. This approach may be an important control strategy for influenza epidemics and pandemics.

The 2017-2018 North American influenza season caused more hospitalizations and deaths than any year since the 2009 H1N1 pandemic. The majority of recorded influenza infections were caused by A(H3N2) viruses, with most of the virus's North American diversity falling into the A2 clade. Within A2, we observe a subclade which we call A2/re that rose to comprise almost 70 per cent of A(H3N2) viruses circulating in North America by early 2018. Unlike most fast-growing clades, however, A2/re contains no amino acid substitutions in the hemagglutinin (HA) segment. Moreover, hemagglutination inhibition assays did not suggest substantial antigenic differences between A2/re viruses and viruses sampled during the 2016-2017 season. Rather, we observe that the A2/re clade was the result of a reassortment event that occurred in late 2016 or early 2017 and involved the combination of the HA and PB1 segments of an A2 virus with neuraminidase (NA) and other segments a virus from the clade A1b. The success of this clade shows the need for antigenic analysis that targets NA in addition to HA. Our results illustrate the potential for non-HA drivers of viral success and necessitate the need for more thorough tracking of full viral genomes to better understand the dynamics of influenza epidemics.

BACKGROUND: Non-influenza respiratory viruses are responsible for a substantial burden of disease in the United States. Household transmission is thought to contribute significantly to subsequent transmission through the broader community. In the context of the COVID-19 pandemic, contactless surveillance methods are of particular importance. METHODS: From November 2019 to April 2020, 303 households in the Seattle area were remotely monitored in a prospective longitudinal study for symptoms of respiratory viral illness. Enrolled participants reported weekly symptoms and submitted respiratory samples by mail in the event of an acute respiratory illness (ARI). Specimens were tested for fourteen viruses, including SARS-CoV-2, using RT-PCR. Participants completed all study procedures at home without physical contact with research staff. RESULTS: In total, 1171 unique participants in 303 households were monitored for ARI. Of participating households, 128 (42%) included a child aged <5 years and 202 (67%) included a child aged 5-12 years. Of the 678 swabs collected during the surveillance period, 237 (35%) tested positive for one or more non-influenza respiratory viruses. Rhinovirus, common human coronaviruses, and respiratory syncytial virus were the most common. Four cases of SARS-CoV-2 were detected in three households. CONCLUSIONS: This study highlights the circulation of respiratory viruses within households during the winter months during the emergence of the SARS-CoV-2 pandemic. Contactless methods of recruitment, enrollment and sample collection were utilized throughout this study, and demonstrate the feasibility of home-based, remote monitoring for respiratory infections.

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).

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.

Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence- only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth.

IMPORTANCE: Attention-deficit/hyperactivity disorder (ADHD) is the most common childhood neurobehavioral disorder. Studies suggest that prenatal and early childhood exposure to endocrine-disrupting chemicals may be associated with ADHD, but the association during adolescence has not been studied to date. OBJECTIVE: To evaluate the association between exposure to select endocrine-disrupting chemicals during adolescence and ADHD-related behaviors. DESIGN, SETTING, AND PARTICIPANTS: For this cross-sectional analysis, data were collected from 205 adolescents in the New Bedford Cohort, an ongoing prospective birth cohort, between June 18, 2011, and June 10, 2014. The adolescents provided spot urine samples and underwent neurodevelopmental testing. Statistical analyses performed from January 15 to December 31, 2019, used a repeated-measures analysis with multivariate modified Poisson models to estimate the adjusted relative risk of ADHD-related behaviors associated with exposure to endocrine-disrupting chemicals. EXPOSURES: Urinary biomarker concentrations of endocrine-disrupting chemicals or their metabolites, including phthalates, parabens, phenols, and triclocarban, were quantified. Summary exposure measures were created, combining biomarker concentrations of chemicals with a shared mechanism of action, exposure pathway, or chemical class. MAIN OUTCOMES AND MEASURES: Behaviors related to ADHD were assessed with up to 14 indices from self-, parent-, and teacher-completed behavioral checklists using validated and standardized instruments; specifically, the Conners Attention Deficit Scale and the Behavior Assessment System for Children, Second Edition. Scores on each index were dichotomized to identify those with evidence of a significant behavioral problem, defined by each scale's interpretive guidelines. RESULTS: Among the 205 participants, the mean (SD) age at assessment was 15.3 (0.7) years, with 112 girls (55%) and 124 non-Hispanic White participants (61%). The median urine concentrations were 0.45 μmol/L of Σantiandrogenic phthalates, 0.13 μmol/L of ΣDEHP metabolites, 0.49 μmol/L of Σpersonal care product phthalates, 0.35 μmol/L of Σparabens, 0.02 μmol/L of Σbisphenols, and 0.02 μmol/L of Σdichlorophenols. A total of 82 (40%) had scores consistent with a significant behavioral problem, whereas 39 (19%) had an ADHD diagnosis. Each 2-fold increase in the sum of antiandrogenic phthalate concentrations was associated with a 1.34 (95% CI, 1.00-1.79) increase in the risk of significant ADHD-related behavior problems, whereas a 2-fold increase in the sum of dichlorophenols was associated with a 1.15 (95% CI, 1.01-1.32) increased risk. These associations tended to be stronger in male participants, but comparisons of sex-specific differences were imprecise. CONCLUSIONS AND RELEVANCE: Endocrine-disrupting chemicals are used in a wide variety of consumer products resulting in ubiquitous exposure. The study findings suggest that exposure to some of these chemicals, particularly certain phthalates, during adolescence may be associated with behaviors characteristic of ADHD.

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.

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has spread globally, with >52,000 cases in California as of May 4, 2020. Here we investigate the genomic epidemiology of SARS-CoV-2 in Northern California from late January to mid-March 2020, using samples from 36 patients spanning 9 counties and the Grand Princess cruise ship. Phylogenetic analyses revealed the cryptic introduction of at least 7 different SARS-CoV-2 lineages into California, including epidemic WA1 strains associated with Washington State, with lack of a predominant lineage and limited transmission between communities. Lineages associated with outbreak clusters in 2 counties were defined by a single base substitution in the viral genome. These findings support contact tracing, social distancing, and travel restrictions to contain SARS-CoV-2 spread in California and other states.

From January 21 through February 23, 2020, public health agencies detected 14 U.S. cases of coronavirus disease 2019 (COVID-19), all related to travel from China (1,2). The first nontravel-related U.S. case was confirmed on February 26 in a California resident who had become ill on February 13 (3). Two days later, on February 28, a second nontravel-related case was confirmed in the state of Washington (4,5). Examination of four lines of evidence provides insight into the timing of introduction and early transmission of SARS-CoV-2, the virus that causes COVID-19, into the United States before the detection of these two cases. First, syndromic surveillance based on emergency department records from counties affected early by the pandemic did not show an increase in visits for COVID-19-like illness before February 28. Second, retrospective SARS-CoV-2 testing of approximately 11,000 respiratory specimens from several U.S. locations beginning January 1 identified no positive results before February 20. Third, analysis of viral RNA sequences from early cases suggested that a single lineage of virus imported directly or indirectly from China began circulating in the United States between January 18 and February 9, followed by several SARS-CoV-2 importations from Europe. Finally, the occurrence of three cases, one in a California resident who died on February 6, a second in another resident of the same county who died February 17, and a third in an unidentified passenger or crew member aboard a Pacific cruise ship that left San Francisco on February 11, confirms cryptic circulation of the virus by early February. These data indicate that sustained, community transmission had begun before detection of the first two nontravel-related U.S. cases, likely resulting from the importation of a single lineage of virus from China in late January or early February, followed by several importations from Europe. The widespread emergence of COVID-19 throughout the United States after February highlights the importance of robust public health systems to respond rapidly to emerging infectious threats.