Local-Scale phylodynamics reveal differential community impact of SARS-CoV-2 in metropolitan US county

SARS-CoV-2 transmission is largely driven by heterogeneous dynamics at a local scale, leaving local health departments to design interventions with limited information. We analyzed SARS-CoV-2 genomes sampled between February 2020 and March 2022 jointly with epidemiological and cell phone mobility data to investigate fine scale spatiotemporal SARS-CoV-2 transmission dynamics in King County, Washington, a diverse, metropolitan US county. We applied an approximate structured coalescent approach to model transmission within and between North King County and South King County alongside the rate of outside introductions into the county. Our phylodynamic analyses reveal that following stay-at-home orders, the epidemic trajectories of North and South King County began to diverge. We find that South King County consistently had more reported and estimated cases, COVID-19 hospitalizations, and longer persistence of local viral transmission when compared to North King County, where viral importations from outside drove a larger proportion of new cases. Using mobility and demographic data, we also find that South King County experienced a more modest and less sustained reduction in mobility following stay-at-home orders than North King County, while also bearing more socioeconomic inequities that might contribute to a disproportionate burden of SARS-CoV-2 transmission. Overall, our findings suggest a role for local-scale phylodynamics in understanding the heterogeneous transmission landscape. One Sentence SummaryAnalysis of SARS-CoV-2 genomes in King County, Washington show that diverse areas in the same metropolitan region can have different epidemic dynamics.

Trends in risk factors and symptoms associated with SARS-CoV-2 and Rhinovirus test positivity in King County, Washington: A Test-Negative Design Study of the Greater Seattle Coronavirus Assessment Network

ImportanceFew 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 co-circulating endemic viruses, such as rhinovirus. ObjectiveTo understand how risk factors and symptoms associated with SARS-CoV-2 test positivity changed over the course of the pandemic and to compare these to the factors associated with rhinovirus test positivity. DesignThis test-negative design study used multivariable logistic regression to assess associations between SARS-CoV-2 and rhinovirus test positivity and self-reported demographic and symptom variables over a 22-month period. SettingKing County, Washington, June 2020-April 2022 Participants23,278 symptomatic individuals of all ages enrolled in a cross-sectional community surveillance study. ExposuresSelf-reported data for 15 demographic and health behavior variables and 16 symptoms. Main Outcome(s) and Measure(s)RT-PCR confirmed SARS-CoV-2 or rhinovirus infection. ResultsClose contact with a SARS-CoV-2 case (adjusted odds ratio, aOR 4.3, 95% CI 3.7-5.0) and loss of smell/taste (aOR 3.7, 95% CI 3.0-4.5) were the variables most associated with SARS-CoV-2 test positivity, but both attenuated during the Omicron period. Contact with a vaccinated case (aOR 2.4, 95% CI 1.7-3.3) was associated with a lower odds of test positivity than contact with an unvaccinated case (aOR 4.4, 95% CI 2.7-7.3). Sore throat was associated with Omicron infection (aOR 2.3, 95% CI 1.6-3.2) but not Delta. Vaccine effectiveness for participants fully vaccinated with a booster dose was 43% (95% CI 11-63%) for Omicron and 92% (95% CI 61-100%) for Delta. Variables associated with rhinovirus test positivity included age <12 years (aOR 4.0, 95% CI 3.5-4.6) and reporting a runny or stuffy nose (aOR 4.6, 95% CI 4.1-5.2). Race, region, and household crowding were significantly associated with both SARS-CoV-2 and rhinovirus test positivity. Conclusions and RelevanceEstimated risk factors and symptoms associated with SARS-CoV-2 infection have 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 socioeconomic disparities persisted in the third year of SARS-CoV-2 circulation and were also present in rhinovirus infection, although the causal pathways remain unclear. Trends in testing behavior and availability may influence these results. Key Points QuestionWhat are the characteristics associated with SARS-CoV-2 and rhinovirus infection? FindingsIn this test-negative design study of 23,278 participants, reporting close contact with a SARS-CoV-2 case was the strongest risk factor associated with test positivity. Loss of smell and taste was associated with the Delta variant, but not the Omicron variant. Vaccination and prior infection provided greater protection against Delta infection than Omicron Infection. Young age was the strongest predictor of rhinovirus positivity. Sociodemographic disparities were present for both SARS-CoV-2 and rhinovirus. MeaningMonitoring factors associated with respiratory pathogen test positivity remains important to identify at-risk populations in the post-SARS-CoV-2 pandemic period.

Interactions among 17 respiratory pathogens: a cross-sectional study using clinical and community surveillance data

BackgroundCo-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. MethodsWe 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. Results21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33{middle dot}5%), Streptococcus pneumoniae (SPn, 29{middle dot}0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9{middle dot}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. ConclusionsViral 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.

Associations between SARS-CoV-2 variants and risk of COVID-19 hospitalization among confirmed cases in Washington State: a retrospective cohort study

BackgroundThe COVID-19 pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with seven SARS-CoV-2 variants. MethodsOur study includes individuals with positive SARS-CoV-2 RT-PCR in the Washington Disease Reporting System with available viral genome data, from December 1, 2020 to January 14, 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. Findings58,848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95%CI 2.40-4.26), Beta (HR 2.85, 95%CI 1.56-5.23), Delta (HR 2.28 95%CI 1.56-3.34) or Alpha (HR 1.64, 95%CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95%CI 0.56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. ConclusionInfection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance. SummaryHospitalization risk following infection with SARS-CoV-2 variant remains unclear. We find a higher hospitalization risk in cases infected with Alpha, Beta, Gamma, and Delta, but not Omicron, with vaccination lowering risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.

SARS-CoV-2 Epidemiology on a Public University Campus in Washington State

BackgroundTesting programs have been utilized as part of SARS-CoV-2 mitigation strategies on university campuses, and it is not known which strategies successfully identify cases and contain outbreaks. ObjectiveEvaluation of a testing program to control SARS-CoV-2 transmission at a large university. DesignProspective longitudinal study using remote contactless enrollment, daily mobile symptom and exposure tracking, and self-swab sample collection. Individuals were tested if the participant was (1) exposed to a known case, developed new symptoms, or reported high-risk behavior, (2) a member of a group experiencing an outbreak, or (3) at baseline upon enrollment. SettingAn urban, public university during Autumn quarter of 2020 ParticipantsStudents, staff, and faculty. MeasurementsSARS-CoV-2 PCR testing was conducted, and viral genome sequencing was performed. ResultsWe enrolled 16,476 individuals, performed 29,783 SARS-CoV-2 tests, and detected 236 infections. Greek community affiliation was the strongest risk factor for testing positive. 75.0% of positive cases reported at least one of the following: symptoms (60.8%), exposure (34.7%), or high-risk behaviors (21.5%). 88.1% of viral genomes (52/59) sequenced from Greek-affiliated students were genetically identical to at least one other genome detected, indicative of rapid SARS-CoV-2 spread within this group, compared to 37.9% (11/29) of genomes from non-Greek students and employees. LimitationsObservational study. ConclusionIn a setting of limited resources during a pandemic, we prioritized testing of individuals with symptoms and high-risk exposure during outbreaks. Rapid spread of SARS- CoV-2 occurred within outbreaks without evidence of further spread to the surrounding community. A testing program focused on high-risk populations may be effective as part of a comprehensive university-wide mitigation strategy to control the SARS-CoV-2 pandemic.

Viral genome sequencing places White House COVID-19 outbreak into phylogenetic context

In October 2020, an outbreak of at least 50 COVID-19 cases was reported surrounding individuals employed at or visiting the White House. Here, we applied genomic epidemiology to investigate the origins of this outbreak. We enrolled two individuals with exposures linked to the White House COVID-19 outbreak into an IRB-approved research study and sequenced their SARS-CoV-2 infections. We find these viral sequences are identical to each other, but are distinct from over 190,000 publicly available SARS-CoV-2 genomes. These genomes fall as part of a lineage circulating in the USA since April or May 2020 and detected in Virginia and Michigan. Looking forwards, sequencing of additional community SARS-CoV-2 infections collected in the USA prior to October 2020 may shed further light on its geographic ancestry. In sequencing of SARS-CoV-2 infections collected after October 2020, it may be possible to identify infections that likely descend from the White House COVID-19 outbreak.

Viral genomes reveal patterns of the SARS-CoV-2 outbreak in Washington State

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. One Sentence SummaryLocal outbreak dynamics of SARS-CoV-2 in Washington State (USA) were driven by regionally different mitigation measures and repeated introductions of unique viral variants with different viral loads.

Cryptic transmission of SARS-CoV-2 in Washington State

Following its emergence in Wuhan, China, in late November or early December 2019, the SARS-CoV-2 virus has rapidly spread throughout the world. 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, indicating cryptic spread of COVID-19 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 and the power of pathogen genomics to inform epidemiological understanding.

Effects of weather-related social distancing on city-scale transmission of respiratory viruses

BACKGROUNDUnusually 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. METHODSResidual 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, with disruption of contact rates and care-seeking informed by data on local traffic volumes and hospital admissions. RESULTSDisruption 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 early epidemic phase. CONCLUSIONHigh-intensity, short-duration social distancing measures may substantially reduce total incidence in a respiratory virus epidemic if implemented near the epidemic peak. One sentence summaryDisruptions of school and work due to heavy snowfall in the Seattle metro area reduced the total size of respiratory virus epidemics by up to 9%.