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.

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 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.

Preliminary support for a 'dry swab, extraction free' protocol for SARS-CoV-2 testing via RT-qPCR

Structured AbstractO_ST_ABSBackgroundC_ST_ABSThe urgent need for massively scaled clinical testing for SARS-CoV-2, along with global shortages of critical reagents and supplies, has necessitated development of streamlined laboratory testing protocols. Conventional nucleic acid testing for SARS-CoV-2 involves collection of a clinical specimen with a nasopharyngeal swab in transport medium, nucleic acid extraction, and quantitative reverse transcription PCR (RT-qPCR) (1). As testing has scaled across the world, the global supply chain has buckled, rendering testing reagents and materials scarce (2). To address shortages, we developed SwabExpress, an end-to-end protocol developed to employ mass produced anterior nares swabs and bypass the requirement for transport media and nucleic acid extraction. MethodsWe evaluated anterior nares swabs, transported dry and eluted in low-TE buffer as a direct-to-RT-qPCR alternative to extraction-dependent viral transport media. We validated our protocol of using heat treatment for viral activation and added a proteinase K digestion step to reduce amplification interference. We tested this protocol across archived and prospectively collected swab specimens to fine-tune test performance. ResultsAfter optimization, SwabExpress has a low limit of detection at 2-4 molecules/uL, 100% sensitivity, and 99.4% specificity when compared side-by-side with a traditional RT-qPCR protocol employing extraction. On real-world specimens, SwabExpress outperforms an automated extraction system while simultaneously reducing cost and hands-on time. ConclusionSwabExpress is a simplified workflow that facilitates scaled testing for COVID-19 without sacrificing test performance. It may serve as a template for the simplification of PCR-based clinical laboratory tests, particularly in times of critical shortages during pandemics.