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BackgroundThe annual reappearance of respiratory viruses has been recognized for decades. The onset of the COVID-19 pandemic altered typical respiratory virus transmission patterns. COVID-19 mitigation measures taken during the pandemic were targeted at SARS-CoV-2 respiratory transmission and thus broadly impacted the burden of acute respiratory illnesses (ARIs), in general. MethodsWe used the longitudinal Household Influenza Vaccine Evaluation (HIVE) cohort of households in southeast Michigan to characterize mitigation strategy adherence, respiratory illness burden, and the circulation of 15 respiratory viruses during the COVID-19 pandemic determined by RT-PCR of respiratory specimens collected at illness onset. Study participants were surveyed twice during the study period (March 1, 2020, to June 30, 2021), and serologic specimens were collected for antibody measurement by electrochemiluminescence immunoassay. Incidence rates of ARI reports and virus detections were calculated and compared using incidence rate ratios for the study period and a pre-pandemic period of similar length. ResultsOverall, 437 participants reported a total of 772 ARIs and 329 specimens (42.6%) had respiratory viruses detected. Rhinoviruses were the most frequently detected organism, but seasonal coronaviruses--excluding SARS-CoV-2--were also common. Illness reports and percent positivity were lowest from May to August 2020, when mitigation measures were most stringent. Study participants were more adherent to mitigation measures in the first survey compared with the second survey. Supplemental serology surveillance identified 5.3% seropositivity for SARS-CoV-2 in summer 2020; 3.0% between fall 2020 and winter 2021; and 11.3% in spring 2021. Compared to a pre-pandemic period of similar length, the incidence rate of total reported ARIs for the study period was 50% lower (95% CI: 0.5, 0.6; p<0.001) than the incidence rate from March 1, 2016, to June 30, 2017. ConclusionsThe burden of ARI in the HIVE cohort during the COVID-19 pandemic fluctuated, with declines occurring concurrently with the widespread use of public health measures. It is notable, however, that rhinovirus and seasonal coronaviruses continued to circulate even as influenza and SARS-CoV-2 circulation was low.
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Transmission bottlenecks limit the spread of novel mutations and reduce the efficiency of natural selection along a transmission chain. Many viruses exhibit tight bottlenecks, and studies of early SARS-CoV-2 lineages identified a bottleneck of 1-3 infectious virions. While increased force of infection, host receptor binding, or immune evasion may influence bottleneck size, the relationship between transmissibility and the transmission bottleneck is unclear. Here, we compare the transmission bottleneck of non-variant-of-concern (non-VOC) SARS-CoV-2 lineages to those of the Alpha, Delta, and Omicron variants. We sequenced viruses from 168 individuals in 65 multiply infected households in duplicate to high depth of coverage. In 110 specimens collected close to the time of transmission, within-host diversity was extremely low. At a 2% frequency threshold, 51% had no intrahost single nucleotide variants (iSNV), and 42% had 1-2 iSNV. In 64 possible transmission pairs with detectable iSNV, we identified a bottleneck of 1 infectious virion (95% CI 1-1) for Alpha, Delta, and Omicron lineages and 2 (95% CI 2-2) in non-VOC lineages. The latter was driven by a single iSNV shared in one non-VOC household. The tight transmission bottleneck in SARS-CoV-2 is due to low genetic diversity at the time of transmission, a relationship that may be more pronounced in rapidly transmissible variants. The tight bottlenecks identified here will limit the development of highly mutated VOC in typical transmission chains, adding to the evidence that selection over prolonged infections in immunocompromised patients may drive their evolution.
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BackgroundWe estimated SARS-CoV-2 Delta and Omicron-specific effectiveness of 2 and 3 mRNA COVID-19 vaccine doses in adults against symptomatic illness in US outpatient settings. MethodsBetween October 1, 2021, and February 12, 2022, research staff consented and enrolled eligible participants who had fever, cough, or loss of taste or smell and sought outpatient medical care or clinical SARS-CoV-2 testing within 10 days of illness onset. Using the test-negative design, we compared the odds of receiving 2 or 3 mRNA COVID-19 vaccine doses among SARS-CoV-2 cases versus controls using logistic regression. Regression models were adjusted for study site, age, onset week, and prior SARS-CoV-2 infection. Vaccine effectiveness (VE) was calculated as (1 - adjusted odds ratio) x 100%. ResultsAmong 3847 participants included for analysis, 574 (32%) of 1775 tested positive for SARS-CoV-2 during the Delta predominant period and 1006 (56%) of 1794 participants tested positive during the Omicron predominant period. When Delta predominated, VE against symptomatic illness in outpatient settings was 63% (95% CI: 51% to 72%) among mRNA 2-dose recipients and 96% (95% CI: 93% to 98%) for 3-dose recipients. When Omicron predominated, VE was 21% (95% CI: -6% to 41%) among 2-dose recipients and 62% (95% CI: 48% to 72%) among 3-dose recipients. ConclusionsIn this adult population, 3 mRNA COVID-19 vaccine doses provided substantial protection against symptomatic illness in outpatient settings when the Omicron variant became the predominant cause of COVID-19 in the U.S. These findings support the recommendation for a 3rd mRNA COVID-19 vaccine dose.
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Accurate estimates of total burden of SARS-CoV-2 are needed to inform policy, planning and response. We sought to quantify SARS-CoV-2 cases, hospitalizations, and deaths by age in Michigan. COVID-19 cases reported to the Michigan Disease Surveillance System were multiplied by age and time-specific adjustment factors to correct for under-detection. Adjustment factors were estimated in a model fit to incidence data and seroprevalence estimates. Age-specific incidence of SARS-CoV-2 hospitalization, death, and vaccination, and variant proportions were estimated from publicly available data. We estimated substantial under-detection of infection that varied by age and time. Accounting for under-detection, we estimate cumulative incidence of infection in Michigan reached 75% by mid-November 2021, and over 87% of Michigan residents were estimated to have had [≥]1 vaccination dose and/or previous infection. Comparing pandemic waves, the relative burden among children increased over time. Adults [≥]80 years were more likely to be hospitalized or die if infected in fall 2020 than if infected during later waves. Our results highlight the ongoing risk of periods of high SARS-CoV-2 incidence despite widespread prior infection and vaccination. This underscores the need for long-term planning for surveillance, vaccination, and other mitigation measures amidst continued response to the acute pandemic.
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The first cluster of SARS-CoV-2 cases with lineage B.1.1.7 in the state of Michigan was identified through intensive university-led surveillance sampling and targeted sequencing. A collaborative investigation and response was conducted by the local and state health departments, and the campus and athletic medicine COVID-19 response teams, using S-gene target failure screening and rapid genomic sequencing to inform containment strategies. A total of 50 cases of B.1.1.7-lineage SARS-CoV-2 were identified in this outbreak, which was due to three coincident introductions of B.1.1.7-lineage SARS-CoV-2, all of which were genetically distinct from lineages which later circulated in the broader community. This investigation demonstrates the successful implementation of a genomically-informed outbreak response which can be extended to university campuses and other settings at high risk for rapid emergence of new variants.
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Individuals in contact with persons with COVID-19 are at high risk of developing COVID-19, but protection offered by COVID-19 vaccines in the context of known exposure is unknown. Symptomatic outpatients reporting acute onset of COVID-19-like illness and tested for SARS-CoV-2 infection were enrolled. Among 2,229 participants, 283/451 (63%) of those reporting contact and 331/1778 (19%) without known contact tested SARS-CoV-2 positive. Using the test-negative design, adjusted vaccine effectiveness was 71% (95% confidence interval, 49%-83%) among fully vaccinated participants reporting contact versus 80% (95% CI, 72%-86%) among those without. This study supports COVID-19 vaccination and highlights the importance of efforts to increase vaccination coverage.
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COVID-19 has had high incidence at institutions of higher education (IHE) in the United States, but the transmission dynamics in these settings are not well understood. It remains unclear to what extent IHE-associated outbreaks have contributed to transmission in nearby communities. We implemented high-density prospective genomic surveillance to investigate these dynamics at the University of Michigan-Ann Arbor and the surrounding community during the Fall 2020 semester (August 16th -November 24th). We sequenced complete SARS-CoV-2 genomes from 1659 individuals, including 468 students, representing 20% of cases in students and 25% of total confirmed cases in Washtenaw County over the study interval. Phylogenetic analysis identified over 200 introductions into the student population, most of which were not related to other student cases. There were two prolonged transmission clusters among students that spanned across multiple on-campus residences. However, there were very few genetic descendants of student clusters among non-students during a subsequent November wave of infections in the community. We conclude that outbreaks at the University of Michigan did not significantly contribute to the rise in Washtenaw County COVID-19 incidence during November 2020. These results provide valuable insights into the distinct transmission dynamics of SARS-CoV-2 among IHE populations and surrounding communities.
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Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified a viral load threshold that minimizes false positives. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.
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We compared symptoms and characteristics of 4961 ambulatory patients with and without laboratory-confirmed SARS-CoV-2 infection. Findings indicate that clinical symptoms alone would be insufficient to distinguish between COVID-19 and other respiratory infections (e.g., influenza) and/or to evaluate the effects of preventive interventions (e.g., vaccinations).
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BackgroundSevere COVID-19 can manifest in rapid decompensation and respiratory failure with elevated inflammatory markers. This presentation is consistent with cytokine release syndrome in chimeric antigen receptor T cell therapy, for which IL-6 blockade is approved treatment. MethodsWe assessed effectiveness and safety of IL-6 blockade with tocilizumab in a single-center cohort of patients with COVID-19 requiring mechanical ventilation. The primary endpoint was survival probability post-intubation; secondary analyses included an ordinal illness severity scale integrating superinfections. Outcomes in patients who received tocilizumab compared to tocilizumab-untreated controls were evaluated using multivariable Cox regression with propensity score inverse probability weighting (IPTW). Findings154 patients were included, of whom 78 received tocilizumab and 76 did not. Median follow-up was 47 days (range 28-67). Baseline characteristics were similar between groups, although tocilizumab-treated patients were younger (mean 55 vs. 60 years), less likely to have chronic pulmonary disease (10% vs. 28%), and had lower D-dimer values at time of intubation (median 2.4 vs. 6.5 mg/dL). In IPTW-adjusted models, tocilizumab was associated with a 45% reduction in hazard of death [hazard ratio 0.55 (95% CI 0.33, 0.90)] and improved status on the ordinal outcome scale [odds ratio per 1-level increase: 0.59 (0.36, 0.95)]. Though tocilizumab was associated with an increased proportion of patients with superinfections (54% vs. 26%; p<0.001), there was no difference in 28-day case fatality rate among tocilizumab-treated patients with versus without superinfection [22% vs. 15%; p=0.42]. InterpretationIn this cohort of mechanically ventilated COVID-19 patients, tocilizumab was associated with a decreased likelihood of death despite higher superinfection occurrence. Randomized controlled trials are urgently needed to confirm these findings. KEY POINTSO_ST_ABSQuestionC_ST_ABSCan therapy with the IL-6 receptor antagonist tocilizumab improve outcomes in patients with severe COVID-19 illness requiring mechanical ventilation? FindingsIn this observational, controlled study of 154 patients, receipt of tocilizumab was associated with a 45% reduction in the hazard of death, despite twice the frequency of superinfection (54% vs 26%), both of which were statistically significant findings. MeaningTocilizumab therapy may improve survival in patients with COVID-19 illness requiring mechanical ventilation. These results can inform clinical practice pending the results of randomized clinical trials.
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BackgroundCommunity based studies of influenza and other respiratory viruses (e.g. SARS-COV-2) require laboratory confirmation of infection. During the current COVID-19 pandemic, social distancing guidelines require alternative data collection in order protect both research staff and participants. Home-collected respiratory specimens are less resource intensive, can be collected earlier after symptom onset, and provide a low-contact means of data collection. A prospective, multi-year, community-based cohort study is an ideal setting to examine the utility of home-collected specimens for identification of influenza. MethodsWe describe the feasibility and reliability of home-collected specimens for the detection of influenza. We collected data and specimens between October 2014 and June 2017 from the Household Influenza Vaccine Evaluation (HIVE) Study. Cohort participants were asked to collect a nasal swab at home upon onset of acute respiratory illness. Research staff also collected nose and throat swab specimens in the study clinic within 7 days of onset. We estimated agreement using Cohens kappa and calculated sensitivity and specificity of home-collected compared to staff-collected specimens. ResultsWe tested 336 paired staff- and home-collected respiratory specimens for influenza by RT-PCR; 150 staff-collected specimens were positive for influenza A/H3N2, 23 for influenza A/H1N1, 14 for influenza B/Victoria, and 31 for influenza B/Yamagata. We found moderate agreement between collection methods for influenza A/H3N2 (0.70) and B/Yamagata (0.69) and high agreement for influenza A/H1N1 (0.87) and B/Victoria (0.86). Sensitivity ranged from 78-86% for all influenza types and subtypes. Specificity was high for influenza A/H1N1 and both influenza B lineages with a range from 96-100%, and slightly lower for A/H3N2 infections (88%). ConclusionsCollection of nasal swab specimens at home is both feasible and reliable for identification of influenza virus infections.