Coronavirus Occurrence and Transmission Over 8 Years in the HIVE Cohort of Households in Michigan

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156082/1/jiaa161.pdfSEL

Home collection of nasal swabs for detection of influenza in the Household Influenza Vaccine Evaluation Study

BackgroundCommunity‐based studies of influenza and other respiratory viruses (eg, SARS‐CoV‐2) require laboratory confirmation of infection. During the current COVID‐19 pandemic, social distancing guidelines require alternative data collection in order to 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 Cohen’s 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% to 86% for all influenza types and subtypes. Specificity was high for influenza A/H1N1 and both influenza B lineages with a range from 96% to 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.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166444/1/irv12822_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/166444/2/irv12822.pd

Rapid transmission and tight bottlenecks constrain the evolution of highly transmissible SARS-CoV-2 variants

Here, by sequencing viruses from individuals in multiple households, Bendall et al. find that SARS-CoV-2 transmission bottleneck does not vary between individuals infected with pre-variant lineages and those infected with highly transmissible Alpha, Delta, or Omicron variants, suggesting these tight bottlenecks will limit the spread of new mutations

Genetic-Based Prediction of Disease Traits: Prediction is Very Difficult, Especially about the Future

Translation of results from genetic findings to inform medical practice is a highly anticipated goal of human genetics. The aim of this paper is to review and discuss the role of genetics in medically-relevant prediction. Germline genetics presages disease onset and therefore can contribute prognostic signals that augment laboratory tests and clinical features. As such, the impact of genetic-based predictive models on clinical decisions and therapy choice could be profound. However, given that (i) medical traits result from a complex interplay between genetic and environmental factors, (ii) the underlying genetic architectures for susceptibility to common diseases are not well-understood, and (iii) replicable susceptibility alleles, in combination, account for only a moderate amount of disease heritability, there are substantial challenges to constructing and implementing genetic risk prediction models with high utility. In spite of these challenges, concerted progress has continued in this area with an ongoing accumulation of studies that identify disease predisposing genotypes. Several statistical approaches with the aim of predicting disease have been published. Here we summarize the current state of disease susceptibility mapping and pharmacogenetics efforts for risk prediction, describe methods used to construct and evaluate genetic-based predictive models, and discuss applications

Respiratory syncytial virus hospitalization in middle-aged and older adults

BACKGROUND: The importance of Respiratory Syncytial Virus (RSV) is increasingly recognized in hospitalized adults, but mainly in those ≥ 65 years. OBJECTIVES: We sought to describe the epidemiology and clinical severity of RSV compared to influenza in hospitalized adults ≥18 years. STUDY DESIGN: Adults hospitalized with acute respiratory illnesses (ARI) of ≤10days duration were prospectively enrolled from two Michigan hospitals during two influenza seasons. Collected specimens were tested for RSV and influenza by real-time, reverse transcription polymerase chain reaction (RT-PCR). Viral load and subtype were determined for RSV-positive specimens. We evaluated factors associated with RSV and outcomes of infection using multivariable logistic regression. RSV-positive patients were separately compared to two reference groups: RSV-negative and influenza-negative, and influenza-positive patients. RESULTS: RSV was detected in 84 (7%) of 1259 hospitalized individuals (55 RSV-B, 29 RSV-A). The highest prevalence was found in 50-64year olds (40/460; 8.7%); 98% of RSV cases in this age group had at least one chronic comorbidity. RSV detection was associated with obesity (OR: 1.71 95% CI: 0.99-3.06, p=0.03). Individuals with RSV were admitted to the hospital later in their illness and had a higher median Charlson comborbidity index (3 vs 2 p\u3c0.001) compared to those with influenza. Clinical severity of RSV-associated hospitalizations was similar to influenza-associated hospitalizations. DISCUSSION: In this study we observed the highest frequency of RSV-associated hospitalizations among adult 50-64 years old; many of whom had chronic comorbidities. Our results suggest the potential benefit of including these individuals in future RSV vaccination strategies

Respiratory virus circulation during the first year of the COVID-19 pandemic in the Household Influenza Vaccine Evaluation (HIVE) cohort

BackgroundThe annual reappearance of respiratory viruses has been recognized for decades. COVID-19 mitigation measures taken during the pandemic were targeted at respiratory transmission and broadly impacted the burden of acute respiratory illnesses (ARIs).MethodsWe used the longitudinal Household Influenza Vaccine Evaluation (HIVE) cohort in southeast Michigan to characterize the circulation of respiratory viruses from March 1, 2020, to June 30, 2021, using RT-PCR of respiratory specimens collected at illness onset. Participants were surveyed twice during the study period, and SARS-CoV-2 antibodies were measured in serum by electrochemiluminescence immunoassay. Incidence rates of ARI reports and virus detections were compared between the study period and a preceding pre-pandemic period of similar duration.ResultsOverall, 437 participants reported a total of 772 ARIs; 42.6% had respiratory viruses detected. Rhinoviruses were the most frequent virus, 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. Seropositivity for SARS-CoV-2 was 5.3% in summer 2020 and increased to 11.3% in spring 2021. 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 a pre-pandemic comparison period (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. Rhinovirus and seasonal coronaviruses continued to circulate even when influenza and SARS-CoV-2 circulation was low.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/175944/1/irv13106_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/175944/2/irv13106.pd