Background As part of the Household Influenza Vaccine Evaluation (HIVE) study, acute respiratory infections (ARI) have been identified in children and adults from 2010 to 2018. Methods Annually, 890 to 1441 individuals were followed and contacted weekly to report ARIs. Specimens collected during illness were tested for human coronaviruses (HCoV) types OC43, 229E, HKU1, and NL63. Results In total, 993 HCoV infections were identified during the 8 years, with OC43 most commonly seen and 229E the least. HCoVs were detected in a limited time period, between December and April/May and peaked in January/February. Highest infection frequency was in children <5 years (18 per 100 person-years), with little variation in older age groups (range, 7 to 11 per 100 person-years). Overall, 9% of adult cases and 20% of cases in children were associated with medical consultation. Of the 993 infections, 260 were acquired from an infected household contact. The serial interval between index and household-acquired cases ranged from 3.2 to 3.6 days and the secondary infection risk ranged from 7.2% to 12.6% by type. Conclusions Coronaviruses are sharply seasonal. They appear, based on serial interval and secondary infection risk, to have similar transmission potential to influenza A(H3N2) in the same population.

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 ≤10 days 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 50-64 year 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 < 0.001) 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.

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.