Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

The implementation of mandatory influenza vaccination policies among healthcare personnel (HCP) is controversial. Thus, we examined the affect of mandatory influenza vaccination policies among HCP working in outpatient settings.

Four Veterans’ Affairs (VA) health systems and three non-VA medical centers.

We analyzed rates of influenza and other viral causes of respiratory infections among HCP working in outpatient sites at 4 VA health systems without mandatory influenza vaccination policies and 3 non-VA health systems with mandatory influenza vaccination policies.

Influenza vaccination was associated with a decreased risk of influenza (odds ratio, 0.17; 95% confidence interval [CI], 0.13–0.22) but an increased risk of other respiratory viral infections (incidence rate ratio, 1.26; 95% CI, 1.02–1.57).

Our fitted regression models suggest that if influenza vaccination rates in clinics where vaccination was not mandated had equalled those where vaccine was mandated, HCP influenza infections would have been reduced by 52.1% (95% CI, 51.3%–53.0%). These observations, their possible causes, and additional strategies to reduce influenza and other viral respiratory illnesses among HCP working in ambulatory clinics warrant further investigation.

To determine the effect of mandatory and nonmandatory influenza vaccination policies on vaccination rates and symptomatic absenteeism among healthcare personnel (HCP).

Retrospective observational cohort study.

This study took place at 3 university medical centers with mandatory influenza vaccination policies and 4 Veterans Affairs (VA) healthcare systems with nonmandatory influenza vaccination policies.

The study included 2,304 outpatient HCP at mandatory vaccination sites and 1,759 outpatient HCP at nonmandatory vaccination sites.

To determine the incidence and duration of absenteeism in outpatient settings, HCP participating in the Respiratory Protection Effectiveness Clinical Trial at both mandatory and nonmandatory vaccination sites over 3 viral respiratory illness (VRI) seasons (2012–2015) reported their influenza vaccination status and symptomatic days absent from work weekly throughout a 12-week period during the peak VRI season each year. The adjusted effects of vaccination and other modulating factors on absenteeism rates were estimated using multivariable regression models.

The proportion of participants who received influenza vaccination was lower each year at nonmandatory than at mandatory vaccination sites (odds ratio [OR], 0.09; 95% confidence interval [CI], 0.07–0.11). Among HCP who reported at least 1 sick day, vaccinated HCP had lower symptomatic days absent compared to unvaccinated HCP (OR for 2012–2013 and 2013–2014, 0.82; 95% CI, 0.72–0.93; OR for 2014–2015, 0.81; 95% CI, 0.69–0.95).

These data suggest that mandatory HCP influenza vaccination policies increase influenza vaccination rates and that HCP symptomatic absenteeism diminishes as rates of influenza vaccination increase. These findings should be considered in formulating HCP influenza vaccination policies.

Infect Control Hosp Epidemiol 2018;39:452–461

Show how detailed incubation period estimates can be used to identify and investigate potential healthcare-associated infections and dangerous diseases.

We used the incubation period of 9 respiratory viruses to derive decision rules for distinguishing between community- and hospital-acquired infection. We developed a method, implemented in a simple spreadsheet, that can be used to investigate the exposure history of an individual patient and more specifically to identify the probable time and location of infection. Illustrative examples are used to explain and evaluate this technique.

If the risks of hospital and community infection are equal, 95% of patients who develop symptoms of adenovirus infection within 5 days of hospital admission will have been infected in the community, as will 95% of patients who develop symptoms within 3 days for human-coronavirus infection, 2.5 days for severe acute respiratory syndrome, 1 day for influenza A, 0.5 day for influenza B, 12 days for measles, 2 days for parainfluenza, 4 days for respiratory syncytial virus infection, and 1.5 days for rhinovirus infection. Sources of infection suggested by analysis of the symptom onset times of individual patients are consistent with those from detailed investigations.

This work shows how a detailed understanding of the incubation period can be an effective tool for identifying the source of infection, ultimately ensuring patient safety.