Maternal varicella antibodies in children aged less than one year: Assessment of antibody decay.

OBJECTIVES: To investigate maternal antibody levels to varicella in infants <12 months of age in Ontario, Canada. STUDY DESIGN: In this study, we included specimens from infants <12 months of age, born at ≥37 weeks gestational age, who had sera collected at The Hospital for Sick Children (Toronto, Canada) between 2014-2016. We tested sera using a glycoprotein-based enzyme-linked immunosorbent assay (gpELISA). We measured varicella susceptibility (antibody concentration <150mIU/mL) and mean varicella antibody concentration, and assessed the probability of susceptibility and concentration between one and 11 months of age using multivariable logistic regression and Poisson regression. RESULTS: We found that 32% of 196 included specimens represented infants susceptible to varicella at one month of age, increasing to nearly 80% at three months of age. At six months of age, all infants were susceptible to varicella and the predicted mean varicella antibody concentration declined to 62 mIU/mL (95% confidence interval 40, 84), well below the threshold of protection. CONCLUSIONS: We found that varicella maternal antibody levels wane rapidly in infants, leaving most infants susceptible by four months of age. Our findings have implications for the timing of first dose of varicella-containing vaccine, infection control measures, and infant post-exposure prophylaxis recommendations.

Assessment of population infection with SARS-CoV-2 in Ontario, Canada, March to June 2020.

BackgroundSerosurveys for SARS-CoV-2 aim to estimate the proportion of the population that has been infected.AimThis observational study assesses the seroprevalence of SARS-CoV-2 antibodies in Ontario, Canada during the first pandemic wave.MethodsUsing an orthogonal approach, we tested 8,902 residual specimens from the Public Health Ontario laboratory over three time periods during March-June 2020 and stratified results by age group, sex and region. We adjusted for antibody test sensitivity/specificity and compared with reported PCR-confirmed COVID-19 cases.ResultsAdjusted seroprevalence was 0.5% (95% confidence interval (CI): 0.1-1.5) from 27 March-30 April, 1.5% (95% CI: 0.7-2.2) from 26-31 May, and 1.1% (95% CI: 0.8-1.3) from 5-30 June 2020. Adjusted estimates were highest in individuals aged ≥ 60 years in March-April (1.3%; 95% CI: 0.2-4.6), in those aged 20-59 years in May (2.1%; 95% CI: 0.8-3.4) and in those aged ≥ 60 years in June (1.6%; 95% CI: 1.1-2.1). Regional seroprevalence varied, and was highest for Toronto in March-April (0.9%; 95% CI: 0.1-3.1), for Toronto in May (3.2%; 95% CI: 1.0-5.3) and for Toronto (1.5%; 95% CI: 0.9-2.1) and Central East in June (1.5%; 95% CI: 1.0-2.0). We estimate that COVID-19 cases detected by PCR in Ontario underestimated SARS-CoV-2 infections by a factor of 4.9.ConclusionsOur results indicate low population seroprevalence in Ontario, suggesting that public health measures were effective at limiting the spread of SARS-CoV-2 during the first pandemic wave.

Predictors and variability of antibiotic prescribing amongst family physicians.

BACKGROUND: Rising rates of antimicrobial resistance are driven by overuse of antibiotics. Characterizing physician antibiotic prescribing variability can inform interventions to optimize antibiotic use. OBJECTIVES: To describe predictors of overall antibiotic prescribing as well as the inter-physician variability in antibiotic prescribing amongst family physicians. METHODS: We conducted a 5 year cohort study of antibiotic prescribing rates by family physicians in Ontario, Canada using a repository of electronic medical records. Using multilevel logistic regression models fitted with random intercepts for physicians, we evaluated the association of patient-, physician- and clinic-level characteristics with antibiotic prescribing rates. RESULTS: We included 3956921 physician-patient encounters, 322129 unique patients and 313 physicians from 41 family medicine clinics. Physicians prescribed a median of 54 (interdecile range 28-95) antibiotics per 1000 encounters. Female children aged 3-5 years were most likely to receive antibiotics compared with men ≥65 years (OR 4.01, 95% CI 3.89-4.13). The only significant physician-level predictor was median daily patient visits of ≥20 compared with <10 (OR 1.28, 95% CI 1.06-1.55). The median ORs without and with patient characteristics were 1.68 and 1.69, respectively. Thus, the odds of receiving an antibiotic varied by 1.7-fold for the same patient simply by virtue of encountering two different physicians. CONCLUSIONS: We observed substantial inter-physician variability in antibiotic prescribing that could not be explained by sociodemographic and clinical patient differences, suggesting that risk adjustment of antibiotic prescribing practices may not be required for audit and feedback of family physicians working in similar practice settings.

Comparing prescribing and dispensing databases to study antibiotic use: a validation study of the Electronic Medical Record Administrative data Linked Database (EMRALD).

BACKGROUND: Monitoring and studying community antibiotic use is a critical component in combating rising antimicrobial resistance. OBJECTIVES: To validate an electronic medical record dataset containing antibiotic prescriptions and to quantify some important differences between prescribing and dispensing databases. METHODS: We evaluated antibiotics prescribed and dispensed to patients ≥65 years of age during 2011-15. We compared the EMRALD prescribing database with the validated Ontario Drug Benefit (ODB) dispensing database. Using ODB as the gold standard and limiting to EMRALD physicians, we calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) with 95% CIs. We also compared the relative change in antibiotic use prescribed by all physicians to this population over time between the databases using Poisson regression models. RESULTS: In this population, 74% of all antibiotics dispensed were from non-EMRALD physicians. Trends in use were discordant over time. When we limited ODB to EMRALD prescribers only to assess the validity of EMRALD data, we observed good sensitivity and excellent specificity for correctly identifying antibiotics at 85% (95% CI 84%-85%) and 98% (95% CI 98%-98%), respectively. The PPV was 78% (95% CI 78%-78%) and the NPV was 99% (95% CI 99%-99%). All performance measures were higher among the highest prescribing physicians. CONCLUSIONS: We demonstrated EMRALD is well suited for studying antibiotic prescribing by EMRALD physicians. However, due to the frequency with which patients receive antibiotic prescriptions from their non-primary care physicians, we caution against the use of non-population-based prescribing databases to infer antibiotic use rates or trends over time.

Influence of an independent quarterly audit on publicly reported vancomycin-resistant enterocococi bacteremia data in Ontario, Canada.

BACKGROUND: All Ontario hospitals are mandated to self-report vancomycin-resistant enterocococi (VRE) bacteremias to Ontario's Ministry of Health and Long-term Care for public reporting purposes. Independent quarterly audits of publicly reported VRE bacteremias between September 2013 and June 2015 were carried out by Public Health Ontario. VRE bacteremia case-reporting errors between January 2009 and August 2013 were identified by a single retrospective audit. METHODS: Employing a quasiexperimental pre-post study design, the relative risk of VRE bacteremia reporting errors before and after quarterly audits were modeled using Poisson regression adjusting for hospital type, case counts reported to the Ministry of Health and Long-term Care, and autocorrelation via generalized estimating equation. RESULTS: Overall, 24.5% (126 out of 514) of VRE bacteremias were reported in error; 114 out of 367 (31%) VRE bacteremias reported before quarterly audits and 12 out of 147 (8.1%) reported after audits were found to be incorrect. In adjusted analysis, quarterly audits of VRE bacteremias were associated with significant reductions in reporting errors when compared with before quarterly auditing (relative risk, 0.17; 95% confidence interval, 0.05-0.63). Risk of reporting errors among community hospitals were greater than acute teaching hospitals of the region (relative risk, 4.39; 95% CI, 3.07-5.70). CONCLUSIONS: This study found independent quarterly audits of publicly reported VRE bacteremias to be associated with significant reductions in reporting errors. Public reporting systems should consider adopting routine data audits and hospital-targeted training to improve data accuracy.

Excess Length of Stay Attributable to Clostridium difficile Infection (CDI) in the Acute Care Setting: A Multistate Model.

BACKGROUND: Standard estimates of the impact of Clostridium difficile infections (CDI) on inpatient lengths of stay (LOS) may overstate inpatient care costs attributable to CDI. In this study, we used multistate modeling (MSM) of CDI timing to reduce bias in estimates of excess LOS. METHODS: A retrospective cohort study of all hospitalizations at any of 120 acute care facilities within the US Department of Veterans Affairs (VA) between 2005 and 2012 was conducted. We estimated the excess LOS attributable to CDI using an MSM to address time-dependent bias. Bootstrapping was used to generate 95% confidence intervals (CI). These estimates were compared to unadjusted differences in mean LOS for hospitalizations with and without CDI. RESULTS: During the study period, there were 3.96 million hospitalizations and 43,540 CDIs. A comparison of unadjusted means suggested an excess LOS of 14.0 days (19.4 vs 5.4 days). In contrast, the MSM estimated an attributable LOS of only 2.27 days (95% CI, 2.14-2.40). The excess LOS for mild-to-moderate CDI was 0.75 days (95% CI, 0.59-0.89), and for severe CDI, it was 4.11 days (95% CI, 3.90-4.32). Substantial variation across the Veteran Integrated Services Networks (VISN) was observed. CONCLUSIONS: CDI significantly contributes to LOS, but the magnitude of its estimated impact is smaller when methods are used that account for the time-varying nature of infection. The greatest impact on LOS occurred among patients with severe CDI. Significant geographic variability was observed. MSM is a useful tool for obtaining more accurate estimates of the inpatient care costs of CDI.