Meningococcal disease in North America: Updates from the Global Meningococcal Initiative.

This review summarizes the recent Global Meningococcal Initiative (GMI) regional meeting, which explored meningococcal disease in North America. Invasive meningococcal disease (IMD) cases are documented through both passive and active surveillance networks. IMD appears to be decreasing in many areas, such as the Dominican Republic (2016: 18 cases; 2021: 2 cases) and Panama (2008: 1 case/100,000; 2021: <0.1 cases/100,000); however, there is notable regional and temporal variation. Outbreaks persist in at-risk subpopulations, such as people experiencing homelessness in the US and migrants in Mexico. The recent emergence of ß-lactamase-positive and ciprofloxacin-resistant meningococci in the US is a major concern. While vaccination practices vary across North America, vaccine uptake remains relatively high. Monovalent and multivalent conjugate vaccines (which many countries in North America primarily use) can provide herd protection. However, there is no evidence that group B vaccines reduce meningococcal carriage. The coronavirus pandemic illustrates that following public health crises, enhanced surveillance of disease epidemiology and catch-up vaccine schedules is key. Whole genome sequencing is a key epidemiological tool for identifying IMD strain emergence and the evaluation of vaccine strain coverage. The Global Roadmap on Defeating Meningitis by 2030 remains a focus of the GMI.

Risk factors for severe PCR-positive SARS-CoV-2 infection in hospitalised children

Objective To identify risk factors for severe disease in children hospitalised for SARS-CoV-2 infection. Design Multicentre retrospective cohort study. Setting 18 hospitals in Canada, Iran and Costa Rica from 1 February 2020 to 31 May 2021. Patients Children<18 years of age hospitalised for symptomatic PCR-positive SARS-CoV-2 infection, including PCR-positive multisystem inflammatory syndrome in children (MIS-C). Main outcome measure Severity on the WHO COVID-19 Clinical Progression Scale was used for ordinal logistic regression analyses. Results We identified 403 hospitalisations. Median age was 3.78 years (IQR 0.53–10.77). At least one comorbidity was present in 46.4% (187/403) and multiple comorbidities in 18.6% (75/403). Eighty-one children (20.1%) met WHO criteria for PCR-positive MIS-C. Progression to WHO clinical scale score ≥6 occurred in 25.3% (102/403). In multivariable ordinal logistic regression analyses adjusted for age, chest imaging findings, laboratory-confirmed bacterial and/or viral coinfection, and MIS-C diagnosis, presence of a single (adjusted OR (aOR) 1.90, 95% CI 1.13 to 3.20) or multiple chronic comorbidities (aOR 2.12, 95% CI 1.19 to 3.79), obesity (aOR 3.42, 95% CI 1.76 to 6.66) and chromosomal disorders (aOR 4.47, 95% CI 1.25 to 16.01) were independent risk factors for severity. Age was not an independent risk factor, but different age-specific comorbidities were associated with more severe disease in age-stratified adjusted analyses: cardiac (aOR 2.90, 95% CI 1.11 to 7.56) and non-asthma pulmonary disorders (aOR 3.07, 95% CI 1.26 to 7.49) in children<12 years old and obesity (aOR 3.69, 1.45–9.40) in adolescents≥12 years old. Among infants<1 year old, neurological (aOR 10.72, 95% CI 1.01 to 113.35) and cardiac disorders (aOR 10.13, 95% CI 1.69 to 60.54) were independent predictors of severe disease. Conclusion We identified risk factors for disease severity among children hospitalised for PCR-positive SARS-CoV-2 infection. Comorbidities predisposing children to more severe disease may vary by age. These findings can potentially guide vaccination programmes and treatment approaches in children.

COVID-19 pandemic impact on childhood vaccination coverage in Quebec, Canada.

Response measures to mitigate the coronavirus disease 2019 pandemic impacted access to routine vaccination services. We evaluate the impact of the pandemic on routine infant vaccination uptake by comparing vaccination coverage, vaccine delays and doses administered in 2019 and 2020, in Quebec, Canada. Using a population-based vaccination registry, we compared vaccination coverage at 3, 5, 13 and 19 months of age between 2019 and 2020 cohorts each month from January to November. For vaccine delays, we measured the cumulative proportion vaccinated in each targeted cohort monthly. We also compared the measles-containing vaccines administered before 24 months of age between the same period in 2019 and 2020. A decline in vaccination coverage and children vaccinated on time was observed in all cohorts during the first months of the pandemic. The greatest impact was observed for the 18-month vaccination visit with a difference in vaccination coverage between both cohorts of 30.9% in May. Measles-containing doses administered during the first months of the pandemic were lower in 2020 compared with 2019: -21.1% in March (95%CI-21.6;-20.4), and -39.2% in April (95%CI-40.0;-38.2). After May, the coverage increased for all cohorts to reach pre-pandemic levels after a few months for most target ages. Routine childhood vaccinations were affected during the first months of the pandemic, but catch-up occurred thereafter and vaccination coverage in affected cohorts were very close to levels of 2019 after a few months of follow-up. Real-time monitoring of childhood vaccination is essential but also for other vaccination programs, severely affected by the pandemic.

Seasonality of Respiratory Viruses at Northern Latitudes.

Importance: Every year, respiratory viruses exact a heavy burden on Canadian hospitals during winter months. Generalizable seasonal patterns of respiratory virus transmission may estimate the evolution of SARS-CoV-2 or other emerging pathogens. Objective: To describe the annual and biennial variation in respiratory virus seasonality in a northern climate. Design, Setting, and Participants: This cohort study is an epidemiological assessment using population-based surveillance of patients with medically attended respiratory tract infection from 2005 through 2017 in Alberta, Canada. Incident cases of respiratory virus infection and infant respiratory syncytial virus (RSV) hospitalizations in Alberta were extracted from the Data Integration for Alberta Laboratories platform and Alberta Health Services Discharge Abstract Database, respectively. A deterministic susceptible-infected-recovered-susceptible mathematical model with seasonal forcing function was fitted to the data for each virus. The possible future seasonal course of SARS-CoV-2 in northern latitudes was modeled on the basis of these observations. The analysis was conducted between December 15, 2020, and February 10, 2021. Exposures: Seasonal respiratory pathogens. Main Outcomes and Measures: Incidence (temporal pattern) of respiratory virus infections and RSV hospitalizations. Results: A total of 37 719 incident infections with RSV, human metapneumovirus, or human coronaviruses 229E, NL63, OC43, or HKU1 among 35 375 patients (18 069 [51.1%] male; median [interquartile range], 1.29 [0.42-12.2] years) were documented. A susceptible-infected-recovered-susceptible model mirrored the epidemiological data, including a striking biennial variation with alternating severe and mild winter peaks. Qualitative description of the model and numerical simulations showed that strong seasonal contact rate and temporary immunity lasting 6 to 12 months were sufficient to explain biennial seasonality in these various respiratory viruses. The seasonality of 10 212 hospitalizations among children younger than 5 years with RSV was also explored. The median (interquartile range) rate of hospitalizations per 1000 live births was 18.6 (17.6-19.9) and 11.0 (10.4-11.7) in alternating even (severe) and odd (less-severe) seasons, respectively (P = .001). The hazard of admission was higher for children born in severe (even) seasons compared with those born in less-severe (odd) seasons (hazard ratio, 1.68; 95% CI, 1.61-1.75; P < .001). Conclusions and Relevance: In this modeling study of respiratory viruses in Alberta, Canada, the seasonality followed a pattern estimated by simple mathematical models, which may be informative for anticipating future waves of pandemic SARS-CoV-2.