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Background Overweight, obesity, and associated comorbidities are a pressing global issue among children of all ages, particularly among low-income populations. Rapid weight gain (RWG) in the first 6 months of infancy contributes to childhood obesity. Suboptimal sleep-wake patterns and gut microbiota (GM) have also been associated with childhood obesity, but little is known about their influences on early infant RWG. Sleep may alter the GM and infant metabolism, and ultimately impact obesity; however, data on the interaction between sleep-wake patterns and GM development on infant growth are scarce. In this study, we aim to investigate associations of infant sleep-wake patterns and GM development with RWG at 6 months and weight gain at 12 months. We also aim to evaluate whether temporal interactions exist between infant sleep-wake patterns and GM, and if these relations influence RWG. Methods The Snuggle Bug/ Acurrucadito study is an observational, longitudinal study investigating whether 24-h, actigraphy-assessed, sleep-wake patterns and GM development are associated with RWG among infants in their first year. Based on the Ecological Model of Growth, we propose a novel conceptual framework to incorporate sleep-wake patterns and the GM as metabolic contributors for RWG in the context of maternal-infant interactions, and familial and socio-physical environments. In total, 192 mother-infant pairs will be recruited, and sleep-wake patterns and GM development assessed at 3 and 8 weeks, and 3, 6, 9, and 12 months postpartum. Covariates including maternal and child characteristics, family and environmental factors, feeding practices and dietary intake of infants and mothers, and stool-derived metabolome and exfoliome data will be assessed. The study will apply machine learning techniques combined with logistic time-varying effect models to capture infant growth and aid in elucidating the dynamic associations between study variables and RWG. Discussion Repeated, valid, and objective assessment at clinically and developmentally meaningful intervals will provide robust measures of longitudinal sleep, GM, and growth. Project findings will provide evidence for future interventions to prevent RWG in infancy and subsequent obesity. The work also may spur the development of evidence-based guidelines to address modifiable factors that influence sleep-wake and GM development and prevent childhood obesity.

What is already known about this topic? COVID-19 vaccines have been recommended for children aged 6 months–5 years since June 2022; approximately one million doses were administered to persons in this age group during June–August 2022. What is added by this report? Local and systemic reactions after vaccination with either BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) COVID-19 vaccines were reported for children aged 6 months–4 years and 6 months–5 years, respectively, to v-safe and VAERS safety monitoring systems. Serious adverse events were rarely reported. What are the implications for public health practice? Initial vaccine safety data indicate that among young children, local and systemic reactions are expected after COVID-19 vaccination and serious adverse events are rare.

Information systems are used by most states to maintain registries of immunization data both for monitoring population-level adherence and for use in clinical practice and research. Direct data exchange between such systems and electronic health record systems presents an opportunity to improve the completeness and quality of information available. Our goals were to describe and compare the completeness of the Arizona State Immunization System, the electronic health record at a large community health provider in Arizona exchanging electronic data with the Arizona system, and personal immunization records in an effort to contribute to the discussion on the completeness of state-run immunization registries and data exchange with these registries. Immunization histories from these sources were collected and reviewed sequentially. Unique dates of vaccination administrations were counted for each patient and tagged on the basis of comparisons across sources. We quantified completeness by combining information from all 3 sources and comparing each source with the complete set. We determined that the state registry was 71.8% complete, the hospital electronic health record was 81.9% complete, and personal records were 87.8% complete. Of the 2017 unique vaccination administrations, 65% were present in all 3 sources, 24.6% in 2 of the 3 sources, and 10.4% in only 1 source. Only 11% of patients had records in complete agreement across the 3 sources. This study highlights issues related to data completeness, exchange, and reporting of immunization information to state registries and suggests that there is some degree of deficiency in completeness of immunization registries and other sources. This study indicates that there is a need to strengthen links between electronic data sources with immunization information and describes potential improvements in completeness that such efforts could provide, enabling providers to better rely on state immunization registries and to improve research utilization of immunization information systems.

On October 12, 2022, the Food and Drug Administration (FDA) issued Emergency Use Authorizations (EUAs) for bivalent (mRNA encoding the spike protein from the SARS-CoV-2 ancestral strain and BA.4/BA.5 Omicron variants) formulations of Pfizer-BioNTech and Moderna mRNA COVID-19 vaccines for use as a single booster dose ≥2 months after completion of primary series or monovalent booster vaccination for children aged 5-11 years (Pfizer-BioNTech) and 6-17 years (Moderna); on December 8, 2022, FDA amended the EUAs to include children aged ≥6 months (1,2). The Advisory Committee on Immunization Practices (ACIP) recommends that all persons aged ≥6 months receive an age-appropriate bivalent mRNA booster dose (3). The safety of bivalent mRNA booster doses among persons aged ≥12 years has previously been described (4). To characterize the safety of bivalent mRNA booster doses among children aged 5-11 years after receipt of bivalent Pfizer-BioNTech and Moderna booster doses, CDC reviewed adverse events and health impacts reported to v-safe,* a voluntary, smartphone-based U.S. safety surveillance system established by CDC to monitor adverse events after COVID-19 vaccination, and to the Vaccine Adverse Event Reporting System (VAERS), a U.S. passive vaccine safety surveillance system co-managed by CDC and FDA (5). During October 12-January 1, 2023, a total of 861,251 children aged 5-11 years received a bivalent Pfizer-BioNTech booster, and 92,108 children aged 6-11 years received a bivalent Moderna booster. Among 3,259 children aged 5-11 years registered in v-safe who received a bivalent booster dose, local (68.7%) and systemic reactions (49.5%) were commonly reported in the week after vaccination. Approximately 99.8% of reports to VAERS for children aged 5-11 years after bivalent booster vaccination were nonserious. There were no reports of myocarditis or death after bivalent booster vaccination. Eighty-four percent of VAERS reports were related to vaccination errors, 90.5% of which did not list an adverse health event. Local and systemic reactions reported after receipt of a bivalent booster dose are consistent with those reported after a monovalent booster dose; serious adverse events are rare. Vaccine providers should provide this information when counseling parents or guardians about bivalent booster vaccination. Preliminary safety findings from the first 11 weeks of bivalent booster vaccination among children aged 5-11 years are reassuring. Compared with the low risk of serious health effects after mRNA COVID-19 vaccination, the health effects of SARS-CoV-2 infection include death and serious long-term sequalae (6). ACIP recommends that all persons aged ≥6 months receive an age-appropriate bivalent mRNA booster dose ≥2 months after completion of a COVID-19 primary series or receipt of a monovalent booster dose. .

As of May 7, 2023, CDC's Advisory Committee on Immunization Practices (ACIP) recommends that all children aged 6 months-5 years receive at least 1 age-appropriate bivalent mRNA COVID-19 vaccine dose. Depending on their COVID-19 vaccination history and history of immunocompromise, these children might also need additional doses* (1-3). Initial vaccine safety findings after primary series vaccination among children aged 6 months-5 years showed that transient local and systemic reactions were common whereas serious adverse events were rare (4). To characterize the safety of a third mRNA COVID-19 vaccine dose among children aged 6 months-5 years, CDC reviewed adverse events and health surveys reported to v-safe, a voluntary smartphone-based U.S. safety surveillance system established by CDC to monitor health after COVID-19 vaccination (https://vsafe.cdc.gov/en/) and the Vaccine Adverse Event Reporting System (VAERS), a U.S. passive vaccine safety surveillance system co-managed by CDC and the Food and Drug Administration (FDA) (https://vaers.hhs.gov/) (5). During June 17, 2022-May 7, 2023, approximately 495,576 children aged 6 months-4 years received a third dose (monovalent or bivalent) of Pfizer-BioNTech vaccine and 63,919 children aged 6 months-5 years received a third dose of Moderna vaccine. A third mRNA COVID-19 vaccination was recorded for 2,969 children in v-safe; approximately 37.7% had no reported reactions, and among those for whom reactions were reported, most reactions were mild and transient. VAERS received 536 reports after a third dose of mRNA COVID-19 vaccine for children in these age groups; 98.5% of reports were nonserious and most (78.4%) were classified as a vaccination error. No new safety concerns were identified. Preliminary safety findings after a third dose of COVID-19 vaccine for children aged 6 months-5 years are similar to those after other doses. Health care providers can counsel parents and guardians of young children that most reactions reported after vaccination with Pfizer-BioNTech or Moderna vaccine were mild and transient and that serious adverse events are rare.

Methicillin resistant Staphylococcus aureus (MRSA) is currently a major cause of skin and soft tissue infections (SSTI) in the United States. Seasonal variation of MRSA infections in hospital settings has been widely observed. However, systematic time-series analysis of incidence data is desirable to understand the seasonality of community acquired (CA)-MRSA infections at the population level. In this paper, using data on monthly SSTI incidence in children aged 0-19 years and enrolled in Medicaid in Maricopa County, Arizona, from January 2005 to December 2008, we carried out time-series and nonlinear regression analysis to determine the periodicity, trend, and peak timing in SSTI incidence in children at different age: 0-4 years, 5-9 years, 10-14 years, and 15-19 years. We also assessed the temporal correlation between SSTI incidence and meteorological variables including average temperature and humidity. Our analysis revealed a strong annual seasonal pattern of SSTI incidence with peak occurring in early September. This pattern was consistent across age groups. Moreover, SSTIs followed a significantly increasing trend over the 4-year study period with annual incidence increasing from 3.36% to 5.55% in our pediatric population of approximately 290,000. We also found a significant correlation between the temporal variation in SSTI incidence and mean temperature and specific humidity. Our findings could have potential implications on prevention and control efforts against CA-MRSA.

Community associated methicillin-resistant Staphylococcus aureus (CA-MRSA) has become a major cause of skin and soft tissue infections (SSTIs) in the US. We developed an age-structured compartmental model to study the spread of CA-MRSA at the population level and assess the effect of control intervention strategies. We used Monte-Carlo Markov Chain (MCMC) techniques to parameterize our model using monthly time series data on SSTIs incidence in children (≤ 19 years) during January 2004 -December 2006 in Maricopa County, Arizona. Our model-based forecast for the period January 2007-December 2008 also provided a good fit to data. We also carried out an uncertainty and sensitivity analysis on the control reproduction number, Rc which we estimated at 1.3 (95% CI [1.2,1.4]) based on the model fit to data. Using our calibrated model, we evaluated the effect of typical intervention strategies namely reducing the contact rate of infected individuals owing to awareness of infection and decolonization strategies targeting symptomatic infected individuals on both [Formula: see text] and the long-term disease dynamics. We also evaluated the impact of hypothetical decolonization strategies targeting asymptomatic colonized individuals. We found that strategies focused on infected individuals were not capable of achieving disease control when implemented alone or in combination. In contrast, our results suggest that decolonization strategies targeting the pediatric population colonized with CA-MRSA have the potential of achieving disease elimination.

Competence-based medical education requires robust data to link competence with clinical experiences. The SARS-CoV-2 (COVID-19) pandemic abruptly altered the standard trajectory of clinical exposure in medical training programs. Residency program directors were tasked with identifying and addressing the resultant gaps in each trainee's experiences using existing tools. This study aims to demonstrate a feasible and efficient method to capture electronic health record (EHR) data that measure the volume and variety of pediatric resident clinical experiences from a continuity clinic; generate individual-, class-, and graduate-level benchmark data; and create a visualization for learners to quickly identify gaps in clinical experiences. This pilot was conducted in a large, urban pediatric residency program from 2016 to 2022. Through consensus, 5 pediatric faculty identified diagnostic groups that pediatric residents should see to be competent in outpatient pediatrics. Information technology consultants used International Classification of Diseases, Tenth Revision (ICD-10) codes corresponding with each diagnostic group to extract EHR patient encounter data as an indicator of exposure to the specific diagnosis. The frequency (volume) and diagnosis types (variety) seen by active residents (classes of 2020-2022) were compared with class and graduated resident (classes of 2016-2019) averages. These data were converted to percentages and translated to a radar chart visualization for residents to quickly compare their current clinical experiences with peers and graduates. Residents were surveyed on the use of these data and the visualization to identify training gaps. Patient encounter data about clinical experiences for 102 residents (N=52 graduates) were extracted. Active residents (n=50) received data reports with radar graphs biannually: 3 for the classes of 2020 and 2021 and 2 for the class of 2022. Radar charts distinctly demonstrated gaps in diagnoses exposure compared with classmates and graduates. Residents found the visualization useful in setting clinical and learning goals. This pilot describes an innovative method of capturing and presenting data about resident clinical experiences, compared with peer and graduate benchmarks, to identify learning gaps that may result from disruptions or modifications in medical training. This methodology can be aggregated across specialties and institutions and potentially inform competence-based medical education.

Community associated methicillin-resistant Staphylococcus aureus (CA-MRSA) has become a major cause of skin and soft tissue infections (SSTIs) in the US. We developed an age-structured compartmental model to study the spread of CA-MRSA at the population level and assess the effect of control intervention strategies. We used Monte-Carlo Markov Chain (MCMC) techniques to parameterize our model using monthly time series data on SSTIs incidence in children (≤19 years) during January 2004 -December 2006 in Maricopa County, Arizona. Our model-based forecast for the period January 2007-December 2008 also provided a good fit to data. We also carried out an uncertainty and sensitivity analysis on the control reproduction number, which we estimated at 1.3 (95% CI [1.2,1.4]) based on the model fit to data. Using our calibrated model, we evaluated the effect of typical intervention strategies namely reducing the contact rate of infected individuals owing to awareness of infection and decolonization strategies targeting symptomatic infected individuals on both and the long-term disease dynamics. We also evaluated the impact of hypothetical decolonization strategies targeting asymptomatic colonized individuals. We found that strategies focused on infected individuals were not capable of achieving disease control when implemented alone or in combination. In contrast, our results suggest that decolonization strategies targeting the pediatric population colonized with CA-MRSA have the potential of achieving disease elimination.