Allergic diseases and immunodeficiencies in children, lessons learnt from COVID-19 pandemic by 2022: A statement from the EAACI-section on pediatrics.

By the April 12, 2022, the COVID-19 pandemic had resulted in over half a billion people being infected worldwide. There have been 6.1 million deaths directly due to the infection, but the pandemic has had many more short- and long-term pervasive effects on the physical and mental health of the population. Allergic diseases are among the most prevalent noncommunicable chronic diseases in the pediatric population, and health-care professionals and researchers were seeking answers since the beginning of pandemic. Children are at lower risk of developing severe COVID-19 or dying from infection. Allergic diseases are not associated with a higher COVID-19 severity and mortality, apart from severe/poorly controlled asthma. The pandemic disrupted routine health care, but many mitigation strategies, including but not limited to telemedicine, were successfully implemented to continue delivery of high-standard care. Although children faced a multitude of pandemic-related issues, allergic conditions were effectively treated remotely while reduction in air pollution and lack of contact with outdoor allergens resulted in improvement, particularly respiratory allergies. There is no evidence to recommend substantial changes to usual management modalities of allergic conditions in children, including allergen immunotherapy and use of biologicals. Allergic children are not at greater risk of multisystem inflammatory syndrome development, but some associations with Long COVID were reported, although the data are limited, and further research is needed. This statement of the EAACI Section on Pediatrics provides recommendations based on the lessons learnt from the pandemic, as available evidence.

A review of applications of the Bayes factor in psychological research.

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The article is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines. (PsycInfo Database Record (c) 2023 APA, all rights reserved).