COVID-19 prevention methods such as masking and social distancing also suppressed the circulation of common respiratory diseases, leaving young children lacking immunity to pathogens they otherwise would have been exposed to, a new multi-center clinical research study reveals. The investigators say their findings help explain the large post-pandemic rebound in these diseases and enable more accurate predictions for the future.

About The Study: In this modeling study, economic favorability of COVID-19 vaccination varied by age. Cost-effectiveness results for individuals in the 2 older age groups were favorable and generally robust to changes in parameter inputs, while results for the younger age group were sensitive to parameter input changes. As the evidence base for COVID-19 vaccination and burden of illness evolves, it may be important to continue to update and revise the economic evaluation of vaccination. The Advisory Committee on Immunization Practices considered these results in its decision to recommend vaccination with the 2023 to 2024 COVID-19 mRNA vaccines.

About The Study: Stratified analyses in this study revealed that prediabetes was significantly associated with mortality only among younger adults (ages 20-54), highlighting the importance of age-specific interventions. Lifestyle behaviors, limited health care access, and life stage challenges may contribute to the increased mortality risk in younger adults. Early-onset health problems in this group may also reflect stronger genetic predispositions, leading to more rapid disease progression and more severe health outcomes. These findings underscore the need for tailored diabetes prevention programs targeting young adults—such as flexible, virtual, and peer-led options—to increase accessibility and engagement. Routine screening and timely referrals to age-appropriate programs are essential.

The first paper from a multi-year clinical research study has been published in The Lancet Infectious Diseases: Dynamics of Endemic Virus Re-emergence in Children in the USA Following the COVID-19 Pandemic (2022-2023): A Longitudinal Immunoepidemiologic Surveillance Study and demonstrates how the approach can improve modeling to better predict future outbreaks.

The paper shares findings from a multicenter clinical research study, one of many studies that are part of the recently launched PREMISE (Pandemic Response Repository through Microbial and Immune Surveillance and Epidemiology) program, led by Dr. Daniel Douek at the National Institutes of Health’s (NIH) Vaccine Research Center (VRC). Data collected during the first year of the PREMISE study, 2022-2023, shows for the first time how non-pharmaceutical interventions such as masking and distancing targeted towards SARS-CoV-2 during the pandemic also decreased circulation rates of and population immunity to common respiratory pathogens in children. The study provides new evidence-based insight into what was driving the large post-pandemic rebound in these diseases and enables more accurate predictions for the future.

Large language models such as ChatGPT recognise widespread myths about the human brain better than many educators. However, if false assumptions are embedded into a lesson scenario, artificial intelligence (AI) does not reliably correct them. These were the findings of an international study that included psychologists from Martin Luther University Halle-Wittenberg (MLU). The researchers attribute this behaviour to the fundamental nature of AI models: they act as people pleasers. However, this problem can be solved by a simple trick. The study was published in the journal “Trends in Neuroscience and Education”.