Background And Objectives: With the goal of slowing down the spread of the SARS-CoV-2 virus, restrictions to physical contacts have been taken in many countries. We examine to what extent intergenerational and other types of nonphysical contacts have reduced the risk of increased perceived depressive feelings during the lockdown for people aged 50+.
Research Design And Methods: We implemented an online panel survey based on quota sampling in France, Italy, and Spain in April 2020, about 1 month after the start of the lockdown. Our analyses are based on logistic regression models and use post-stratification weights.
Results: About 50% of individuals aged 50+ felt sad or depressed more often than usual during the lockdown in the 3 considered countries. Older people who increased or maintained unchanged nonphysical contacts with noncoresident individuals during the lockdown were at a lower risk of increased perceived depressive feelings compared to those who experienced a reduction in nonphysical contacts. The beneficial effect of nonphysical contacts was stronger for intergenerational relationships. The effects were similar by gender and stronger among individuals aged 70+, living in Spain and not living alone before the start of the lockdown.
Discussion And Implications: In the next phases of the COVID-19 pandemic, or during any future similar pandemic, policy makers may implement measures that balance the need to reduce the spread of the virus with the necessity of allowing for limited physical contacts. Social contacts at a distance may be encouraged as a means to keep social closeness, while being physically distant.
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http://dx.doi.org/10.1093/geront/gnaa144 | DOI Listing |
Proc Natl Acad Sci U S A
November 2024
Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139.
Protein language models (pLMs) have emerged as potent tools for predicting and designing protein structure and function, and the degree to which these models fundamentally understand the inherent biophysics of protein structure stands as an open question. Motivated by a finding that pLM-based structure predictors erroneously predict nonphysical structures for protein isoforms, we investigated the nature of sequence context needed for contact predictions in the pLM Evolutionary Scale Modeling (ESM-2). We demonstrate by use of a "categorical Jacobian" calculation that ESM-2 stores statistics of coevolving residues, analogously to simpler modeling approaches like Markov Random Fields and Multivariate Gaussian models.
View Article and Find Full Text PDFNanoscale
October 2024
Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA.
PLoS One
June 2024
Peter O'Donnell Jr. School of Public Health at UT Southwestern Medical Center, Dallas, Texas, United States of America.
Background: Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission.
View Article and Find Full Text PDFFront Microbiol
February 2024
State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Background: Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!