Crisis response during the COVID-19 pandemic: Changes in social contact and social participation of older Americans.

OBJECTIVE: This study aimed to assess changes in social contact with family, friends and healthcare providers, as well as social participation in working, volunteering, religious services and other organized activities, among older adults during the COVID-19 pandemic while examining the role of pre-COVID sociodemographic characteristics or cognitive and physical limitations in changes in social contact and participation. METHODS: We conducted secondary data analyses in the National Health and Aging Trends Study (NHATS) COVID-19 questionnaire, collected in 2020 during a period of workplace closures and social distancing guidelines. We linked data to pre-COVID sociodemographic and medical information collected in 2019 before COVID interrupted social life. The frequency of participants' social contact and social participation prior to and during the COVID-19 pandemic, were compared using paired t-tests for summed scores. Multivariate linear regression was used to relate participants' socio-demographic, prior physical and cognitive performance with levels of social contact and participation and with changes reported during the COVID-19 pandemic. RESULTS: In total, results from 2,486 eligible participants revealed that COVID-19 was associated with decreased social contact among family and friends (change: -0.62; SE: 0.06; p<0.0001), and social participation among older adults (change: -0.58; SE: 0.02; p<0.0001). Pre-COVID characteristics including older age, lower educational attainment, poorer physical performance, and more chronic conditions were associated with lower social contact and social participation and with how older adults adapted their social lives during the COVID-19 pandemic. DISCUSSION: These results emphasize the importance of increasing digital inclusion for older adults in a major crisis.

A personalized pharmaco-epistatic network model of precision medicine.

Precision medicine, the utilization of targeted treatments to address an individual's disease, relies on knowledge about the genetic cause of that individual's drug response. Here, we present a functional graph (FunGraph) theory to chart comprehensive pharmacogenetic architecture for each and every patient. FunGraph is the combination of functional mapping - a dynamic model for genetic mapping and evolutionary game theory guiding interactive strategies. It coalesces all pharmacogenetic factors into multilayer and multiplex networks that fully capture bidirectional, signed and weighted epistasis. It can visualize and interrogate how epistasis moves in the cell and how this movement leads to patient- and context-specific genetic architecture in response to organismic physiology. We discuss the future implementation of FunGraph to achieve precision medicine.