Prioritization of COVID-19 risk factors in July 2020 and February 2021 in the UK

Tangirala, Sivateja; Tierney, Braden T.; Patel, Chirag

doi:10.1038/s43856-023-00271-3

Cited by 2 publications

References 41 publications

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The Role of WeChat in Supporting Elderly Connectivity During COVID-19 Lockdown in Guangzhou

Zhao

2024

SHS Web of Conf.

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This research investigates the motivations and impacts of WeChat usage among older adults in Guangzhou during the COVID-19 pandemic lockdown. Through qualitative interviews, this study explores how older adults in Guangzhou emotionally experience WeChat use during the lockdown. Findings indicate that WeChat played a vital role during the pandemic, facilitating emotional connections, daily life needs, information access, and positive psychological development among older adults. It fostered socialization, emotional support, and resilience, challenging conventional notions of elderly social media usage and highlighting diverse technological habits. Theoretical implications emphasize WeChat’s multi-functionality and the varied ways older individuals employ it. Practical implications stress the importance of social media in enhancing social participation and quality of life for older adults, especially in combating loneliness. WeChat’s utility during emergencies, like epidemics, is underscored. Addressing the digital divide and ensuring equitable digital access are crucial to preventing older individuals’ marginalization in the digital age. The study acknowledges limitations, including a small sample size and focus on a specific urban area. Future research directions involve expanding the sample, employing quantitative methods, enhancing sample representativeness, and examining diverse regions and demographics. Ongoing studies can capture evolving usage patterns and experiences of older adults in a changing technological and societal landscape.

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The Role of WeChat in Supporting Elderly Connectivity During COVID-19 Lockdown in Guangzhou

Zhao

2024

SHS Web of Conf.

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Identifying direct risk factors in UK Biobank with simultaneous Bayesian-frequentist model-averaged hypothesis testing using Doublethink

Arning,

Fryer,

Wilson

2024

Preprint

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Big data approaches to discovering non-genetic risk factors have lagged behind genome-wide association studies that routinely uncover novel genetic risk factors for diverse diseases. Instead, epidemiology typically focuses on candidate risk factors. Since modern biobanks contain thousands of potential risk factors, candidate approaches may introduce bias, inadequately control for multiple testing, and miss important signals. Bayesian model averaging offers a solution, but classical statistics predominates, perhaps because of concern that the prior unduly influences results. Here we show that simultaneous Bayesian and frequentist discovery of direct risk factors is possible via a model-averaged hypothesis testing approach for large samples called ‘Doublethink’. Doublethink produces interchangeable posterior odds andp-values that control the false discovery rate (FDR) and familywise error rate (FWER). We implement the Doublethink approach in R and apply it to discover direct risk factors for COVID-19 hospitalization in 2020 among 1,912 variables in UK Biobank. We find nine exposome-wide significant variables at 9% FDR and 0.05% FWER. These include several commonly reported risk factors (e.g. age, sex, obesity) but exclude others (e.g. diabetes, cardiovascular disease, hypertension) which might be mediated through variables measuring general comorbidity (e.g. numbers of medications). We identify significant direct effects among infrequently reported risk factors (psychiatric disorders, infection, dementia and aging), and show how testing groups of correlated variables is a useful alternative to pre-analysis variable selection. We discuss the potential for impact and limitations of joint Bayesian-frequentist inference, and the mutual insights afforded into the long-standing differences on statistical approaches to scientific discovery.

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Prioritization of COVID-19 risk factors in July 2020 and February 2021 in the UK

Cited by 2 publications

References 41 publications

The Role of WeChat in Supporting Elderly Connectivity During COVID-19 Lockdown in Guangzhou

The Role of WeChat in Supporting Elderly Connectivity During COVID-19 Lockdown in Guangzhou

Identifying direct risk factors in UK Biobank with simultaneous Bayesian-frequentist model-averaged hypothesis testing using Doublethink

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