A Bayesian policy learning model of COVID-19 non-pharmaceutical interventions

This article examines the impact of non-pharmaceutical interventions on the initial exponential growth of the infected population and the final exponential decay of the infected population. We employ a Bayesian dynamic model to test whether there is learning, a random walk pattern, or another type of learning with evolving epidemiological data over time across 168 countries and 41,706 country-date observations. Although we show that Bayesian learning is not taking place, most policy measures appear to assert some effect. In particular, we show that economic policy variables are of importance for the main epidemiological parameters derived from the policy learning model. In an empirical second-stage application, we further investigate the underlying dynamics between the epidemiological parameters and household debt repayments, a key economic variable, in the UK. Results show no Bayesian learning, although a higher transmission rate would increase household debt repayments, while the recovery rate would have a negative impact. Therefore, suboptimal learning is taking place.

Implementation of a Workflow for COVID-19 Monoclonal Antibody Infusions at a Veterans Affairs Medical Center

Background. In the setting of the global pandemic due to COVID-19, high-risk patients with mild to moderate disease were identified as a group who would benefit from COVID-19 monoclonal antibody (mAB) treatment to mitigate progression to severe disease or hospitalization. The U.S. Food and Drug Administration (FDA), under Emergency Use Authorizations (EUA) approved multiple COVID-19 mAB therapies with specific criteria for eligibility of candidates, documentation of discussion with patients, and reporting of all errors and serious adverse events. Methods. A cross discipline working group implemented a mAB clinic at complexity level 1a VA Medical Center in metropolitan Washington, D.C. through collaboration of personnel committed to patient care. The team successfully persuaded hospital leadership to provide space and leveraged technologies for rapid communication and dissemination of education. A stewardship driven medical center wide surveillance system rapidly identified outpatients for screening;primary care and ED providers were engaged through various electronic methods of education, including email, web-based team communication, intranet webpages and other electronic modalities. Within the EMR, an order panel was implemented to assure that the key requirements of the EUA were met and the provider was guided to the appropriate mAB, nursing, and PRN rescue medication orders. Results. Of over 17,000 COVID-PCR tests were performed at our medical center, 198 outpatients were screened and 16 received COVID-19 mAB infusions between January 2, 2021 to May 31, 2021. One patient experienced a reaction requiring the infusion to be stopped and supportive medications to be administered;there were no long-term sequalae reported as a result of this event. Conclusion. A multidisciplinary collaboration is well suited to implement innovative processes and policies for novel therapies in the middle of a pandemic. An agile workflow, regular communications between members of the workgroup, and commitment of institutional leadership helped facilitate the changes necessary to provide our patients the opportunity to receive potentially life-saving therapies.

Everybody hurts: Self-employment, financial concerns, mental distress, and well-being during COVID-19

Adopting an abductive approach, in this paper we use two studies to examine the relationships between financial worries and well-being amongst the self-employed during the time of the COVID-19 pandemic. In Study 1 of 4806 participants from the Understanding Society's COVID-19 survey of the UK population, we find that financial worries were associated with higher mental distress for self-employed when facing reduced work hours. In Study 2, in a sample of 1794 participants from the six-country COVID study, we find that higher than expected fall in income mediates the association between self-employment and happiness. The findings have implications for research regarding financial worries, distress, and well-being of the self-employed. © 2021

The impact of financial insecurity on the self-employed's short-term psychological distress: Evidence from the COVID-19 pandemic

The earnings of the self-employed are relatively low and volatile, a risk that exacerbated during the recent COVID-19 pandemic. Using three two-weeks-apart waves of data from the Understanding America Study, we show that relative to wage workers, the self-employed experience greater psychological distress through self-reported financial insecurity (the chance of running out of money). Using additional cross-sectional data from the COVID-19 Household Impact Survey, we show that the self-reported chance of job loss disproportionally impacts the psychological distress of the self-employed. Together, these results underscore that the economic uncertainties induced by the COVID-19 pandemic hit the self-employed particularly harsh by deteriorating short-term psychological distress. Moreover, our study is informative about the impact of income uncertainty on psychological distress. © 2020 Elsevier Inc.