We estimate the effect of social media deactivation on users' emotional state in two large randomized experiments before the 2020 U.S. election. People who deactivated Facebook for the six weeks before the election reported a 0.060 standard deviation improvement in an index of happiness, depression, and anxiety, relative to controls who deactivated for just the first of those six weeks. People who deactivated Instagram for six weeks reported a 0.041 standard deviation improvement relative to controls. Exploratory analysis suggests the Facebook effect is driven by people over 35, while the Instagram effect is driven by women under 25.

We study the effects of social media political advertising by randomizing subsets of 36,906 Facebook users and 25,925 Instagram users to have political ads removed from their news feeds for six weeks before the 2020 US presidential election. We show that most presidential ads were targeted toward parties' own supporters and that fundraising ads were most common. On both Facebook and Instagram, we found no detectable effects of removing political ads on political knowledge, polarization, perceived legitimacy of the election, political participation (including campaign contributions), candidate favorability, and turnout. This was true overall and for both Democrats and Republicans separately.

We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 weeks before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.

We evaluate quartile rankings of countries during the COVID-19 pandemic using both official (confirmed) and excess mortality data. By December 2021, the quartile rankings of three-fifths of the countries differ when ranked by excess vs. official mortality. Countries that were "doing substantially better" in the excess mortality measure were characterized by higher urban population shares; higher GDP per capita; and higher scores on institutional and policy variables. In a narrow model, after controlling for GDP per capita and vaccination rates, we find that the Excess / Official mortality ratio was smaller in countries with higher vaccination rates. In a broader model, after adding institutional and policy variables, the Excess / Official mortality ratio was smaller in countries with a higher institutional measure of voice and accountability.

We compare the importance of market factors against that of COVID-19 dynamics and policy responses in explaining Eurozone sovereign spreads. First, we estimate a multifactor model for changes in credit default swap (CDS) spreads over 2014 to June 2019. Then, we apply a synthetic control-type procedure to extrapolate model-implied changes in CDS. The factor model does very well over the rest of 2019 but breaks down during the pandemic, especially in March of 2020. We find that the March 2020 divergence is well accounted for by COVID-specific risks and associated policies, mortality outcomes, and policy announcements, rather than traditional determinants. Daily CDS widening ceased almost immediately after the European Central Bank announced the Pandemic Emergency Purchase Programme, but the divergence between actual and model-implied changes persisted. This points to COVID-19 Dominance — widening spreads during the pandemic leading to unconventional monetary policies that primarily aim to mitigate short-run fears, temporarily pushing away concerns over fiscal risk.

We trace the cross-country associations between COVID-19 mortality, policy interventions aimed at limiting social contact, and their interactions with institutional and demographic characteristics. With a lag, more stringent pandemic policies were associated with lower mortality growth rates. The association between stricter pandemic policies and lower future mortality growth is more pronounced in countries with a greater proportion of the elderly and urban population, greater democratic freedoms, and larger international travel flows. Countries with greater policy stringency in place prior to the first death realized lower peak mortality rates and exhibited lower durations to the first mortality peak. In contrast, countries with higher initial mobility saw higher peak mortality rates in the first phase of the pandemic, and countries with a larger elderly population, a greater share of employees in vulnerable occupations, and a higher level of democracy took longer to reach their peak mortalities.

Creutzfeldt–Jakob disease (CJD) is a rapidly progressive and universally fatal prion disease. Prior research on CJD in the U.S. demonstrated a stable incidence rate from 1979 - 2006, though recent trends are not as well described. The incidence of sporadic CJD (sCJD), the most common type of CJD, is higher among older patients. Due to demographic trends worldwide towards aging populations, the epidemiology of CJD is evolving. We examined death certificate data from 2007 - 2020 to better understand recent trends of CJD in the U.S. We find evidence of large increases in CJD prevelance, mostly concentrated amongst the elderly and female U.S. population.

Despite complex care needs during critical COVID-19, the associated long-term healthcare spending is poorly understood, limiting the ability of policy-makers to prioritise necessary care and plan for future medical countermeasures. We conducted a retrospective cohort study of adults hospitalised with COVID-19 in the USA (Apr. ‒ June 2020) using data from the national PINC AI Healthcare Database. Patients were followed for 365 days to measure hospital spending starting on the date of admission. We used a multivariable logistic model to identify characteristics associated with high spending. Patients who received care in the intensive care unit, received a non-recommended COVID-19 treatment, had a longer length of stay, and had Medicare or Medicaid insurance were associated with a higher predicted probability of high hospital spending over 365 days. Most hospital spending incurred over 1 year was for care within 90 days of admission. Patients receiving complex care or non-recommended treatments were associated with higher spending, while those receiving recommended treatments were associated with lower spending.

In early 2021, effective SARS-CoV-2 (COVID-19) vaccines became available in the United States; by mid-April 2021, vaccine availability outstripped demand, daily vaccination rates peaked, and COVID-19 vaccines were found highly effective in adult populations. Accurate estimates of the number of vaccine-preventable deaths had higher vaccination rates been attained could have helped local policymakers and possibly persuaded more to get vaccinated. Because existing estimation methodologies are limited, for the period 1/1/21 – 4/30/22, we simulated the number of vaccine-preventable deaths associated with two-dose COVID-19 vaccination that incorporated state-level population, death, and vaccination numbers and three scenarios of vaccination rate achievement. Nationally, we found that had 100% of the population became fully vaccinated during the period examined, 318,979 deaths, or approximately 50% of reported COVID-19 deaths, might have been prevented; had 85% been so, 28% might have been prevented. Across states, we found substantial variation in the proportion of avoidable COVID-19 deaths, from 25% in Massachusetts to 74% in Alaska.

Ambulatory surgical centers (ASCs) are increasingly being acquired by private equity firms, yet the implications for patients remain understudied. In this study we employed a quasi-experimental difference-in-differences design within an event study framework to assess changes in outcomes associated with the acquisition of ASCs by private equity entities. Using a two-way fixed effects model, we assessed the baseline probability of an unplanned hospital visit, total costs, and total encounters three years preacquisition compared with three years postacquisition in ASCs acquired by private equity versus those acquired by non–private equity entities. There was no statistically significant observed change in the probability of an unplanned hospital visit, total costs, or total encounters after acquisition by private equity relative to acquisition by non–private equity entities. When we compared private equity–acquired ASCs with matched ASCs that were never acquired, we also found no statistically significant relative change in the probability of an unplanned hospital visit, total costs, or total encounters.

One of the most important consequences of the COVID-19 pandemic on health care delivery in the U.S. is the acceleration of a long-building shift from inpatient to outpatient delivery of operative care. Before the pandemic, enhanced recovery pathways and minimally invasive techniques opened the possibility of performing increasingly complex operations in hospital outpatient departments and ambulatory surgical centers. To create inpatient surge capacity during the pandemic, emergency waivers expanded the care that outpatient surgical centers could provide, rendering them increasingly important sites of care delivery for both the present need for inpatient capacity as well as the future of value-based care. In this article, we analyze this shifting trend and provide policy recommendations for federal health agencies.