This note seeks the socioeconomic roots of racial disparities in COVID-19 mortality, using county-level mortality, economic, and demographic data from 3,140 counties. For all minorities, the minority's population share is strongly correlated with total COVID-19 deaths. For Hispanic/Latino and Asian minorities those correlations are fragile, and largely disappear when we control for education, occupation, and commuting patterns. For African Americans and First Nations populations, the correlations are very robust. Surprisingly, for these two groups the racial disparity does not seem to be due to differences in income, poverty rates, education, occupational mix, or even access to healthcare insurance. A significant portion of the disparity can, however, be sourced to the use of public transit.

Racial Disparity in COVID-19 Deaths: Seeking Economic Roots with Census data.

10.3386/w27086

Reductions in ambient pollution have been taken as an indisputable "silver lining" to the COVID-19 Pandemic. Indeed, worldwide economic contraction induced by COVID-19 lockdowns should generate global air quality improvements ceteris paribus, including to China's notoriously-poor air quality. We analyze China's official pollution monitor data and account for the large, recurrent improvement in air quality following Lunar New Year (LNY), which essentially coincided with lock-downs in 2020. With the important exception of NO2, China's air quality improvements in 2020 are smaller than we should expect near the pandemic's epicenter: Hubei province. Compared with LNY improvements experienced in 2018 and 2019 in Hubei, we see smaller improvements in SO2 while ozone concentrations increased in both relative and absolute terms (roughly doubling). Similar patterns are found for the six provinces neighboring Hubei. We conclude that COVID-19 had ambiguous impacts on China's pollution, with evidence of relative deterioration in air quality near the Pandemic's epicenter.

Ambiguous Pollution Response to COVID-19 in China

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We analyze the correlates of COVID-19 cases and deaths across US counties. We consider a wide range of correlates - population density, public transportation, age structure, nursing home residents, connectedness to source countries, etc. - finding that these variables are important predictors of variation in disease severity. Many of the effects are persistent - even increasing - through time. We also show that there are fewer deaths and cases in counties where Donald Trump received a high share of the vote in 2016, partly explaining the emerging political divide over lockdown and reopening policies, but that this correlation is reversed when controlling for shares of minority groups. The patterns we identify are meant to improve our understanding of the drivers of the spread of COVID-19, with an eye toward helping policymakers design responses that are sensitive to the specificities of different locations.

Understanding Spatial Variation in COVID-19 across the United States

10.3386/w27137

Drawing on firm-level expectations at a one-year forecast horizon in the Survey of Business Uncertainty (SBU), we construct novel, forward-looking reallocation measures for jobs and sales. These measures rise sharply after February 2020, reaching rates in April that are 2.4 (3.9) times the pre-COVID average for jobs (sales). We also draw on special questions in the April SBU to quantify the near-term impact of the COVID-19 shock on business staffing. We find 3 new hires for every 10 layoffs caused by the shock and estimate that 42 percent of recent layoffs will result in permanent job loss. Our survey evidence aligns well with anecdotal evidence of large pandemic-induced demand increases at some firms, with contemporaneous evidence on gross business formation, and with a sharp pandemic-induced rise in equity return dispersion across firms. After developing the evidence, we consider implications of our evidence for the economic outlook and for policy responses to the pandemic. Unemployment benefit levels that exceed worker earnings, policies that subsidize employee retention, occupational licensing restrictions, and regulatory barriers to business formation will impede reallocation responses to the COVID-19 shock.

COVID-19 Is Also a Reallocation Shock

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How quickly will American businesses reopen after COVID-19 lockdowns end? We use a nationwide survey of small businesses to measure firms’ expectations about their re-opening and future demand. A plurality of firms in our sample expect to reopen within days of the end of legal restrictions, but a sizable minority expect to delay their reopening. While health-related variables, such as COVID-19 case rates and physical proximity of workers, do explain the prevalence and expected duration of regulated lockdown, these variables have little or no correlation with post-lockdown reopening intentions. Instead, almost one half of closed or partially open businesses said that their reopening would depend on the reopening of related businesses, including customers and suppliers. Owners expect demand to be one-third lower than before the crisis through autumn. Firms with more pessimistic expectations about demand predict a later reopening. Using an instrumental variables strategy, we estimate the relationship between demand expectations and reopening. These estimates suggest that post-lockdown delays in reopening can be explained by low levels of expected demand.

Business Reopening Decisions and Demand Forecasts During the COVID-19 Pandemic

10.3386/w27559

In the decade following the financial crisis of 2008, investment funds in corporate bond markets became prominent market players and generated concerns of financial fragility. The COVID-19 crisis provides an opportunity to inspect their resilience in a major stress event. Using daily microdata, we document major outflows in these funds during this period, far greater than anything they experienced in past events. Large outflows were sustained over several weeks and were widespread across funds. Inspecting the role of sources of fragility, we show that both the illiquidity of fund assets and the vulnerability to fire sales were important factors in explaining outflows in this episode. The exposure to sectors most hurt by the COVID-19 crisis was also important. Two policy announcements by the Federal Reserve about extraordinary direct interventions in corporate-bond markets seem to have played an important role in calming down the panic and reversing the outflows.

Financial Fragility in the COVID-19 Crisis: The Case of Investment Funds in Corporate Bond Markets

10.3386/w27294

This paper provides the first nationally representative estimates of vulnerability to severe com-plications from COVID-19 overall and across race-ethnicity and socioeconomic status. We use the Panel Study of Income Dynamics (PSID) to examine the prevalence of specific health condi-tions associated with complications from COVID-19 and to calculate, for each individual, an index of the risk of severe complications from respiratory infections developed by DeCaprio et al. (2020). We show large disparities across race-ethnicity and socioeconomic status in the prev-alence of conditions which are associated with the risk of severe complications from COVID-19. Moreover, we show that these disparities emerge early in life, prior to age 65, leading to higher vulnerability to such complications. While vulnerability is highest among older adults regardless of their race-ethnicity or socioeconomic status, our results suggest particular attention should also be given to the risk of adverse outcomes in midlife for non-Hispanic Blacks, adults with a high school degree or less, and low-income Americans.

Disparities in Vulnerability to Severe Complications from COVID-19 in the United States

10.3386/w27208

Big data on job-vacancy postings reveal several dimensions of the impact of COVID-19 on the U.S. job market. Firms have cut back on postings for high-skill jobs more than for low-skill jobs, with small firms nearly halting their new hiring altogether. New-hiring cuts and downskilling are most pronounced in local labor markets lacking depth (where employment is concentrated within a few firms), in low-income areas, and in areas with greater income inequality. Cuts are deeper in industries where workers are more unionized and in the non-tradable sector. Access to finance modulates corporate hiring, with credit-constrained firms curtailing their job postings the most. Our study shows how the early-2020 global pandemic is shaping the dynamics of hiring, identifying the firms, jobs, places, industries, and labor markets most affected by it. Our results point to important challenges to the scale and speed of a recovery.

Corporate Hiring under COVID-19: Labor Market Concentration, Downskilling, and Income Inequality

10.3386/w27185

Key factors in modeling a pandemic and guiding policy-making include mortality rates associated with infections; the ability of government policies, medical systems, and society to adapt to the changing dynamics of a pandemic; and institutional and demographic characteristics affecting citizens’ perceptions and behavioral responses to stringent policies. This paper traces the cross-country associations between COVID-19 mortality, policy interventions aimed at limiting social contact, and their interactions with institutional and demographic characteristics. We document that, 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 population 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. Our results suggest that policy interventions are effective at slowing the geometric pattern of mortality growth, reducing the peak mortality, and shortening the duration to the first peak. We also shed light on the importance of institutional and demographic characteristics in guiding policy-making for future waves of the pandemic.

Accounting for Global COVID-19 Diffusion Patterns, January-April 2020

10.3386/w27249

COVID-19 may accelerate the automation of jobs, as employers invest in technology to adapt the production process to safeguard against current and potential future pandemics. We identify occupations that have high automation potential and also exhibit a high degree of risk of viral infection. We then examine regional variation in terms of which local labor markets are most at risk. Next we outline the differential impact that COVID-19 may have on automatable jobs for different demographic groups. We find that occupations held by mid-educated females are at highest risk, notably including some healthcare, office and administrative support, and protective service occupations.

COVID-19 and Implications for Automation

10.3386/w27431

We build a publicly available platform that tracks economic activity at a granular level in real time using anonymized data from private companies. We report daily statistics on consumer spending, business revenues, employment rates, and other key indicators disaggregated by county, industry, and income group. Using these data, we study the mechanisms through which COVID-19 affected the economy by analyzing heterogeneity in its impacts across geographic areas and income groups. We first show that high-income individuals reduced spending sharply in mid-March 2020, particularly in areas with high rates of COVID-19 infection and in sectors that require physical interaction. This reduction in spending greatly reduced the revenues of businesses that cater to high-income households in person, notably small businesses in affluent ZIP codes. These businesses laid off most of their low-income employees, leading to a surge in unemployment claims in affluent areas. Building on this diagnostic analysis, we use event study designs to estimate the causal effects of policies aimed at mitigating the adverse impacts of COVID. State-ordered reopenings of economies have little impact on local employment. Stimulus payments to low-income households increased consumer spending sharply, but had modest impacts on employment in the short run, perhaps because very little of the increased spending flowed to businesses most affected by the COVID-19 shock. Paycheck Protection Program loans have also had little impact on employment at small businesses. These results suggest that traditional macroeconomic tools – stimulating aggregate demand or providing liquidity to businesses – may have diminished capacity to restore employment when consumer spending is constrained by health concerns. During a pandemic, it may be more fruitful to mitigate economic hardship through social insurance. More broadly, this analysis illustrates how real-time economic tracking using private sector data can help rapidly identify the origins of economic crises and facilitate ongoing evaluation of policy impacts.

How Did COVID-19 and Stabilization Policies Affect Spending and Employment? A New Real-Time Economic Tracker Based on Private Sector Data

10.3386/w27344

We report the results of a nationally-representative sample of the US population during the COVID-19 pandemic. The survey ran in two waves from April 1-5, 2020 and May 2-8, 2020. Of those employed pre-COVID-19, we find that about half are now working from home, including 35.2% who report they were commuting and recently switched to working from home. In addition, 10.1% report being laid-off or furloughed since the start of COVID-19. There is a strong negative relationship between the fraction in a state still commuting to work and the fraction working from home. We find that the share of people switching to remote work can be predicted by the incidence of COVID-19 and that younger people were more likely to switch to remote work. Furthermore, states with a higher share of employment in information work including management, professional and related occupations were more likely to shift toward working from home and had fewer people laid off or furloughed. We find no substantial change in results between the two waves, suggesting that most changes to remote work manifested by early April.

COVID-19 and Remote Work: An Early Look at US Data

10.3386/w27229

One of the most common policy prescriptions to reduce the spread of COVID-19 has been to legally enforce social distancing through state or local shelter-in-place orders (SIPOs). This paper is the first to explore the comparative effectiveness of early county-level SIPOs versus later statewide mandates in curbing COVID-19 growth. We exploit the unique laboratory of Texas, a state in which the early adoption of local SIPOs by densely populated counties covered almost two-thirds of the state’s population prior to Texas’s adoption of a statewide SIPO on April 2, 2020. Using an event study framework, we document that countywide SIPO adoption is associated with a 14 percent increase in the percent of residents who remain at home full-time, a social distancing effect that is largest in urbanized and densely populated counties. Then, we find that in early adopting counties, COVID-19 case growth fell by 19 to 26 percentage points two-and-a-half weeks following adoption of a SIPO, a result robust to controls for county-level heterogeneity in outbreak timing, coronavirus testing, and border SIPO policies. This effect is driven nearly entirely by highly urbanized and densely populated counties. We find that approximately 90 percent of the curbed growth in COVID-19 cases in Texas came from the early adoption of SIPOs by urbanized counties, suggesting that the later statewide shelter-in-place mandate yielded relatively few health benefits.

Were Urban Cowboys Enough to Control COVID-19? Local Shelter-in-Place Orders and Coronavirus Case Growth

10.3386/w26971

Using tools described in our earlier work (Hassan et al., 2019, 2020), we develop text-based measures of the costs, benefits, and risks listed firms in the US and over 80 other countries associate with the spread of Covid-19 and other epidemic diseases. We identify which firms expect to gain or lose from an epidemic disease and which are most affected by the associated uncertainty as a disease spreads in a region or around the world. As Covid-19 spread globally in the first quarter of 2020, firms' primary concerns relate to the collapse of demand, increased uncertainty, and disruption in supply chains. Other important concerns relate to capacity reductions, closures, and employee welfare. Financing concerns were mentioned relatively rarely in the first quarter but appear to become a more important concern in the second quarter. We also identify some firms that foresee opportunities in new or disrupted markets due to the spread of the disease. Finally, we find some evidence that firms that have experience with SARS or H1N1 have more positive expectations about their ability to deal with the coronavirus outbreak.

Firm-level Exposure to Epidemic Diseases: Covid-19, SARS, and H1N1

10.3386/w27099

We study the impact of non-pharmaceutical policy interventions (NPIs) like “stay-at-home” orders on the spread of infectious disease. Local policies have little impact on the economy nor on local public health. Stay-at-home is only weakly associated with slower growth of Covid-19 cases. Reductions in observed “mobility” are not associated with slower growth of Covid-19 cases. Stay-at-home is associated with lower workplace and more residential activity, but common shocks matter much more. Moreover, job losses have been no higher in US states that implemented stay-at-home during the Covid-19 pandemic than in states that did not have stay-at-home. All of these results demonstrate that the Covid-19 pandemic is a common economic and public health shock. They also show that policy spillovers and behavioral responses are important. The tradeoff between the economy and public health in a pandemic depends strongly on what is happening elsewhere. This underscores the importance of coordinated economic and public health responses.

Health vs. Wealth? Public Health Policies and the Economy During Covid-19

10.3386/w27173

There is growing concern that the COVID-19 pandemic may have severe, adverse effects on the health care sector, a sector of the economy that historically has been somewhat shielded from the business cycle. In this paper, we study one aspect of this issue by estimating the magnitude of the COVID-19 pandemic on use of outpatient health services. We use 2010-2020 data from the Outpatient Influenza-like Illness Surveillance Network (ILINet). Our findings indicate that the COVID-19 pandemic is associated with about a 67 percent decline in the total number of outpatient visits per provider by the week of April 12-18th, 2020 relative to the same week in prior years. Effects become apparent earlier in the pandemic for outpatient visits for non-flu symptoms, but we find negative effects on outpatient visits for flu symptoms as well.

Effects of the COVID-19 Pandemic on Outpatient Providers in the US

10.3386/w27245

Little is known about individual beliefs concerning the Coronavirus Disease 2019 (COVID-19). Still less is known about how these beliefs influence the spread of the virus by determining social distancing behaviors. To shed light on these questions, we conduct an online experiment (n = 3,610) with participants in the US and UK. Participants are randomly allocated to a control group, or one of two treatment groups. The treatment groups are shown upper- or lower-bound expert estimates of the infectiousness of the virus. We present three main empirical findings. First, individuals dramatically overestimate the infectiousness of COVID-19 relative to expert opinion. Second, providing people with expert information partially corrects their beliefs about the virus. Third, the more infectious people believe that COVID-19 is, the less willing they are to take social distancing measures, a finding we dub the “fatalism effect”. We estimate that small changes in people's beliefs can generate billions of dollars in mortality benefits. Finally, we develop a theoretical model that can explain the fatalism effect.

Fatalism, Beliefs, and Behaviors During the COVID-19 Pandemic

10.3386/w27422

The threat of COVID-19 has increased the health risks of going to an office or factory, leading more workers to do their jobs remotely. In this paper, we provide results from firm surveys on both small and large businesses on the prevalence and productivity of remote work, and expectations about the persistence of remote work once the COVID-19 crisis ends. We present four main findings. First, while overall levels of remote work are high, there is considerable variation across industries. The Dingel and Neiman (2020) measure of suitability for remote work does a remarkably good job of predicting the industry level patterns of remote work - highlighting the challenge of moving many industries to remote work. Second, remote work is much more common in industries with better educated and better paid workers. Third, in our larger survey, employers think that there has been less productivity loss from remote working in better educated and higher paid industries. Fourth, more than one-third of firms that had employees switch to remote work believe that remote work will remain more common at their company even after the COVID-19 crisis ends.

What Jobs are Being Done at Home During the Covid-19 Crisis? Evidence from Firm-Level Surveys

10.3386/w27448

We summarize some of the early effects and discuss possible future effects of the COVID-19 pandemic and recession on the employment outcomes of older workers in the United States. We start by discussing what we know about how older workers faired in prior recessions in the United States and how COVID-19 and this recession may differ. We then estimate some early effects of the COVID-19 pandemic and recession on employment and unemployment rates by age group and sex using Current Population Survey data. We calculate employment and unemployment rates multiple ways to account for the complicated employment situation and possible errors in survey enumeration. We find that while previous recessions, in some ways, did not affect employment outcomes for older workers as much, this recession disproportionately affected older workers of ages 65 and older. For example, we find that unemployment rates in April 2020 increased to 15.43% for those ages 65 and older, compared to 12.99% for those ages 25-44. We also find that COVID-19 and the recession disproportionately affected women, where women have reached higher unemployment rates than men, which was consistent for all age groups and unemployment rate measures we used.

Early Evidence on the Impact of COVID-19 and the Recession on Older Workers

10.3386/w27132

We make several contributions to understanding how the COVID-19 epidemic and policy responses have affected U.S. labor markets, benchmarked against two previous recessions. First, monthly Current Population Survey (CPS) data show greater declines in employment in April 2020 (relative to February) for Hispanics, workers aged 20 to 24, and those with high school degrees and some college. Second, we show that job loss was larger in occupations that require more interpersonal contact and that cannot be performed remotely. Pre-epidemic sorting into occupations with more potential for remote work and industries that are currently essential explain a large share of gaps in recent unemployment for key racial, ethnic, age, and education sub-populations. However, there is a larger unexplained component to the gender employment gaps. We also address measurement issues known to have affected the March and April 2020 CPS. In particular, non-response increased dramatically, especially among the incoming rotation groups. Some of the increase appears non-random, but is not likely to be driving our conclusions. We also demonstrate the importance of tracking workers who report having a job but being absent, in addition to tracking employed and unemployed workers. We conclude with a discussion of policy priorities implied by the disparities in labor market losses from the COVID-19 crisis that we identify.

Determinants of Disparities in Covid-19 Job Losses

10.3386/w27496

During health crises, like COVID-19, individuals are inundated with messages promoting health-preserving behavior. Does additional light-touch messaging by a credible individual change behavior? Do the features of the message matter? To answer this, we conducted a large-scale messaging campaign in West Bengal, India. Twenty-five million individuals were sent an SMS containing a 2.5-minute clip, delivered by West Bengal native and 2019 Nobel laureate Abhijit Banerjee. All messages encouraged reporting symptoms to the local public health worker. In addition, each message emphasizes one health-preserving behavior (distancing or hygiene) and one motivation for action (effects on everyone or just on self). Further, some messages addressed concerns about ostracism of the infected. Messages were randomized at the PIN code level. As control, three million individuals received a message pointing them to government information. The campaign (i) doubled the reporting of health symptoms to the community health workers (p = 0.001 for fever, p = 0.024 for respiratory symptoms); (ii) decreased travel beyond one’s village in the last two days by 20% (p = 0.026) (on a basis of 37% in control) and increased estimated hand-washing when returning home by 7% (p = 0.044) (67.5% in control); (iii) spilled over to behaviors not mentioned in the message – mask-wearing was never mentioned but increased 2% (p = 0.042), while distancing and hygiene both increased in the sample where they were not mentioned by similar amounts as where they were mentioned; (iv) spilled over onto nonrecipients within the same community, with effects similar to those for individuals who received the messages.

Messages on COVID-19 Prevention in India Increased Symptoms Reporting and Adherence to Preventive Behaviors Among 25 Million Recipients with Similar Effects on Non-recipient Members of Their Communities

10.1038/d41586-020-02205-8

Look beyond gender — if research thrives on collaboration, a book asks, why do we reward individualism?

Equity: a mathematician shares her solution

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Em­ploy­ment rates in the United States fell dra­mat­i­cally between February 2020 and April 2020 as the initial reper­cus­sions of the COVID-19 pandemic re­ver­ber­ated through the labor market. This paper uses data from the CPS Basic Monthly Files to document that the em­ploy­ment decline was par­tic­u­larly severe for im­mi­grants. His­tor­i­cally, immigrant men were more likely to be employed than native men. The COVID-​related labor market dis­rup­tions elim­i­nated the immigrant em­ploy­ment advantage. By April 2020, immigrant men had lower em­ploy­ment rates than native men. The reversal occurred both because the rate of job loss for at-work immigrant men rose relative to that of natives, and because the rate at which out-​of-work im­mi­grants could find jobs fell relative to the native job-​finding rate. A small part of the relative increase in the immigrant rate of job loss arises because im­mi­grants were less likely to work in jobs that could be performed remotely and suffered disparate em­ploy­ment con­se­quences as the lockdown permitted workers with more “remotable” skills to continue their work from home.

The Adverse Effect of the COVID-19 Labor Market Shock on Immigrant Em­ploy­ment

Limited data are available about transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), among youths. During June 17–20, an overnight camp in Georgia (camp A) held orientation for 138 trainees and 120 staff members; staff members remained for the first camp ses-sion, scheduled during June 21–27, and were joined by 363 campers and three senior staff members on June 21. Camp A adhered to the measures in Georgia’s Executive Order* that allowed overnight camps to operate beginning on May 31, including requiring all trainees, staff members, and campers to provide documentation of a negative viral SARS-CoV-2 test ≤12 days before arriving. Camp A adopted most† components of CDC’s Suggestions for Youth and Summer Camps§ to minimize the risk for SARS-CoV-2 introduction and transmis-sion. Measures not implemented were cloth masks for campers and opening windows and doors for increased ventilation in buildings. Cloth masks were required for staff members. Camp attendees were cohorted by cabin and engaged in a variety of indoor and outdoor activities, including daily vigorous singing and cheering. On June 23, a teenage staff member left camp A after developing chills the previous evening. The staff member was tested and reported a positive test result for SARS-CoV-2 the following day (June 24).

SARS-CoV-2 Transmission and Infection Among Attendees of an Overnight Camp — Georgia, June 2020

10.31234/osf.io/w3tfb

How can online communication most effectively respond to misinformation posted on social media? Recent studies examining the content of corrective messages provide mixed results – several studies suggest that politer, hedged messages may increase engagement with corrections, while others favor direct messaging which does not shed doubt on the credibility of the corrective message. Furthermore, common debunking strategies often include keeping the message simple and clear, while others recommend including a detailed explanation of why the initial misinformation is incorrect. To shed more light on how correction style affects correction efficacy, we manipulated both correction strength (direct, hedged) and type (negation, explanation) in response to participants from Amazon Mechanical Turk (N = 2,228) who indicated they would share a false story in a survey experiment. We found minimal evidence suggesting that correction strength or type affects correction engagement, both in terms of likelihood of replying, and accepting or resisting corrective information. However, we do find that analytic thinking and active open-minded thinking are associated with greater updating of beliefs in response to corrective messages, regardless of correction style. Our results help shed light on the efficacy of user-generated corrections of misinformation on social media.

You’re definitely wrong, maybe: Correction style has minimal effect on corrections of misinformation online

10.31234/osf.io/enrv9

Resilience, as a trait, process, or outcome, is an important factor to explain behavioral diversity between individuals and population groups in face of stress and adversity. Individuals and groups who can bounce back shorty after stressful events, experience less severe negative emotions (depression, anxiety) and manage situations through efficient problem-solving strategies are categorized as resilient. Enhancing populations’ and individuals’ resilience becomes a central strategy for prevention of maladaptive behaviors, especially among adolescents. Several psychosocial interventions, mostly taking a positive psychology approach, improve resilience and reduce disruptive behaviors (e.g., using illicit drug and alcohol or self-harm behaviors) among adolescents. However, the role of brain awareness and training interventions targeting cognitive underpinning of resilience is not fully explored. In this chapter, we firstly review the existing literature and address the interventions that indirectly increase cognitive resilience among school-aged adolescents. Then we introduce the Promoting Cognitive Resilience (ProCoRe), a new multi-modal cognitive resilience training program, that taps different cognitive functions that are documented to be effective in the neuroscience literature. Clinical and public health implications of the ProCoRe as a prevention program to empower adolescents to avoid high risk behaviors in face of stressful through effective emotion regulation and impulse control. are discussed.

Enhancing Cognitive Resilience in Adolescence and Young Adults: A Neuroscience-informed Approach

10.31234/osf.io/xjd64

Political polarization, or the ideological distance between the political left and right, has grown steadily in recent decades. There is a rising concern over the role that ‘bad actors’ or trolls may play in polarization in online networks. In this research, we examine the processes by which trolls may sow intergroup conflict through polarizing rhetoric. We developed a dictionary to gauge online polarization by measuring language associated with communications that display partisan bias in their diffusion. We validated the polarized language dictionary in three different contexts and across multiple time periods. We found the polarization dictionary made out-of-set predictions, generalized to new political contexts (#BlackLivesMatter), and predicted partisan differences in public polls about COVID-19. Then we analyzed 383,510 tweets from a known Russian troll source (the Internet Research Agency) and found that their use of polarized language has increased over time. We also compared troll tweets from 3 different countries (N = 798,33) and found that they all utilize more polarized language on average than a control dataset of tweets from regular Americans (N = 1,507,300) and trolls have dramatically increased their use of polarized rhetoric over time. These results illustrate how trolls leverage polarized language. We also provide an open-source, simple tool for exploration of polarized communications on social media.

Troll and Divide: The Language of Online Polarization

10.31234/osf.io/wtdf2

This study empirically investigates the complex interplay between the severity of the coronavirus pandemic, mobility changes in retail and recreation, transit stations, workplaces, and residential areas, and lockdown measures in 88 countries of the word. To conduct the study, data on mobility patterns, socioeconomic and demographic characteristics of people, lockdown measures, and coronavirus pandemic were collected from multiple sources (e.g., Google, UNDP, UN, BBC, Oxford University, Worldometer). A Structural Equation Modeling (SEM) technique is used to investigate the direct and indirect effects of independent variables on dependent variables considering the intervening effects of mediators. Results show that lockdown measures have significant effects to encourage people to maintain social distancing. However, pandemic severity and socioeconomic and institutional factors have limited effects to sustain social distancing practice. The results also explain that socioeconomic and institutional factors of urbanity and modernity have significant effects on pandemic severity. Countries with a higher number of elderly people, employment in the service sector, and higher globalization trend are the worst victims of the coronavirus pandemic (e.g., USA, UK, Italy, and Spain). Social distancing measures are reasonably effective at tempering the severity of the pandemic.

COVID-19 Pandemic Severity, Lockdown Regimes, and People’s Mobility: Evidence from 88 Countries

2005.04343v4

A growing number of contact tracing apps are being developed to complement manual contact tracing. A key question is whether users will be willing to adopt these contact tracing apps. In this work, we survey over 4,500 Americans to evaluate (1) the effect of both accuracy and privacy concerns on reported willingness to install COVID19 contact tracing apps and (2) how different groups of users weight accuracy vs. privacy. Drawing on our findings from these first two research questions, we (3) quantitatively model how the amount of public health benefit (reduction in infection rate), amount of individual benefit (true-positive detection of exposures to COVID), and degree of privacy risk in a hypothetical contact tracing app may influence American's willingness to install. Our work takes a descriptive ethics approach toward offering implications for the development of policy and app designs related to COVID19.

How good is good enough for COVID19 apps? The influence of benefits, accuracy, and privacy on willingness to adopt

The covid-19 pandemic led many countries to close schools and declare lockdowns during the Spring of 2020, with important impacts on the labor market. We document the effects of the covid-19 lockdown in Spain, which was hit early and hard by the pandemic and suffered one of the strictest lockdowns in Europe. We collected rich household survey data in early May of 2020. We document large em­ploy­ment losses during the lockdown, es­pe­cially in “quar­an­tined” sectors and non-​essential sectors that do not allow for remote work. Em­ploy­ment losses were mostly temporary, and hit lower-​educated workers par­tic­u­larly hard. Women were slightly more likely to lose their job than men, and those who remained employed were more likely to work from home. The lockdown led to a large increase in childcare and housework, given the closing of schools and the inability to outsource. We find that men increased their par­tic­i­pa­tion in housework and childcare slightly, but most of the burden fell on women, who were already doing most of the housework before the lockdown. Overall, we find that the covid-19 crisis appears to have increased gender in­equal­i­ties in both paid and unpaid work in the short-​term.

How the COVID-19 Lockdown Affected Gender In­equal­ity in Paid and Unpaid Work in Spain

We evaluate the causal effect of class size (i.e., number of students in a classroom) on incidence of class closure due to flu epidemic in 2015, 2016, and 2017, applying an in­stru­men­tal variable method with the Mai­monides rule to ad­min­is­tra­tive data of public primary and middle school students in one of the largest mu­nic­i­pal­i­ties within the City of Tokyo Met­ro­pol­i­tan Area. Given the classroom area of 63m2 set by reg­u­la­tion in Japan, class size reduction improves social dis­tanc­ing among students in a classroom. We find that class size reduction is effective to reduce class closure due to flu: one unit reduction of class size decreases class closure by about 5%; and forming small classes with 27 students at most, sat­is­fy­ing the social dis­tanc­ing of 1.5 m rec­om­mended to prevent droplet infection including influenza and COVID-19, reduces class closure by about 90%. In addition, we find that the older are students, the larger are the effects of class size reduction. Our findings provide sup­port­ive evidence for the ef­fec­tive­ness of social dis­tanc­ing policy in primary and middle schools to protect students from droplet in­fec­tious disease including COVID-19.

Do Class Size Re­duc­tions Protect Students from In­fec­tious Disease? Lessons for COVID-19 Policy from Flu Epidemic in Tokyo Met­ro­pol­i­tan Area

10.31234/osf.io/puqea

There is preliminary evidence that some patients recovering from novel coronavirus disease (COVID-19) may experience ongoing symptoms such as myalgia, fatigue and headache. Such symptoms have been observed as persistent sequelae of the earlier outbreak of severe acute respiratory syndrome (SARS). In this paper, evidence is presented that novel coronavirus infections may be associated with hypocortisolism which may persist for weeks or months, and that this may be a risk factor for both post-viral symptoms and post-traumatic stress disorder in patients recovering from COVID-19. The mechanisms underlying this phenomenon may involve reversible inflammation or dysfunction at the level of the pituitary gland, or a dysregulated host immune or stress response. The implications of these findings for the assessment and management of patients recovering from the acute phase of COVID-19 are discussed.

COVID-19, hypocortisolism, and psychosomatic sequelae

10.31234/osf.io/zykq7

Children, particularly girls, have heightened vulnerability to sexual violence committed by non-stranger perpetrators (e.g., neighbours) at private residences during the daytime, owing to school closures and a lack of alternative safe venues. Women have heightened vulnerability to sexual and physical violence at all times of day, with attacks by stranger and non-stranger (e.g., intimate partners) perpetrators occurring in both private residences and in public, owing to social isolation and being trapped with abusers. The socio-economic impact of the crisis has increased tensions within households, with reports of physical violence and increased homelessness for women. Vulnerability to violence has been amplified across the population as a whole, with numerous incidents of death and injuries caused by the police while enforcing COVID-19 emergency measures. Policy recommendations are offered.

Patterns of Violence and Its Impact on Women and Children Amidst the Covid-19 Pandemic in Kenya Policy Brief

This study examines the initial impact of COVID-19 shutdowns on the em­ploy­ment and hours of un­in­cor­po­rated self-​employed workers using data from the Current Pop­u­la­tion Survey. Although the shutdowns decreased em­ploy­ment and hours for all groups, dif­fer­en­tial effects by gender, couple status, and parental status exist. Coupled women were less likely to be working than coupled men, while single women were more likely to be working than single men. However, fathers of school-​age children who remained employed were working reduced hours compared to men without children. Remote work mitigated some of the negative effects on em­ploy­ment and hours.

Initial Impact of the COVID-19 Pandemic on the Em­ploy­ment and Hours of Self-​Employed Coupled and Single Workers by Gender and Parental Status

10.31234/osf.io/dgr45

Aims The recent pandemic of COVID-19 has not only shaken the healthcare but also economic structure around the world. In addition to these direct effects, it has also brought in some indirect difficulties owing to the information epidemic on social media. As India experienced a later outbreak of COVID-19 and a prolonged uninterrupted lockdown, we aimed to understand the nature of panic social media users in India are experiencing due to the flow of (mis)information. We further extend this investigation to other countries. Methods We performed a cross-sectional study by conducting survey on multiple social media platforms. We received 1075 responses (sex ratio 2:1) through opportunity sampling from social media users of 30 different countries (between April 11, 2020 and May 15, 2020). We performed both quantitative and qualitative analyses on the 935 respondents from India. Several hypotheses are statistically tested on them and are further examined on rest of the 140 social media users from 29 other countries. We also performed a separate Twitter hashtag analysis and sentiment analysis on the responses. We applied a citizen science approach to involve the respondents in the analysis pipeline after the survey. Results This cross-sectional study on 1075 social media users from India and 29 other countries revealed a significant increase of social media usage and rise of panic over time in India. Middle-aged people and female exhibit a higher panic in India. The amount of panic was independent of the nature of association with COVID-19. The change of mental health was associated with panic level and productivity. Further qualitative analysis highlights the occurrences of information panic, economic panic, moral panic and spiritual panic, among other causes. Conclusions Several panic behaviors are unique to social media users in India possibly because COVID-19 broke out relatively later in comparison with the other countries and the uninterrupted lockdown prolonged for a long time. The amount of social media usage might not be causal but has a significant role in generating panic among the people in India. A significantly higher level of panic among the middle-aged people can be attributed to their higher amount of responsibility. The popularity of different hashtags, including the names of drugs under trial for COVID-19, in limited countries highlight that the causes of panic are not the same everywhere. As some of the respondents took part as citizen scientists a robust perspective to the outcome is obtained.

The Nature, Cause and Consequence of COVID-19 Panic among Social Media Users in India

10.31234/osf.io/xwyjq

In the last decade, political protest events have been rising in Western democracies. At the same time, there has been a steady increase in the diffusion of conspiracy theories in political communication, a phenomenon that has captured the interest of scholars for its growing political relevance. However, while most research focuses on the reasons why citizens believe in conspiracies, studies looking at the political-behavioral implications of such beliefs, in particular their connection to political radicalism, have been more limited. In this paper we investigate the association between people's belief in conspiracies and their propensity to endorse political violence and to legitimate radical political action. We propose a model in which belief in conspiracies mediates the impact of dispositional aggression on radical attitudes, and test it empirically on an online sample of US residents collected on Amazon Mechanical Turk. Our results suggest that conspiracy theories partially channel individuals' aggression towards political targets.

Belief in conspiracy theories, aggression, and attitudes towards political violence

10.31234/osf.io/7wghn

This research report explores the impacts of the COVID-19 pandemic on patterns of sexual and gender-based violence (SGBV) in Kenya. The research entailed conducting interviews across the 47 counties of Kenya, including in informal settlements, to document sexual violence and other violations of adults and children during the COVID-19 pandemic. There have been 6,366 confirmed COVID-19 cases and 148 deaths in Kenya as of June 30, 2020. The Kenyan government implemented emergency measures in the wake of COVID-19 that included a nightly dusk-to-dawn curfew, school closures, and restrictions to road, rail, and air movements, as examples. The research was prompted by concerns raised by SGBV and human rights organisations that the COVID-19 crisis is exacerbating women and girls’ vulnerability to SGBV and preventing their access to life-saving services. The research findings suggest three main impacts of the COVID-19 emergency on SGBV: 1. Emergency measures are exacerbating the vulnerability of children and women; 2. The socio-economic impact of the crisis has increased tensions within households, with reports of physical violence and increased homelessness for women; and 3. Vulnerability to violence has been amplified across the population as a whole according to reports by human rights actors, with there being numerous incidents of death and injuries caused by the police while enforcing the COVID-19 emergency measures put into place. We offer policy recommendations based on our findings.

Sexual and Other Forms of Violence during the COVID-19 Pandemic Emergency in Kenya

10.31234/osf.io/jnesc

Cognitive resources are needed for successful executive functioning; when resources are limited due to competing demands, task performance is impaired. Although some tasks are accomplished with relatively few resources (e.g., judging trustworthiness and emotion in others), others are more complex. Specifically, in the face of emotional ambiguity (i.e., stimuli that do not convey a clear positive or negative meaning, such as a surprised facial expression), our decisions to approach or avoid appear to rely on the availability of top-down regulatory resources to overcome an initial negativity bias. Cognition-emotion interaction theories (e.g., dual competition) posit that emotion and executive processing rely on shared resources, suggesting that competing demands would hamper these regulatory responses towards emotional ambiguity. Here, we employed a 2x2 design to investigate the effects of load (low versus high) and domain (non-emotional vs. emotional) on evaluations of surprised faces. As predicted, there were domain-specific effects, such that categorizations of surprise were more negative for emotional than non-emotional loads. Consistent with prior work, low load (regardless of domain; i.e., domain-general) was associated with greater response competition on trials resulting in a positive categorization, showing that positive categorizations are characterized by an initial negativity. This effect was diminished under high load. These results lend insight into the resources supporting a positive valence bias by demonstrating that emotion-specific regulatory resources are important for overriding the initial negativity in response to emotional ambiguity. However, both domain-general and domain-specific loads impact the underlying processes.

Emotional working memory load selectively increases negativity bias

10.3386/w27550

The coronavirus has created an enormous—and expensive—challenge for elementary and secondary schools, while simultaneously depleting the revenue sources on which public schools depend. During the Great Recession, the federal government filled in a significant share of lost revenue. In contrast, the federal response to date has been limited. If Congress decides to invest in future generations, it faces a range of options for how to structure an aid package. One key aspect for any stabilization package is how federal funds should be allocated to states. We consider the types of approaches used in recent proposals, during the Great Recession, and at the onset of the COVID-19 crisis, as well as in major ongoing federal education programs for compensatory and special education. We simulate the distribution of funds and show the considerable difference in how per-child allocations correlate with child poverty rates under the most likely alternative approaches.

Federal Aid to School Districts During the COVID-19 Recession

10.3386/w27063

This paper analyzes a sequential approach to lifting interventions in the COVID-19 pandemic taking heterogeneity in the population into account. The population is heterogeneous in terms of the consequences of infection (need for hospitalization and critical care, and mortality) and in terms of labor force participation. Splitting the population in two groups by age, a less affected younger group that is more likely to work, and a more affected older group less likely to work, and lifting interventions sequentially (for the younger group first and the older group later on) can substantially reduce mortality, demands on the health care system, and the economic cost of interventions.

Sequential Lifting of COVID-19 Interventions with Population Heterogeneity