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    1. Why do we adopt new rules, such as social distancing? While decades of psychology research stresses the importance of social influence on individual behaviour, many COVID-19 campaigns focused on convincing individuals that distancing is the right thing to do. In a global dataset (114 countries, n=6674), we investigated how social influences predict people’s adherence to distancing rules during the pandemic. Analyses showed that people practised distancing more when they thought their close social circle did so; this social influence mattered more than people thinking distancing was the right thing. People’s adherence also aligned with their fellow citizens’, but only if they deeply bonded with their country. Personal vulnerability to the disease predicted distancing more for people with larger social circles. Empathy, collective efficacy and collectivism also significantly predicted distancing. During crises, policymakers can achieve behavioural change by emphasising shared values and harnessing the social influence of close friends and relatives.
    1. While severe social-distancing measures have proven effective in slowing the coronavirus disease 2019 (COVID-19) pandemic, second-wave scenarios are likely to emerge as restrictions are lifted. Here we integrate anonymized, geolocalized mobility data with census and demographic data to build a detailed agent-based model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in the Boston metropolitan area. We find that a period of strict social distancing followed by a robust level of testing, contact-tracing and household quarantine could keep the disease within the capacity of the healthcare system while enabling the reopening of economic activities. Our results show that a response system based on enhanced testing and contact tracing can have a major role in relaxing social-distancing interventions in the absence of herd immunity against SARS-CoV-2.
    1. School closures due to the COVID-19 pandemic have disrupted the education of 91% of students worldwide. As a critical process in supporting young children’s resilience, play is increasingly recognised as a valuable pedagogical strategy within a shifting educational landscape during the pandemic. This study reports on findings from a survey on play in early childhood education of 309 early childhood teachers during primary school closures in Ireland. Eighty-two per cent of teachers recommended play strategies to parents during remote teaching and home schooling and almost all teachers (99%) intended to use play as a pedagogical strategy upon school reopening. Teachers believed play was an especially important pedagogical tool in supporting young children’s social-emotional development, learning and transition back to school. Over a third highlighted uncertainty surrounding capacity to use play upon school reopening given COVID-19 regulations, emphasizing the need for greater guidance to support teachers’ commitment to play-based pedagogical strategies.
    1. This study investigated the psychological impact of the COVID-19 pandemic in pregnant women from Bosnia and Herzegovina and Serbia during March and April 2020. 152 respondents filled out an online administered questionnaire assessing psychological impact of the COVID-19 pandemic, fear of COVID-19 infection and death, attachment styles, perceived social support and other relevant sociodemographic and life history variables. The results indicate that the COVID-19 pandemic significantly impacts the level of fear and overall psychological functioning of the pregnant women. Especially prone to increased stress reactions are those who have lower partner support, fearful and preoccupied attachment styles, and lower financial status. The results are discussed in terms of the need for a systemic approach to psychological screening for pregnant women. We also point out the need to carefully evaluate the use of the IES-R when applied to assess reactions to collectively experienced prolonged stressful events such as the pandemic.
    1. Firms with greater financial flexibility should be better able to fund a revenue shortfall resulting from the COVID-19 shock and benefit less from policy responses. We find that firms with high financial flexibility experience a stock price drop lower by 26% or 9.7 percentage points than those with low financial flexibility accounting for a firm’s industry. This differential return persists as stock prices rebound. Similar results hold for CDS spreads. The stock price of a firm with an average payout over assets ratio would have dropped 2 percentage points less with no payouts for the last three years.
    1. Public transit is central to cultivating equitable communities. Meanwhile, the novel coronavirus disease COVID-19 and associated social restrictions has radically transformed ridership behavior in urban areas. Perhaps the most concerning aspect of the COVID-19 pandemic is that low-income and historically marginalized groups are not only the most susceptible to economic shifts but are also most reliant on public transportation. As revenue decreases, transit agencies are tasked with providing adequate public transportation services in an increasingly hostile economic environment. Transit agencies therefore have two primary concerns. First, how has COVID-19 impacted ridership and what is the new post-COVID normal? Second, how has ridership varied spatio-temporally and between socio-economic groups? In this work we provide a data-driven analysis of COVID-19's affect on public transit operations and identify temporal variation in ridership change. We then combine spatial distributions of ridership decline with local economic data to identify variation between socio-economic groups. We find that in Nashville and Chattanooga, TN, fixed-line bus ridership dropped by 66.9% and 65.1% from 2019 baselines before stabilizing at 48.4% and 42.8% declines respectively. The largest declines were during morning and evening commute time. Additionally, there was a significant difference in ridership decline between the highest-income areas and lowest-income areas (77% vs 58%) in Nashville.
    1. We study how the differential timing of local lockdowns due to COVID-19 causally affects households’ spending and macroeconomic expectations at the local level using several waves of a customized survey with more than 10,000 respondents. About 50% of survey participants report income and wealth losses due to the corona virus, with the average losses being $5,293 and $33,482 respectively. Aggregate consumer spending dropped by 31 log percentage points with the largest drops in travel and clothing. We find that households living in counties that went into lockdown earlier expect the unemployment rate over the next twelve months to be 13 percentage points higher and continue to expect higher unemployment at horizons of three to five years. They also expect lower future inflation, report higher uncertainty, expect lower mortgage rates for up to 10 years, and have moved out of foreign stocks into liquid forms of savings. The imposition of lockdowns can account for much of the decline in employment in recent months as well as declines in consumer spending. While lockdowns have pronounced effects on local economic conditions and households’ expectations, they have little impact on approval ratings of Congress, the Fed, or the Treasury but lead to declines in the approval of the President.
    1. In March of 2020, banks faced the largest increase in liquidity demands ever observed. Firms drew funds on a massive scale from pre-existing credit lines and loan commitments in anticipation of cash flow disruptions from the economic shutdown designed to contain the COVID-19 crisis. The increase in liquidity demands was concentrated at the largest banks, who serve the largest firms. Pre-crisis financial condition did not limit banks’ liquidity supply. Coincident inflows of funds to banks from both the Federal Reserve’s liquidity injection programs and from depositors, along with strong pre-shock bank capital, explain why banks were able to accommodate these liquidity demands.
    1. We study partisan differences in Americans’ response to the COVID-19 pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, which could impact the extent to which Republicans and Democrats engage in social distancing and other efforts to reduce disease transmission. We develop a simple model of a pandemic response with heterogeneous agents that clarifies the causes and consequences of heterogeneous responses. We use location data from a large sample of smartphones to show that areas with more Republicans engaged in less social distancing, controlling for other factors including public policies, population density, and local COVID cases and deaths. We then present new survey evidence of significant gaps at the individual level between Republicans and Democrats in self-reported social distancing, beliefs about personal COVID risk, and beliefs about the future severity of the pandemic.
    1. The reproduction number R0 plays an outsized role in COVID-19 risk management. But it is an insufficient statistic, particularly for financial risks, because transmissions are stochastic due to environmental factors. We introduce aggregate transmission shocks into a widely-used epidemic model and link firm valuation to epidemic data by using an asset-pricing framework that accounts for potential vaccines. Pooling early data, we estimate a large R0 and transmission volatility. R0 mismeasures social-distancing benefits because it gives a poor approximation of conditional infection forecasts. R0 mismeasures financial risks since transmission volatility and vaccine news also determine firm-value damage.
    1. We explore the impact of COVID-19 on employee's digital communication patterns through an event study of lockdowns in 16 large metropolitan areas in North America, Europe and the Middle East. Using de- identified, aggregated meeting and email meta-data from 3,143,270 users, we find, compared to pre- pandemic levels, increases in the number of meetings per person (+12.9 percent) and the number of attendees per meeting (+13.5 percent), but decreases in the average length of meetings (-20.1 percent). Collectively, the net effect is that people spent less time in meetings per day (-11.5 percent) in the post- lockdown period. We also find significant and durable increases in length of the average workday (+8.2 percent, or +48.5 minutes), along with short-term increases in email activity. These findings provide insight from a novel dataset into how the nature of work has changed for a large sample of knowledge workers. We discuss these changes in light of the ongoing challenges faced by organizations and workers struggling to adapt and perform in the face of a global pandemic.
    1. Managing the outbreak of COVID-19 in India constitutes an unprecedented health emergency in one of the largest and most diverse nations in the world. On May 4, 2020, India started the process of releasing its population from a national lockdown during which extreme social distancing was implemented. We describe and simulate an adaptive control approach to exit this situation, while maintaining the epidemic under control. Adaptive control is a flexible counter-cyclical policy approach, whereby different areas release from lockdown in potentially different gradual ways, dependent on the local progression of the dis- ease. Because of these features, adaptive control requires the ability to decrease or increase social distancing in response to observed and projected dynamics of the disease outbreak. We show via simulation of a stochastic Susceptible-Infected-Recovered (SIR) model and of a synthetic intervention (SI) model that adaptive control performs at least as well as immediate and full release from lockdown starting May 4 and as full release from lockdown after a month (i.e., after May 31). The key insight is that adaptive response provides the option to increase or decrease socioeconomic activity depending on how it affects disease progression and this freedom allows it to do at least as well as most other policy alternatives. We also discuss the central challenge to any nuanced release policy, including adaptive control, specifically learning how specific policies translate into changes in contact rates and thus COVID-19's reproductive rate in real time.
    1. This study quantifies the effect of state reopening policies on daily mobility, travel, and mixing behavior during the COVID-19 pandemic. We harness cell device signal data to examine the effects of the timing and pace of reopening plans in different states. We quantify the increase in mobility patterns during the reopening phase by a broad range of cell-device-based metrics. Soon (four days) after reopening, we observe a 6% to 8% mobility increase. In addition, we find that temperature and precipitation are strongly associated with increased mobility across counties. The mobility measures that reflect visits to a greater variety of locations responds the most to reopening policies, while total time in vs. outside the house remains unchanged. The largest increases in mobility occur in states that were late adopters of closure measures, suggesting that closure policies may have represented more of a binding constraint in those states. Together, these four observations provide an assessment of the extent to which people in the U.S. are resuming movement and physical proximity as the COVID-19 pandemic continues.
    1. We explore how household consumption responds to epidemics, utilizing transaction-level household financial data to investigate the impact of the COVID-19 virus. As the number of cases grew, households began to radically alter their typical spending across a number of major categories. Initially spending increased sharply, particularly in retail, credit card spending and food items. This was followed by a sharp decrease in overall spending. Households responded most strongly in states with shelter-in-place orders in place by March 29th. We explore heterogeneity across partisan affiliation, demographics and income. Greater levels of social distancing are associated with drops in spending, particularly in restaurants and retail.
    1. Voluntary social distancing plays a vital role in containing the spread of the disease during a pandemic. As a public good, it should be more commonplace in more homogeneous and altruistic societies. However, for healthy people, observing social distancing has private benefits, too. If sick individuals are more likely to stay home, healthy ones have fewer incentives to do so, especially if the asymptomatic transmission is perceived to be unlikely. Theoretically, we show that this interplay may lead to a stricter observance of social distancing in more diverse and less altruistic societies. Empirically, we find that, consistent with the model, the reduction in mobility following the first local case of COVID-19 was stronger in Russian cities with higher ethnic fractionalization and cities with higher levels of xenophobia. For identification, we predict the timing of the first case using pre-existing patterns of internal migration to Moscow. Using SafeGraph data on mobility patterns, we confirm that mobility reduction in the United States was also higher in counties with higher ethnic fractionalization. Our findings highlight the importance of strategic incentives of different population groups for the effectiveness of public policy.
    1. The U.S. health care system has experienced great pressure since early March 2020 as it pivoted to providing necessary care for COVID-19 patients. But there are signs that non-COVID-19 care use declined during this time period. We examine near real time data from a nationwide electronic healthcare records system that covers over 35 million patients to provide new evidence of how non-COVID-19 acute care and preventive/primary care have been affected during the epidemic. Using event study and difference-in-difference models we find that state closure policies (stay-at-home or non-essential business closures) are associated with large declines in ambulatory visits, with effects differing by type of care. State closure policies reduced overall outpatient visits by about 15-16 percent within two weeks. Outpatient visits for health check-ups and well care experience very large declines during the epidemic, with substantial effects from state closure policies. In contrast, mental health outpatient visits declined less than other care, and appear less affected by state closure policies. We find substitution to telehealth modalities may have played an important role in mitigating the decline in mental health care utilization. Aggregate trends in outpatient visits show a 40% decline after the first week of March 2020, only a portion of which is attributed to state policy. A rebound starts around mid April that does not appear to be explained by state reopening policy. Despite this rebound, care visits still remain below the pre-epidemic levels in most cases.
    1. We analyze the externalities that arise when social and economic interactions transmit infectious diseases such as COVID-19. Individually rational agents do not internalize that they impose infection externalities upon others when the disease is transmitted. In an SIR model calibrated to capture the main features of COVID-19 in the US economy, we show that private agents perceive the cost an additional infection to be around $80k whereas the social cost including infection externalities is more than three times higher, around $286k. This misvaluation has stark implications for how society ultimately overcomes the disease: for a population of individually rational agents, the precautionary behavior by the susceptible flattens the curve of infections, but the disease is not overcome until herd immunity is acquired. The resulting economic cost is high; an initial sharp decline in aggregate output followed by a slow recovery over several years. By contrast, the socially optimal approach in our model focuses public policy measures on the infected in order to contain the disease and quickly eradicate it, which produces a much milder recession. If targeting the infected is impossible, the optimal policy in our model is still to aggressively contain and eliminate the disease, and the social cost of an extra infection rises to $586k.
    1. New York City has been rightly characterized as the epicenter of the coronavirus pandemic in the United States. Just one month after the first cases of coronavirus infection were reported in the city, the burden of infected individuals with serious complications of COVID-19 has already outstripped the capacity of many of the city’s hospitals. As in the case of most pandemics, scientists and public officials don’t have complete, accurate, real-time data on the path of new infections. Despite these data inadequacies, there already appears to be sufficient evidence to conclude that the curve in New York City is indeed flattening. The purpose of this report is to set forth the evidence for – and against – this preliminary but potentially important conclusion. Having examined the evidence, we then inquire: if the curve is indeed flattening, do we know what caused to it to level off?
    1. In the wake of the global pandemic known as COVID-19, retirees, along with those hoping to retire someday, have been shocked into a new awareness of the need for better risk management tools to handle longevity and aging. This paper offers an assessment of the status quo prior to the spread of the coronavirus, evaluates how retirement systems are faring in the wake of the shock. Next we examine insurance and financial market products that may render retirement systems more resilient for the world’s aging population. Finally, potential roles for policymakers are evaluated.
    1. Employment rates in the United States fell dramatically between February 2020 and April 2020 as the 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. 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. Undocumented men were particularly hard hit by the pandemic, with their rate of job loss far exceeding the rate of job loss of legal immigrants.
    1. COVID-19 antibody tests have imperfect accuracy. There has been lack of clarity on the meaning of reported rates of false positives and false negatives. For risk assessment and clinical decision making, the rates of interest are the positive and negative predictive values of a test. Positive predictive value (PPV) is the chance that a person who tests positive has been infected. Negative predictive value (NPV) is the chance that someone who tests negative has not been infected. The medical literature regularly reports different statistics, sensitivity and specificity. Sensitivity is the chance that an infected person receives a positive test result. Specificity is the chance that a non-infected person receives a negative result. Knowledge of sensitivity and specificity permits one to predict the test result given a person’s true infection status. These predictions are not directly relevant to risk assessment or clinical decisions, where one knows a test result and wants to predict whether a person has been infected. Given estimates of sensitivity and specificity, PPV and NPV can be derived if one knows the prevalence of the disease, the rate of illness in the population. There is considerable uncertainty about the prevalence of COVID-19. This paper addresses the problem of inference on the PPV and NPV of COVID-19 antibody tests given estimates of sensitivity and specificity and credible bounds on prevalence. I explain the methodological problem, show how to estimate bounds on PPV and NPV, and apply the findings to some tests authorized by the FDA.
    1. Social distancing via shelter-in-place strategies has emerged as the most effective way to combat Covid-19. In the United States, choices about such policies are made by individual states. Here we show that the policy choice made by one state influences the incentives that other states face to adopt similar policies: they can be viewed as strategic complements in a supermodular game. If they satisfy the condition of uniform strict increasing differences then following Heal and Kunreuther ([6]) we show that if enough states engage in social distancing, they will tip others to do the same and thus shift the Nash equilibrium with respect to the number of states engaging in social distancing.
    1. As the COVID-19 pandemic progresses, researchers are reporting findings of randomized trials comparing standard care with care augmented by experimental drugs. The trials have small sample sizes, so estimates of treatment effects are imprecise. Seeing imprecision, clinicians reading research articles may find it difficult to decide when to treat patients with experimental drugs. Whatever decision criterion one uses, there is always some probability that random variation in trial outcomes will lead to prescribing sub-optimal treatments. A conventional practice when comparing standard care and an innovation is to choose the innovation only if the estimated treatment effect is positive and statistically significant. This practice defers to standard care as the status quo. To evaluate decision criteria, we use the concept of near optimality, which jointly considers the probability and magnitude of decision errors. An appealing decision criterion from this perspective is the empirical success rule, which chooses the treatment with the highest observed average patient outcome in the trial. Considering the design of recent and ongoing COVID-19 trials, we show that the empirical success rule yields treatment results that are much closer to optimal than those generated by prevailing decision criteria based on hypothesis tests.
    1. Amid the COVID-19 outbreak and related expected economic downturn, many developed and emerging market central banks around the world engaged in new long-term asset purchase programs, or so-called quantitative easing (QE) interventions. This paper conducts an event-study analysis of 24 COVID-19 QE announcements made by 21 global central banks on their local 10-year government bond yields. We find that the average developed market QE announcement had a statistically significant -0.14% 1-day impact, which is slightly smaller than past interventions during the Great Recession era. In contrast, the average impact of emerging market QE announcements was significantly larger, averaging -0.28% and -0.43% over 1-day and 3-day windows, respectively. Across developed and emerging bond markets, we estimate an overall average 1-day impact of -0.23%. We also show that all 10-year government bond yields in our sample rose sharply in mid-March 2020, but fell substantially after the period of QE announcements that we study in the paper.
    1. We use job vacancy data collected in real time by Burning Glass Technologies, as well as initial unemployment insurance (UI) claims data to study the impact of COVID-19 on the labor market. Our data allow us to track postings at disaggregated geography and by detailed occupation and industry. We find that job vacancies collapsed in the second half of March and are now 30% lower than their level at the beginning of the year. To a first approximation, this collapse was broad based, hitting all U.S. states, regardless of the intensity of the initial virus spread or timing of stay-at-home policies. UI claims also largely match these patterns. Nearly all industries and occupations saw contraction in postings and spikes in UI claims, regardless of whether they are deemed essential and whether they have work-from-home capability. The only major exceptions are in essential retail and nursing, the “front line” jobs most in-demand during the current crisis.
    1. The collapse of economic activity in 2020 from COVID-19 has been immense. An important question is how much of that resulted from government restrictions on activity versus people voluntarily choosing to stay home to avoid infection. This paper examines the drivers of the collapse using cellular phone records data on customer visits to more than 2.25 million individual businesses across 110 different industries. Comparing consumer behavior within the same commuting zones but across boundaries with different policy regimes suggests that legal shutdown orders account for only a modest share of the decline of economic activity (and that having county-level policy data is significantly more accurate than state-level data). While overall consumer traffic fell by 60 percentage points, legal restrictions explain only 7 of that. Individual choices were far more important and seem tied to fears of infection. Traffic started dropping before the legal orders were in place; was highly tied to the number of COVID deaths in the county; and showed a clear shift by consumers away from larger/busier stores toward smaller/less busy ones in the same industry. States repealing their shutdown orders saw identically modest recoveries--symmetric going down and coming back. The shutdown orders did, however, have significantly reallocate consumer activity away from “nonessential” to “essential” businesses and from restaurants and bars toward groceries and other food sellers.
    1. Violence against women is a problem worldwide, with economic costs ranging from 1-4% of global GDP. Using variation in the intensity of government-mandated lockdowns in India, we show that domestic violence complaints increase by 0.47 SD in districts with the strictest lockdown rules. We find similarly large increases in cybercrime complaints. Interestingly, rape and sexual assault complaints decrease 0.4 SD during the same period in districts with the strictest lockdowns, consistent with decreased female mobility in public spaces, public transport, and workplaces. Attitudes toward domestic violence play an important role in the reporting and incidence of domestic violence during the lockdown.
    1. In the midst of epidemics such as COVID-19, therapeutic candidates are unlikely to be able to complete the usual multiyear clinical trial and regulatory approval process within the course of an outbreak. We apply a Bayesian adaptive patient-centered model—which minimizes the expected harm of false positives and false negatives—to optimize the clinical trial development path during such outbreaks. When the epidemic is more infectious and fatal, the Bayesian-optimal sample size in the clinical trial is lower and the optimal statistical significance level is higher. For COVID-19 (assuming a static R0 – 2 and initial infection percentage of 0.1%), the optimal significance level is 7.1% for a clinical trial of a nonvaccine anti-infective therapeutic and 13.6% for that of a vaccine. For a dynamic R0 decreasing from 3 to 1.5, the corresponding values are 14.4% and 26.4%, respectively. Our results illustrate the importance of adapting the clinical trial design and the regulatory approval process to the specific parameters and stage of the epidemic.
    1. We quantify the causal impact of human mobility restrictions, particularly the lockdown of the city of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus (2019-nCoV). We employ a set of difference-in-differences (DID) estimations to disentangle the lockdown effect on human mobility reductions from other confounding effects including panic effect, virus effect, and the Spring Festival effect. We find that the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from Wuhan by 56.35%, and within-Wuhan movements by 54.15%. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities' new infection cases. We find, using simulations with these estimates, that the lockdown of the city of Wuhan on January 23, 2020 contributed significantly to reducing the total infection cases outside of Wuhan, even with the social distancing measures later imposed by other cities. We find that the COVID-19 cases would be 64.81% higher in the 347 Chinese cities outside Hubei province, and 52.64% higher in the 16 non-Wuhan cities inside Hubei, in the counterfactual world in which the city of Wuhan were not locked down from January 23, 2020. We also find that there were substantial undocumented infection cases in the early days of the 2019-nCoV outbreak in Wuhan and other cities of Hubei province, but over time, the gap between the officially reported cases and our estimated “actual” cases narrows significantly. We also find evidence that enhanced social distancing policies in the 63 Chinese cities outside Hubei province are effective in reducing the impact of population inflows from the epicenter cities in Hubei province on the spread of 2019-nCoV virus in the destination cities elsewhere.
    1. We assess the Covid-19 pandemic’s implications for state government sales and income tax revenues. We estimate that the economic declines implied by recent forecasts from the Congressional Budget Office will lead to a shortfall of roughly $106 billion in states’ sales and income tax revenues for the 2021 fiscal year. This is equivalent to 0.5 percent of GDP and 11.5 percent of our pre-Covid sales and income tax projection. Additional tax shortfalls from the second quarter of 2020 may amount to roughly $42 billion. We discuss how these revenue declines fit into several pieces of the broader economic context. These include other revenues (e.g., university tuition and fees) that are also at risk, as well as assets (e.g., pension plan holdings) that are at risk. Further dimensions of context include support enacted through several pieces of federal legislation, as well as spending needs necessitated by the public health crisis itself.
    1. As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported.
    1. Unlike most countries, Korea did not implement a lockdown in its battle against COVID-19, instead successfully relying on testing and contact tracing. Only one region, Daegu-Gyeongbuk (DG), had a significant number of infections, traced to a religious sect. This allows us to estimate the causal effect of the outbreak on the labor market using difference-in-differences. We find that a one per thousand increase in infections causes a 2 to 3 percent drop in local employment. Non-causal estimates of this coefficient from the US and UK, which implemented large-scale lockdowns, range from 5 to 6 percent, suggesting that at most half of the job losses in the US and UK can be attributed to lockdowns. We also find that employment losses caused by local outbreaks in the absence of lockdowns are (i) mainly due to reduced hiring by small establishments, (ii) concentrated in the accommodation/food, education, real estate, and transportation industries, and (iii) worst for the economically vulnerable workers who are less educated, young, in low-wage occupations, and on temporary contracts, even controlling for industry effects. All these patterns are similar to what we observe in the US and UK: The unequal effects of COVID-19 are the same with or without lockdowns. Our finding suggests that the lifting of lockdowns in the US and UK may lead to only modest recoveries in employment unless COVID-19 infection rates fall.
    1. Social distancing restrictions and demand shifts from COVID-19 are expected to shutter many small businesses, but there is very little early evidence on impacts. This paper provides the first analysis of impacts of the pandemic on the number of active small businesses in the United States using nationally representative data from the April 2020 CPS – the first month fully capturing early effects from the pandemic. The number of active business owners in the United States plummeted by 3.3 million or 22 percent over the crucial two-month window from February to April 2020. The drop in business owners was the largest on record, and losses were felt across nearly all industries and even for incorporated businesses. African-American businesses were hit especially hard experiencing a 41 percent drop. Latinx business owners fell by 32 percent, and Asian business owners dropped by 26 percent. Simulations indicate that industry compositions partly placed these groups at a higher risk of losses. Immigrant business owners experienced substantial losses of 36 percent. Female-owned businesses were also disproportionately hit by 25 percent. These findings of early-stage losses to small businesses have important policy implications and may portend longer-term ramifications for job losses and economic inequality.
    1. Since social distancing is the primary strategy for slowing the spread of many diseases, understanding why U.S. counties respond differently to COVID-19 is critical for designing effective public policies. Using daily data from about 45 million mobile phones to measure social distancing we examine how counties responded to both local COVID-19 cases and statewide shelter-in-place orders. We find that social distancing increases more in response to cases and official orders in counties where individuals historically (1) engaged less in community activities and (2) demonstrated greater willingness to incur individual costs to contribute to social objectives. Our work highlights the importance of these two features of social capital—community engagement and individual commitment to societal institutions—in formulating public health policies.
    1. We quantify the macroeconomic effects of COVID-19 for emerging markets using a SIR-multisector-small open economy model and calibrating it to Turkey. Domestic infection rates feed into both sectoral supply and sectoral demand shocks. Sectoral demand shocks also incorporate lower external demand due to foreign infection rates. Infection rates change endogenously with different lockdown policies. To calibrate the model, we use indicators of physical proximity and tele-workability of jobs to measure supply shocks. We use real-time credit card purchases to pin down demand shocks. Our results show that the optimal policy, which yields the lowest economic cost and saves the maximum number of lives, can be achieved under a full lockdown of 39 days. Partial and/or no lockdowns have higher economic costs as it takes longer to control the disease and hence to normalize the demand. Economic costs are much larger for an open economy because of the amplification role of international input-output linkages. Lower capital flows exacerbate this amplification as capital flows are the key form of financing for the production network. We document that sectors with stronger international input-output linkages and higher external debt suffer worse COVID losses and as a result have larger fiscal needs.
    1. The COVID-19 pandemic continues to have profound personal, public health and economic consequences worldwide. Since its onset, health care providers have worked tirelessly to treat adults and children facing this complex condition, and are consequently at increased risk for acute and long-term mental health conditions. Starting in late March, 2020, the Department of Psychiatry, University of Colorado School of Medicine, has launched COVID-19 related wellness programs for health care workers and staff across disciplines and medical settings. The services are designed to support colleagues in health care, promote their physical, emotional and relational well-being, and reduce their risk for adverse mental health issues. With funding from department, institutional, health system, philanthropic, state and federal sources, our interprofessional faculty and staff offer a range of wellness programs
    1. Researchers share how they have adapted fieldwork and collaborations in the face of travel bans and closed borders.
    1. Clinical prediction models to aid diagnosis, assess disease severity or prognosis have enormous potential to aid clinical decision making during the covid‐19 pandemic. A living systematic review has, so far, identified 145 covid‐19 prediction models published (or preprinted) between 03‐January‐2020 and 05‐May‐2020. Despite the considerable interest in developing covid‐19 prediction models, the review concluded that all models to date, with no exception, are at high risk of bias with concerns related to data quality, flaws in the statistical analysis and poor reporting, and none are recommended for use. Disappointingly, the recent study by Yang and colleagues describing the development of a prediction model to identify covid‐19 patients with severe disease, is no different. The study has failed to report important information needed to judge the study findings, but has numerous methodological concerns in design and analysis that deserve highlighting.
    1. Global lockdowns to halt the spread of the coronavirus will have a negligible impact on rising temperatures due to climate change, researchers have found. Lockdowns to stop the spread of the coronavirus caused huge falls in transport use, as well as reductions in industry and commercial operations, cutting the greenhouse gases and pollutants caused by vehicles and other activities. The impact is only short-lived, however, and analysis shows that even if some lockdown measures last until the end of 2021, global temperatures will only be 0.01°C lower than expected by 2030. Advertisement googletag.cmd.push(function() { googletag.display('mpu-mid-article'); }); But if countries choose a strong green stimulus route out of the pandemic, it could halve the temperature rises expected by 2050, says a team led by Piers Forster at the University of Leeds, UK. That gives the world a good chance of keeping temperature rises to the 1.5°C goal that countries signed up to under the international Paris climate agreement to prevent the most dangerous impacts of global warming.
    1. Deanna Montgomery realizes she doesn’t need to be at a laboratory bench to use her scientific experience — or to make a difference.
    1. The concepts of disease elimination and eradication mostly relate to immunisation programme outcomes. Disease eradication is the global reduction of infection to zero cases, whereas disease elimination is the absence of sustained endemic community transmission in a country or other geographical region.6WHOFramework for verifying elimination of measles and rubella.Wkly Epidemiol Rec. 2013; 88: 89-99PubMed Google Scholar With ongoing global SARS-CoV-2 transmission, reduction to zero cases in a defined region is only possible with stringent travel restrictions. For COVID-19, modelling estimates suggested that sustained restrictions that reduced travel by 90% to and from Wuhan, China, early in the spread of SARS-CoV-2, only modestly affected the epidemic trajectory to other regions of China.7Chinazzi M Davis JT Ajelli M et al.The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak.Science. 2020; 368: 395-400PubMed Google Scholar However, in Australia, travel bans were highly effective in controlling the spread of SARS-CoV-2 into Australia and averted a much larger epidemic.
    1. We know little about the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in African countries, including its infectiousness and the proportion of infected people who develop symptoms. Confined exposure of 2010 people on an aircraft carrier resulted in an infection rate of just 50%, and only 50% of infected people developed symptoms.2Lagneau L Covid-19: la contamination du porte-avions Charles de Gaulle garde ses mystères…pour le moment.http://www.opex360.com/2020/04/19/covid-19-la-contamination-du-porte-avions-charles-de-gaulle-garde-ses-mysteres-pour-le-moment/Date accessed: July 4, 2020Google Scholar Under less confined conditions, and similar to other circulating viruses that cause acute respiratory infections, SARS-CoV-2 might cause infection rates well below 30%, thus unable to provoke herd immunity but most probably causing recurring annual infections.Estimated infection fatality rates of around 0·3%3Streeck H Schulte B Kuemmerer B et al.Infection fatality rate of SARS-CoV-2 infection in a German community with a super-spreading event.medRxiv. 2020; (published online June 2.) (preprint).https://doi.org/10.1101/2020.05.04.20090076Google Scholar draw a much less dramatic picture of COVID-19-related deaths than predicted by Wells and colleagues, who presumed 95% of all Congolese will be infected, with an infection fatality rate of over 4%.1Wells CR Stearns JK Lutumba P Galvani AP COVID-19 on the African continent.Lancet Infect Dis. 2020; (published online May 6.)https://doi.org/10.1016/S1473-3099(20)30374-1Summary Full Text Full Text PDF Scopus (0) Google Scholar In DR Congo, we might thus estimate fewer than 40 000 attributable deaths compared with 800 000 Congolese people dying each year in the country.4countryeconomy.comGoogle ScholarDemocratic Republic of the Congo.https://countryeconomy.com/countries/democratic-republic-congoDate accessed: July 4, 2020Google Scholar Such estimates put the prioritisation of this disease over other health threats on the continent immediately into question.
    1. We frequently find ourselves giving the same advice to different students on how to write rebuttals. So we thought we’d write it up. Our experience is with AI conferences (e.g., CVPR, ECCV, ICCV, NeurIPS, ICLR, EMNLP).The core guiding principle is that the rebuttal should be thorough, direct, and easy for the Reviewers and Area Chair (RACs) to follow.
    1. Social media poses a threat to public health by facilitating the spread of misinformation. At the same time, however, social media offers a promising avenue to stem the distribution of false claims – as evidenced by real-time corrections, crowdsourced fact-checking, and algorithmic tagging. Despite the growing attempts to correct misinformation on social media, there is still considerable ambiguity regarding the ability to effectively ameliorate the negative impact of false messages. To address this gap, the current study uses a meta-analysis to evaluate the relative impact of social media interventions designed to correct health-related misinformation (k = 24; N = 6,086). Additionally, the meta-analysis introduces theory-driven moderators that help delineate the effectiveness of social media interventions. The mean effect size of attempts to correct misinformation on social media was positive and significant (d = 0.40, 95% CI [0.25, 0.55], p =.0005) and a publication bias could not be excluded. Interventions were more effective in cases where participants were involved with the health topic, as well as when misinformation was distributed by news organizations (vs. peers) and debunked by experts (vs. non-experts). The findings of this meta-analysis can be used not only to depict the current state of the literature but also to prescribe specific recommendations to better address the proliferation of health misinformation on social media.
    1. The UK faces a second wave of coronavirus infections this winter if the country’s testing and contact tracing system doesn’t improve by the time schools fully reopen and people return to workplaces, researchers have warned.
    1. Extensive empirical evidence suggests that there is a maximal number of people with whom an individual can maintain stable social relationships (the Dunbar number). We argue that this arises as a consequence of a natural phase transition in the dynamic self-organization among N individuals within a social system. We present the calculated size dependence of the scaling properties of complex social network models to argue that this collective behavior is an enhanced form of collective intelligence. Direct calculation establishes that the complexity of social networks as measured by their scaling behavior is nonmonotonic, peaking around 150, thereby providing a theoretical basis for the value of the Dunbar number. Thus, we establish a theory-based bridge spanning the gap between sociology and psychology.
    1. The COVID-19 pandemic has reshaped the demand for goods and services worldwide. The combination of a public health emergency, economic distress, and disinformation-driven panic have pushed customers and vendors towards the shadow economy. In particular Dark Web Marketplaces (DWMs), commercial websites easily accessible via free software, have gained significant popularity. Here, we analyse 472,372 listings extracted from 23 DWMs between January 1, 2020 and July 7, 2020. We identify 518 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds(e.g., vaccines). Finally, we compare trends in their temporal evolution with variations in public attention, as measured by Twitter posts and Wikipedia page visits. We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs, especially when real vaccines or cures become available and are potentially in short supply. We anticipate our analysis will be of interest both to researchers and public agencies focused on the protection of public health.
    1. Modern large engineered network systems normally work in cooperation and incorporate dependencies between their components for purposes of efficiency and regulation. Such dependencies may become a major risk since they can cause small-scale failures to propagate throughout the system. Thus, the dependent nodes could be a natural target for malicious attacks that aim to exploit these vulnerabilities. Here we consider a type of targeted attack that is based on the dependencies between the networks. We study strategies of attacks that range from dependency-first to dependency-last, where a fraction 1−p<math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mn>1</mn><mo>−</mo><mi>p</mi></mrow></math> of the nodes with dependency links, or nodes without dependency links, respectively, are initially attacked. We systematically analyze, both analytically and numerically, the percolation transition of partially interdependent networks, where a fraction q<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>q</mi></math> of the nodes in each network are dependent on nodes in the other network. We find that for a broad range of dependency strength q<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>q</mi></math>, the “dependency-first” attack strategy is actually less effective, in terms of lower critical percolation threshold pc<math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>p</mi><mi>c</mi></msub></math>, compared with random attacks of the same size. In contrast, the “dependency-last” attack strategy is more effective, i.e., higher pc<math xmlns="http://www.w3.org/1998/Math/MathML"><msub><mi>p</mi><mi>c</mi></msub></math>, compared with a random attack. This effect is explained by exploring the dynamics of the cascading failures initiated by dependency-based attacks. We show that while “dependency-first” strategy increases the short-term impact of the initial attack, in the long term the cascade slows down compared with the case of random attacks and vice versa for “dependency-last.” Our results demonstrate that the effectiveness of attack strategies over a system of interdependent networks should be evaluated not only by the immediate impact but mainly by the accumulated damage during the process of cascading failures. This highlights the importance of understanding the dynamics of avalanches that may occur due to different scenarios of failures in order to design resilient critical infrastructures.
    1. Those who sense that this grand experiment in working from home comes with plenty of downsides — longer days, more meetings and more emails to answer — are now backed up by data
    1. There have been several attempts to predict mortality from COVID-19 in the UK, including calculation of age-based case fatality rates1Verity R Okell LC Dorigatti I et al.Estimates of the severity of coronavirus disease 2019: a model-based analysis.Lancet Infect Dis. 2020; 20: 669-677Summary Full Text Full Text PDF PubMed Scopus (191) Google Scholar and relative risk (RR) of mortality.2Banerjee A Pasea L Harris S et al.Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study.Lancet. 2020; 395: 1715-1725Summary Full Text Full Text PDF PubMed Scopus (9) Google Scholar David Spiegelhalter said that “roughly speaking, we might say that getting COVID-19 is like packing a year's worth of risk into a week or two”.3Spiegelhalter D How much “normal” risk does COVID represent?.https://medium.com/wintoncentre/how-much-normal-risk-does-covid-represent-4539118e1196Date: March 21, 2020Date accessed: June 29, 2020Google ScholarIn response to these predictions, we decided to calculate the excess mortality in the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) cohort. The RCGP RSC cohort has been recruited to be nationally representative,4de Lusignan S Dorward J Correa A et al.Risk factors for SARS-CoV-2 among patients in the Oxford Royal College of General Practitioners Research and Surveillance Centre primary care network: a cross-sectional study.Lancet Infect Dis. 2020; (published online May 15.)https://doi.org/10.1016/S1473-3099(20)30371-6Summary Full Text Full Text PDF PubMed Google Scholar and the mortality data for the cohort align well with those from the Office of National Statistics (ONS; appendix p 1).
    1. As the initial phase of the COVID-19 pandemic passes its peak in many countries, serological studies are becoming increasingly important in guiding public health responses. Antibody testing is crucial for monitoring the evolution of the pandemic, providing a more complete picture of the total number of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than molecular diagnostic testing alone.1Cheng MP Yansouni CP Basta NE et al.Serodiagnostics for severe acute respiratory syndrome-related coronavirus-2.Ann Intern Med. 2020; (published online June 4.)https://doi.org/10.7326/M20-2854Crossref Scopus (44) Google Scholar All individuals with SARS-CoV-2-specific antibodies have been exposed to the virus, so antibody testing can highlight differences in past exposure between regions, demographic groups, and occupations.2Metcalf CJE Farrar J Cutts FT et al.Use of serological surveys to generate key insights into the changing global landscape of infectious disease.Lancet. 2016; 388: 728-730Summary Full Text Full Text PDF PubMed Google Scholar Seroprevalence estimates can also be used to estimate the infection fatality rate.3Erikstrup C Hother CE Pedersen OBV et al.Estimation of SARS-CoV-2 infection fatality rate by real-time antibody screening of blood donors.medRxiv. 2020; (published online April 28.) (preprint).https://doi.org/10.1101/2020.04.24.20075291Google Scholar Dashboards that visualise COVID-19 cases confirmed by diagnostic testing have been pivotal in enabling policy makers and researchers to monitor the pandemic.4Dong E Du H Gardner L An interactive web-based dashboard to track COVID-19 in real time.Lancet Infect Dis. 2020; 20: 533-534Summary Full Text Full Text PDF PubMed Scopus (387) Google Scholar Yet, despite the value of antibody testing, there is no unified resource for seroprevalence estimates.To address this need, we created SeroTracker, a custom-built dashboard that systematically monitors and synthesises findings from hundreds of global SARS-CoV-2 serological studies. The dashboard allows users to visualise seroprevalence estimates on a world map and compare estimates between regions, population groups, and testing modalities (eg, assay type or antibody isotype).
    1. Our understanding of how stress affects primary school children’s attention and learning has developed rapidly. We know that children experience differing levels of stressors (factors that cause stress) at home, and that this can influence how they respond to new stressors when they occur in educational contexts. Here, we review evidence showing that stress can increase children’s attention and learning capacities in some circumstance but hinder them in others. We show how children differ in their attention and learning styles, dependent on stress levels: for example, more highly stressed children may be more distracted by superficial features and may find it harder to engage in planning and voluntary control. We review intervention research on stress management techniques in children, concentrating on psychological techniques (such as mindfulness and stress reappraisal), physiological techniques (such as breathing exercises) and environmental factors (such as noise). At the current time, teachers’ awareness of the differing stress response of their pupils may be the most effective factor in helping them accommodate the needs of the children in their classrooms.
    1. osfr provides a (hopefully) convenient R interface to OSF (Open Science Framework, https://www.osf.io), a free service for managing research developed by the Center for Open Science (COS). osfr completed its rOpenSci peer-review earlier this year and has been available on CRAN since February. Throughout its development and since its release I’ve had numerous conversations with members of the R community about OSF (and osfr), and through these interactions a couple recurring patterns emerged. First, it seems that many R users have heard of OSF but relatively few have first-hand experience with it. Second, I’m often asked how OSF compares to GitHub and whether it would even be useful for someone who already uses GitHub to manage their research. In a future post I’ll highlight some features of osfr and demonstrate how it can help form the basis of efficient and inclusive research workflows. However, before you can extract any value from osfr, you need to be an OSF user first. And so, I wanted to take this opportunity to provide a little background about OSF, what it offers, how it differs from something like GitHub, and where it might fit into your workflow as an R/GitHub user. Before diving in, I want to acknowledge that OSF is a multi-faceted product, and includes a number of services under its umbrella, including things like pre-print servers and a research registration repository, which, while incredibly cool and noteworthy, fall outside the scope of this post, which focuses on project management.
    1. Research on health misinformation has grown rapidly as concerns about the potential harmful effects of health misinformation on individuals and society intensify amid a “post-truth” era. In this chapter, we provide a broad overview of current research and evidence concerning the many facets of health misinformation, including its sources, prevalence, characteristics (both content and diffusion features), impact, and mitigation. We conclude that health misinformation originates from many sources, most notably mass and social media, is fairly prevalent, both in interpersonal and mediated settings, and tends to feature negative sentiments, anecdotal evidence, and anti-science narratives. While there is no conclusive evidence that health misinformation spreads more broadly than scientific information, health misinformation reliably leads to misperceptions on health issues. Efforts to mitigate the impact of health misinformation show early promise in correcting misperceptions. We offer several directions for future research, including a call for more investigations on the impact of health misinformation and correcting messages on actual behaviors.
    1. We provide an interim report on the Indian lockdown provoked by the covid-19 pandemic. The main topics — ranging from the philosophy of lockdown to the provision of relief measures — transcend the Indian case. A recurrent theme is the enormous visibility of covid-19 deaths worldwide, with Governments everywhere propelled to respect this visibility, developing countries perhaps even more so. In advanced economies, the cost of achieving this reduction in visible deaths is “merely” a dramatic reduction in overall economic activity, coupled with far-reaching measures to compensate those who bear such losses. But for India, a developing country with great sectoral and occupational vulnerabilities, this dramatic reduction is more than economic: it means lives lost. These lost lives, through violence, starvation, indebtedness and extreme stress (both psychological and physiological) are invisible. It is this conjunction of visibility and invisibility that drives the Indian response. The lockdown meets all international standards so far; the relief package none.
    1. We show that unexpected changes in the trajectory of COVID-19 infections predict US stock returns, in real time. Parameter estimates indicate that an unanticipated doubling (halving) of projected infections forecasts next-day decreases (increases) in aggregate US market value of 4 to 11 percent, indicating that equity markets may begin to rebound even as infections continue to rise, if the trajectory of the disease becomes less severe than initially anticipated. Using the same variation in unanticipated projected cases, we find that COVID-19-related losses in market value at the firm level rise with capital intensity and leverage, and are deeper in industries more conducive to disease transmission. These relationships provide important insight into current record job losses. Measuring US states' drops in market value as the employment weighted average declines of the industries they produce, we find that states with milder drops in market value exhibit larger initial jobless claims per worker. This initially counter-intuitive result suggests that investors value the relative ease with which labor versus capital costs can be shed as revenues decline.
    1. In the early stages of the COVID-19 pandemic, international testing efforts tended to target individuals whose symptoms and/or jobs placed them at a high presumed risk of infection. Testing regimes of this sort potentially result in a high proportion of cases going undetected. Quantifying this parameter, which we refer to as the undetected rate, is an important contribution to the analysis of the early spread of the SARS-CoV-2 virus. We show that partial identification techniques can credibly deal with the data problems that common COVID-19 testing programs induce (i.e. excluding quarantined individuals from testing and low participation in random screening programs). We use public data from two Icelandic testing regimes during the first month of the outbreak and estimate an identified interval for the undetected rate. Our main approach estimates that the undetected rate was between 89% and 93% before the medical system broadened its eligibility criteria and between 80% and 90% after.
    1. Sparked by the killing of George Floyd in police custody, the 2020 Black Lives Matter protests have brought a new wave of attention to the issue of inequality within criminal justice. However, many public health officials have warned that mass protests could lead to a reduction in social distancing behavior, spurring a resurgence of COVID-19. This study uses newly collected data on protests in 315 of the largest U.S. cities to estimate the impacts of mass protests on social distancing, COVID-19 case growth, and COVID-19-related deaths. Event-study analyses provide strong evidence that net stay-at-home behavior increased following protest onset, consistent with the hypothesis that non-protesters’ behavior was substantially affected by urban protests. This effect was not fully explained by the imposition of city curfews. Estimated effects were generally larger for persistent protests and those accompanied by media reports of violence. Furthermore, we find no evidence that urban protests reignited COVID-19 case or death growth after more than five weeks following the onset of protests. We conclude that predictions of population-level spikes in COVID-19 cases from Black Lives Matter protests were too narrowly conceived because of failure to account for non-participants’ behavioral responses to large gatherings.
    1. We analyze the effectiveness of preventive investments aimed at increasing agents' life expectancy, with a focus on influenza and COVID-19 mitigation. Maximizing overall life expectancy requires allocating resources across hazards so as to equalize investments' marginal effectiveness. Based on estimates for the marginal effectiveness of influenza vaccines, we determine the level of COVID-19 mitigation investments that would imply such equalization. Given current projections for COVID-19 mitigation costs, our results suggest that wide-spread influenza vaccination would be an effective life-preserving investment.
    1. What would a hypothetical one million US deaths in the Covid-19 epidemic mean for mortality of individuals at the population level? To put estimates of Covid-19 mortality into perspective, we estimate age-specific mortality for an epidemic claiming for illustrative purposes one million US lives, with results scalable over a broad range of deaths. We calculate the impact on period life expectancy (down 3 years) and remaining life-years (12.3 years per death), which for one million deaths can be valued at six to 10 trillion dollars. The age-patterns of Covid-19 mortality observed in other countries are remarkably similar and exhibit the typical rate of increase by age of normal mortality. The scenario of one million Covid-19 deaths is similar in scale to the decades-long HIV/AIDS and opioid-overdose epidemics but considerably smaller than the Spanish Flu of 1918. Unlike HIV/AIDS and opioid epidemics, the Covid-19 deaths will be concentrated in months rather than spread out over decades.
    1. Both the White House and state governors have explicitly linked thresholds of reduced COVID-19 case growth to the lifting of statewide shelter-in-place orders (SIPOs). This “hardwired” policy endogeneity creates empirical challenges in credibly isolating the causal effect of lifting a statewide SIPO on COVID-19-related health. To break this simultaneity problem, the current study exploits a unique natural experiment generated by a Wisconsin Supreme Court decision. On May 13, 2020, the Wisconsin Supreme Court abolished the state’s “Safer at Home” order, ruling that the Wisconsin Department of Health Services unconstitutionally usurped legislative authority to review COVID-19 regulations. We capitalize on this sudden, dramatic, and largely unanticipated termination of a statewide SIPO to estimate its effect on social distancing and COVID-19 case growth. Using a synthetic control design, we find no evidence that the repeal of the state SIPO impacted social distancing, COVID-19 cases, or COVID-19-related mortality during the fortnight following enactment. Estimated effects were economically small and nowhere near statistically different from zero. We conclude that the impact of shelter-in-place orders is likely not symmetric across enactment and lifting of the orders.
    1. Covid-19 is the single largest threat to global public health since the Spanish Influenza pandemic of 1918-20. Was the world better prepared in 2020 than it was in 1918? After a century of public health and basic science research, pandemic response and mortality outcomes should be better than in 1918-20. We ask whether mortality from historical pandemics has any predictive content for mortality in the ongoing Covid-19 pandemic. We find a strong persistence in public health performance in the early days of the Covid-19 pandemic. Places that performed poorly in terms of mortality in 1918 were more likely to have higher mortality today. This is true across countries and across a sample of US cities. Experience with SARS is associated with lower mortality today. Distrust of expert advice, lack of cooperation at many levels, over-confidence, and health care supply shortages have likely promoted higher mortality today as in the past.
    1. This paper seeks to understand whether a catastrophic and urgent event, such as the first months of the COVID-19 pandemic, accelerates or reverses trends in international collaboration, especially in and between China and the United States. A review of research articles produced in the first months of the COVID-19 pandemic shows that COVID-19 research had smaller teams and involved fewer nations than pre-COVID-19 coronavirus research. The United States and China were, and continue to be in the pandemic era, at the center of the global network in coronavirus related research, while developing countries are relatively absent from early research activities in the COVID-19 period. Not only are China and the United States at the center of the global network of coronavirus research, but they strengthen their bilateral research relationship during COVID-19, producing more than 4.9% of all global articles together, in contrast to 3.6% before the pandemic. In addition, in the COVID-19 period, joined by the United Kingdom, China and the United States continued their roles as the largest contributors to, and home to the main funders of, coronavirus related research. These findings suggest that the global COVID-19 pandemic shifted the geographic loci of coronavirus research, as well as the structure of scientific teams, narrowing team membership and favoring elite structures. These findings raise further questions over the decisions that scientists face in the formation of teams to maximize a speed, skill trade-off. Policy implications are discussed.
    1. Hydroxychloroquine, used to treat malaria and some autoimmune disorders, potently inhibits viral infection of SARS coronavirus (SARS-CoV-1) and SARS-CoV-2 in cell-culture studies. However, human clinical trials of hydroxychloroquine failed to establish its usefulness as treatment for COVID-19. This compound is known to interfere with endosomal acidification necessary to the proteolytic activity of cathepsins. Following receptor binding and endocytosis, cathepsin L can cleave the SARS-CoV-1 and SARS-CoV-2 spike (S) proteins, thereby activating membrane fusion for cell entry. The plasma membrane-associated protease TMPRSS2 can similarly cleave these S proteins and activate viral entry at the cell surface. Here we show that the SARS-CoV-2 entry process is more dependent than that of SARS-CoV-1 on TMPRSS2 expression. This difference can be reversed when the furin-cleavage site of the SARS-CoV-2 S protein is ablated. We also show that hydroxychloroquine efficiently blocks viral entry mediated by cathepsin L, but not by TMPRSS2, and that a combination of hydroxychloroquine and a clinically-tested TMPRSS2 inhibitor prevents SARS-CoV-2 infection more potently than either drug alone. These studies identify functional differences between SARS-CoV-1 and -2 entry processes, and provide a mechanistic explanation for the limited in vivo utility of hydroxychloroquine as a treatment for COVID-19.
    1. The COVID-19 pandemic has led to accelerated efforts to develop therapeutics and vaccines. A key target of these efforts is the spike (S) protein, which is metastable and difficult to produce recombinantly. Here, we characterized 100 structure-guided spike designs and identified 26 individual substitutions that increased protein yields and stability. Testing combinations of beneficial substitutions resulted in the identification of HexaPro, a variant with six beneficial proline substitutions exhibiting ~10-fold higher expression than its parental construct and the ability to withstand heat stress, storage at room temperature, and three freeze-thaw cycles. A 3.2 Å-resolution cryo-EM structure of HexaPro confirmed that it retains the prefusion spike conformation. High-yield production of a stabilized prefusion spike protein will accelerate the development of vaccines and serological diagnostics for SARS-CoV-2.
    1. What is already known about this topic? Older adults and those with chronic obstructive pulmonary disease, heart disease, diabetes, chronic kidney disease, and obesity are at higher risk for severe COVID-19–associated illness. What is added by this report? The median model-based estimate of the prevalence of any of five underlying medical conditions associated with increased risk for severe COVID-19–associated illness among U.S. adults was 47.2% among 3,142 U.S. counties. The estimated number of persons with these conditions followed population distributions, but prevalence was higher in more rural counties. What are the implications for public health practice? The findings can help local decision-makers identify areas at higher risk for severe COVID-19 illness in their jurisdictions and guide resource allocation and implementation of community mitigation strategies.
    1. BackgroundThis is the first randomised controlled trial for assessment of the immunogenicity and safety of a candidate non-replicating adenovirus type-5 (Ad5)-vectored COVID-19 vaccine, aiming to determine an appropriate dose of the candidate vaccine for an efficacy study.MethodsThis randomised, double-blind, placebo-controlled, phase 2 trial of the Ad5-vectored COVID-19 vaccine was done in a single centre in Wuhan, China. Healthy adults aged 18 years or older, who were HIV-negative and previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-free, were eligible to participate and were randomly assigned to receive the vaccine at a dose of 1 × 1011 viral particles per mL or 5 × 1010 viral particles per mL, or placebo. Investigators allocated participants at a ratio of 2:1:1 to receive a single injection intramuscularly in the arm. The randomisation list (block size 4) was generated by an independent statistician. Participants, investigators, and staff undertaking laboratory analyses were masked to group allocation. The primary endpoints for immunogenicity were the geometric mean titres (GMTs) of specific ELISA antibody responses to the receptor binding domain (RBD) and neutralising antibody responses at day 28. The primary endpoint for safety evaluation was the incidence of adverse reactions within 14 days. All recruited participants who received at least one dose were included in the primary and safety analyses. This study is registered with ClinicalTrials.gov, NCT04341389.Findings603 volunteers were recruited and screened for eligibility between April 11 and 16, 2020. 508 eligible participants (50% male; mean age 39·7 years, SD 12·5) consented to participate in the trial and were randomly assigned to receive the vaccine (1 × 1011 viral particles n=253; 5 × 1010 viral particles n=129) or placebo (n=126). In the 1 × 1011 and 5 × 1010 viral particles dose groups, the RBD-specific ELISA antibodies peaked at 656·5 (95% CI 575·2–749·2) and 571·0 (467·6–697·3), with seroconversion rates at 96% (95% CI 93–98) and 97% (92–99), respectively, at day 28. Both doses of the vaccine induced significant neutralising antibody responses to live SARS-CoV-2, with GMTs of 19·5 (95% CI 16·8–22·7) and 18·3 (14·4–23·3) in participants receiving 1 × 1011 and 5 × 1010 viral particles, respectively. Specific interferon γ enzyme-linked immunospot assay responses post vaccination were observed in 227 (90%, 95% CI 85–93) of 253 and 113 (88%, 81–92) of 129 participants in the 1 × 1011 and 5 × 1010 viral particles dose groups, respectively. Solicited adverse reactions were reported by 183 (72%) of 253 and 96 (74%) of 129 participants in the 1 × 1011 and 5 × 1010 viral particles dose groups, respectively. Severe adverse reactions were reported by 24 (9%) participants in the 1 × 1011 viral particles dose group and one (1%) participant in the 5 × 1010 viral particles dose group. No serious adverse reactions were documented.InterpretationThe Ad5-vectored COVID-19 vaccine at 5 × 1010 viral particles is safe, and induced significant immune responses in the majority of recipients after a single immunisation.
    1. The COVID-19 pandemic, which is caused by the novel coronavirus SARS-CoV-2, has been associated with more than 470,000 fatal cases worldwide. In order to develop antiviral interventions quickly, drugs used for treatment of unrelated diseases are currently being repurposed to combat COVID-19. Chloroquine is a anti-malaria drug that is frequently employed for COVID-19 treatment since it inhibits SARS-CoV-2 spread in the kidney-derived cell line Vero1–3. Here, we show that engineered expression of TMPRSS2, a cellular protease that activates SARS-CoV-2 for entry into lung cells4, renders SARS-CoV-2 infection of Vero cells insensitive to chloroquine. Moreover, we report that chloroquine does not block SARS-CoV-2 infection of the TMPRSS2-positive lung cell line Calu-3. These results indicate that chloroquine targets a pathway for viral activation that is not operative in lung cells and is unlikely to protect against SARS-CoV-2 spread in and between patients.
    1. As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads, the susceptible subpopulation declines causing the rate at which new infections occur to slow down. Variation in individual susceptibility or exposure to infection exacerbates this effect. Individuals that are more susceptible or more exposed tend to be infected and removed from the susceptible subpopulation earlier. This selective depletion of susceptibles intensifies the deceleration in incidence. Eventually, susceptible numbers become low enough to prevent epidemic growth or, in other words, the herd immunity threshold is reached. Here we fit epidemiological models with inbuilt distributions of susceptibility or exposure to SARS-CoV-2 outbreaks to estimate basic reproduction numbers (R_0) alongside coefficients of individual variation (CV) and the effects of containment strategies. Herd immunity thresholds are then calculated as 1-(1⁄R_0 )^(1⁄((1+〖CV〗^2 ) )) or 1-(1⁄R_0 )^(1⁄((1+〖2CV〗^2 ) )), depending on whether variation is on susceptibility or exposure. Our inferences result in herd immunity thresholds around 10-20%, considerably lower than the minimum coverage needed to interrupt transmission by random vaccination, which for R_0 higher than 2.5 is estimated above 60%. We emphasize that the classical formula, 1-1⁄R_0 , remains applicable to describe herd immunity thresholds for random vaccination, but not for immunity induced by infection which is naturally selective. These findings have profound consequences for the governance of the current pandemic given that some populations may be close to achieving herd immunity despite being under more or less strict social distancing measures.
    1. Importance  Reported cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection likely underestimate the prevalence of infection in affected communities. Large-scale seroprevalence studies provide better estimates of the proportion of the population previously infected.Objective  To estimate prevalence of SARS-CoV-2 antibodies in convenience samples from several geographic sites in the US.Design, Setting, and Participants  This cross-sectional study performed serologic testing on a convenience sample of residual sera obtained from persons of all ages. The serum was collected from March 23 through May 12, 2020, for routine clinical testing by 2 commercial laboratory companies. Sites of collection were San Francisco Bay area, California; Connecticut; south Florida; Louisiana; Minneapolis-St Paul-St Cloud metro area, Minnesota; Missouri; New York City metro area, New York; Philadelphia metro area, Pennsylvania; Utah; and western Washington State.Exposures  Infection with SARS-CoV-2.Main Outcomes and Measures  The presence of antibodies to SARS-CoV-2 spike protein was estimated using an enzyme-linked immunosorbent assay, and estimates were standardized to the site populations by age and sex. Estimates were adjusted for test performance characteristics (96.0% sensitivity and 99.3% specificity). The number of infections in each site was estimated by extrapolating seroprevalence to site populations; estimated infections were compared with the number of reported coronavirus disease 2019 (COVID-19) cases as of last specimen collection date.Results  Serum samples were tested from 16 025 persons, 8853 (55.2%) of whom were women; 1205 (7.5%) were 18 years or younger and 5845 (36.2%) were 65 years or older. Most specimens from each site had no evidence of antibodies to SARS-CoV-2. Adjusted estimates of the proportion of persons seroreactive to the SARS-CoV-2 spike protein antibodies ranged from 1.0% in the San Francisco Bay area (collected April 23-27) to 6.9% of persons in New York City (collected March 23-April 1). The estimated number of infections ranged from 6 to 24 times the number of reported cases; for 7 sites (Connecticut, Florida, Louisiana, Missouri, New York City metro area, Utah, and western Washington State), an estimated greater than 10 times more SARS-CoV-2 infections occurred than the number of reported cases.Conclusions and Relevance  During March to early May 2020, most persons in 10 diverse geographic sites in the US had not been infected with SARS-CoV-2 virus. The estimated number of infections, however, was much greater than the number of reported cases in all sites. The findings may reflect the number of persons who had mild or no illness or who did not seek medical care or undergo testing but who still may have contributed to ongoing virus transmission in the population.
    1. BackgroundThe risk of vertical and perinatal transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, which causes COVID-19), the most appropriate management, and the neonate's risk of developing COVID-19 during the perinatal period are unknown. Therefore, we aimed to elucidate best practices regarding infection control in mother–newborn dyads, and identify potential risk factors associated with transmission.MethodsIn this observational cohort study, we identified all neonates born between March 22 and May 17, 2020, at three New York Presbyterian Hospitals in New York City (NY, USA) to mothers positive for SARS-CoV-2 at delivery. Mothers could practice skin-to-skin care and breastfeed in the delivery room, but had to wear a surgical mask when near their neonate and practice proper hand hygiene before skin-to-skin contact, breastfeeding, and routine care. Unless medically required, neonates were kept in a closed Giraffe isolette in the same room as their mothers, and were held by mothers for feeding after appropriate hand hygiene, breast cleansing, and placement of a surgical mask. Neonates were tested for SARS-CoV-2 by use of real-time PCR on nasopharyngeal swabs taken at 24 h, 5–7 days, and 14 days of life, and were clinically evaluated by telemedicine at 1 month of age. We recorded demographics, neonatal, and maternal clinical presentation, as well as infection control practices in the hospital and at home.FindingsOf 1481 deliveries, 116 (8%) mothers tested positive for SARS-CoV-2; 120 neonates were identified. All neonates were tested at 24 h of life and none were positive for SARS-CoV-2. 82 (68%) neonates completed follow-up at day 5–7 of life. Of the 82 neonates, 68 (83%) roomed in with the mothers. All mothers were allowed to breastfeed; at 5–7 days of life, 64 (78%) were still breastfeeding. 79 (96%) of 82 neonates had a repeat PCR at 5–7 days of life, which was negative in all; 72 (88%) neonates were also tested at 14 days of life and none were positive. None of the neonates had symptoms of COVID-19.InterpretationOur data suggest that perinatal transmission of COVID-19 is unlikely to occur if correct hygiene precautions are undertaken, and that allowing neonates to room in with their mothers and direct breastfeeding are safe procedures when paired with effective parental education of infant protective strategies.
    1. Health officials are concerned about why some people who test positive for the coronavirus never feel sick. Could it be the luck of genetics? The blessings of youth? Or something else?
    1. Reports of reinfection instead may be cases of drawn-out illness. A decline in antibodies is normal after a few weeks, and people are protected from the coronavirus in other ways.
    1. Biologically, a vaccine against the COVID-19 virus is unlikely to offer complete protection. Logistically, manufacturers will have to make hundreds of millions of doses while relying, perhaps, on technology never before used in vaccines and competing for basic supplies such as glass vials. Then the federal government will have to allocate doses, perhaps through a patchwork of state and local health departments with no existing infrastructure for vaccinating adults at scale. The Centers for Disease Control and Prevention, which has led vaccine distribution efforts in the past, has been strikingly absent in discussions so far—a worrying sign that the leadership failures that have characterized the American pandemic could also hamper this process. To complicate it all, 20 percent of Americans already say they will refuse to get a COVID-19 vaccine, and with another 31 percent unsure, reaching herd immunity could be that much more difficult.
    1. Radical public health responses to the pandemic around the world have asked us to make unprecedented changes to our daily lives. Social distancing measures require compliance with recommendations, instructions, and legal orders that come with undeniable sacrifices for almost all of us (though these sacrifices are far from equally distributed). These extreme public measures depend for their success on public trust.
    1. The UK is ‘locked down’ because of coro­n­avirus (COVID-19). No clear exit strategy currently exists. This paper suggests a possible way forward that combines elements from economics and epi­demi­ol­ogy. The paper proposes as a policy a ‘release’ from lockdown of the young cohort of UK citizens aged between age 20 and 30 who do not live with parents. The paper cal­cu­lates that there are ap­prox­i­mately 4.2 million UK in­di­vid­u­als who fall into this 20-30 ageband and who live outside the original parental home. Of those, 2.6 million work in the private sector, so unless some cor­rec­tive action is taken they are likely to be extremely harshly affected, fi­nan­cially, when compared to employees in the public sector. The paper argues that a young-​workforce release of this kind would lead to sub­stan­tial economic and societal benefits without enormous health costs to the country. In this way, the nation might begin to move forward in the footsteps of the young. The paper’s key concept could in principle be im­ple­mented in other countries.
    1. Preprint servers have existed for decades, but the fight against the coronavirus has seen their use soar. They’re changing how science is done—but need important guardrails.
    1. COVID-19 is spreading and has reached the state of a worldwide pandemic and health systems are or will be tested in how they can deal with it. So far, during this early phase of the pandemic, outcomes in terms of case-​fatality rates (CFR) differ widely across countries. We explore how dif­fer­ences in living arrange­ments of gen­er­a­tions within families con­tribute to the cross country dif­fer­ences. We document a strong positive cor­re­la­tion between countries’ CFRs and the share of working-​age families living with their parents. This suggest that policy needs to focus on inter-​generational social distance when combating this pandemic.
    1. New York City is the hot spot of the COVID-19 pandemic in the United States. This paper merges in­for­ma­tion on the number of tests and the number of in­fec­tions at the New York City zip code level with de­mo­graphic and so­cioe­co­nomic in­for­ma­tion from the decennial census and the American Community Surveys. People residing in poor or immigrant neigh­bor­hoods were less likely to be tested; but the like­li­hood that a test was positive was larger in those neigh­bor­hoods, as well as in neigh­bor­hoods with larger house­holds or pre­dom­i­nantly black pop­u­la­tions. The rate of infection in the pop­u­la­tion depends on both the frequency of tests and on the fraction of positive tests among those tested. The non-​randomness in testing across New York City neigh­bor­hoods indicates that the observed cor­re­la­tion between the rate of infection and the so­cioe­co­nomic char­ac­ter­is­tics of a community tells an in­com­plete story of how the pandemic evolved in a congested urban setting.
    1. It is almost certain that the world economy is entering a recession of historic pro­por­tions; how bad things get will depend on how gov­ern­ments manage the Covid-19 pandemic. At the core of the problem lies a very difficult choice: whether to “flatten the curve” of the epidemic or whether to flatten the curve of the recession. It is unlikely that both can be achieved and, in this case, it is better to address the tradeoff heads-on rather than try to ignore it or assume it doesn’t exist. Because de­vel­op­ing countries are less prepared to deal with the con­se­quences of an economic downturn, they might not be able to afford “social dis­tanc­ing” policies for extended periods.
    1. What is the response of US governors to the COVID-19 pandemic? In this research note, we explore the de­ter­mi­nants of im­ple­ment­ing stay-​at-home orders, focusing on governors’ char­ac­ter­is­tics. In our most con­ser­v­a­tive estimate, being a De­mo­c­ra­tic governor increases the prob­a­bil­ity of im­ple­ment­ing a stay-​at-home order by more than 50 percent. Moreover, we find that the prob­a­bil­ity of im­ple­ment­ing a statewide stay-​at-home order is about 40 percent more likely for governors without a term limit than governors with a term limit. We also find that De­mo­c­ra­tic governors and governors without a term limit are sig­nif­i­cantly faster to adopt statewide orders than Re­pub­li­can governors and governors with a term limit. There is evidence of politics as usual in these unusual times.
    1. Which jobs are more likely to be affected by mobility re­stric­tions due to the Covid-19 pandemic? This paper uses American Time Use Survey data to measure the share of the work hours that are spent at home for different job cat­e­gories. We compute and provide home-​working shares by oc­cu­pa­tion (US census clas­si­fi­ca­tion, SOC and in­ter­na­tional ISCO clas­si­fi­ca­tion), and by industry (US census clas­si­fi­ca­tion, NAICS and in­ter­na­tional ISIC clas­si­fi­ca­tion).
    1. Using the 2012-13 American Time Use Survey, I find that both who people spend time with and how they spend it affect their happiness, adjusted for numerous de­mo­graphic and economic variables. Sat­is­fac­tion among married in­di­vid­u­als increases most with ad­di­tional time spent with spouse. Among singles, sat­is­fac­tion decreases most as more time is spent alone. Assuming that lockdowns constrain married people to spend time solely with their spouses, sim­u­la­tions show that their happiness may have been increased compared to before the lockdowns; but suf­fi­ciently large losses of work time and income reverse this inference. Sim­u­la­tions demon­strate clearly that, assuming lockdowns impose solitude on singles, their happiness was reduced, re­duc­tions that are made more severe by income and work losses.
    1. Many countries consider the lifting of re­stric­tions of social contacts (RSC). We quantify the effects of RSC for Germany. We initially employ a purely sta­tis­ti­cal approach to pre­dict­ing preva­lence of COVID19 if RSC were upheld after April 20. We employ these findings and feed them into our the­o­ret­i­cal model. We find that the peak of the number of sick in­di­vid­u­als would be reached already in April. The number of sick in­di­vid­u­als would fall below 1,000 at the beginning of July. When re­stric­tions are lifted com­pletely on April 20, the number of sick should rise quickly again from around April 27. A balance between economic and in­di­vid­ual costs of RSC and public health ob­jec­tives consists in lifting RSC for ac­tiv­i­ties that have high economic benefits but low health costs. In the absence of large-​scale rep­re­sen­ta­tive testing of CoV-2 in­fec­tions, these ac­tiv­i­ties can most easily be iden­ti­fied if federal states of Germany adopted exit strate­gies that differ across states.
    1. Due to the COVID-19 crisis and the related “social dis­tanc­ing” measures, working from home (WfH) has suddenly become a crucial lever of economic activity. This paper combines survey and ad­min­is­tra­tive data to compute measures for the fea­si­bil­ity of working from home among German employees. Breaking down the data by oc­cu­pa­tion, region, industry, and employee char­ac­ter­is­tics, we document con­sid­er­able variation in the potential to WfH across all di­men­sions. We find that WfH is feasible for roughly 56 percent of the overall German workforce, while less than half of this potential was exploited in the pre-​pandemic economy.
    1. In this ongoing project, we examine the short-​term con­se­quences of COVID-19 on em­ploy­ment and wages in the United States. Guided by a pre-​analysis plan, we document the impact of COVID-19 at the national-​level using a simple dif­fer­ence and test whether states with rel­a­tively more confirmed cases/deaths were more affected. Our findings suggest that COVID-19 increased the un­em­ploy­ment rate, decreased hours of work and labor force par­tic­i­pa­tion and had no sig­nif­i­cant impacts on wages. The negative impacts on labor market outcomes are larger for men, younger workers, Hispanics and less-​educated workers. This suggest that COVID-19 increases labor market in­equal­i­ties. We also in­ves­ti­gate whether the economic con­se­quences of this pandemic were larger for certain oc­cu­pa­tions. We built three indexes using ACS and O*NET data: workers rel­a­tively more exposed to disease, workers that work with proximity to coworkers and workers who can easily work remotely. Our estimates suggest that in­di­vid­u­als in oc­cu­pa­tions working in proximity to others are more affected while oc­cu­pa­tions able to work remotely are less affected. We also find that oc­cu­pa­tions classifed as more exposed to disease are less affected, possibly due to the large number of essential workers in these oc­cu­pa­tions.
    1. On March 19, 2020, Cal­i­for­nia Governor Gavin Newsom issued Executive Order N-33-20 2020, which required all residents of the state of Cal­i­for­nia to shelter in place for all but essential ac­tiv­i­ties such as grocery shopping, re­triev­ing pre­scrip­tions from a pharmacy, or caring for relatives. This shelter-​in-place order (SIPO), the first such statewide order issued in the United States, was designed to reduce COVID-19 cases and mortality. While the White House Task Force on the Coro­n­avirus has credited the State of Cal­i­for­nia for taking early action to prevent a statewide COVID-19 outbreak, no study has examined the impact of Cal­i­for­nia’s SIPO. Using daily state-​level coro­n­avirus data and a synthetic control research design, we find that Cal­i­for­nia’s statewide SIPO reduced COVID-19 cases by 125.5 to 219.7 per 100,000 pop­u­la­tion by April 20, one month following the order. We further find that Cal­i­for­nia’s SIPO led to as many as 1,661 fewer COVID-19 deaths during the first four weeks following its enactment. Back-​of-the-envelope cal­cu­la­tions suggest that there were about 400 job losses per life saved during this short-run post-​treatment period.
    1. This study is the first in the world to in­ves­ti­gate the expected impact of the COVID-19 crisis on career outcomes and career as­pi­ra­tions. To this end, high-​quality survey research with a relevant panel of Belgian employees was conducted. About 21% of them fear losing their jobs due to the crisis—14% are concerned that they will even lose their jobs in the near future. In addition, 26% expect to miss out on pro­mo­tions that they would have received had the COVID-19 crisis not occurred. This fear of a negative impact is higher in vul­ner­a­ble groups, such migrants. In addition, we observe that many panel members believe they will look at the labour market dif­fer­ently and will have different work-​related pri­or­i­ties in the future. In this respect, more than half of the panel members indicate that they have attached more im­por­tance to working con­di­tions and work-life balance since the COVID-19 crisis.
    1. Ar­ti­fi­cial In­tel­li­gence (AI) is a po­ten­tially powerful tool in the fight against the COVID- 19 pandemic. Since the outbreak of the pandemic, there has been a scramble to use AI. This article provides an early, and nec­es­sar­ily selective review, dis­cussing the con­tri­bu­tion of AI to the fight against COVID-19, as well as the current con­straints on these con­tri­bu­tions. Six areas where AI can con­tribute to the fight against COVID-19 are discussed, namely i) early warnings and alerts, ii) tracking and pre­dic­tion, iii) data dash­boards, iv) diagnosis and prognosis, v) treat­ments and cures, and vi) social control. It is concluded that AI has not yet been impactful against COVID-19. Its use is hampered by a lack of data, and by too much data. Over­com­ing these con­straints will require a careful balance between data privacy and public health, and rigorous human-AI in­ter­ac­tion. It is unlikely that these will be addressed in time to be of much help during the present pandemic. In the meantime, extensive gathering of di­ag­nos­tic data on who is in­fec­tious will be essential to save lives, train AI, and limit economic damages.
    1. Food pro­duc­tion and dis­tri­b­u­tion is essential for human well-​being, but the food sector has ex­pe­ri­enced a number of dif­fi­cul­ties main­tain­ing worker health and pro­duc­tiv­ity during the COVID-19 pandemic. We examine em­ploy­ment status changes of persons recently employed in the U.S. food sector with a focus on food man­u­fac­tur­ing and grocery stores. We find that the pandemic sig­nif­i­cantly reduced the prob­a­bil­ity of continued active em­ploy­ment for previous workers in both food man­u­fac­tur­ing and grocery stores. Individual-​level analysis confirms that the COVID-19 infection rate in an in­di­vid­ual’s local labor market is a strong and sig­nif­i­cant factor. The em­ploy­ment changes are not just due to un­em­ploy­ment during facility closures. Previous workers in­creas­ingly exit the labor force as the severity of the COVID-19 infection rate in their local area worsens. The con­sid­er­able risk of infection drives many previous food sector workers to stop working al­to­gether. Main­tain­ing worker health and safety is essential for a stable food supply.
    1. In response to the Covid-19 pandemic, gov­ern­ments around the world have provided a massive fiscal and monetary stimulus. While this policy is welcome in the short run, it does not address the un­der­ly­ing problem in the medium and long run. The reason is that the pandemic has not given rise to a gen­er­al­ized shortfall in aggregate demand. Rather, it has generated a Great Economic Mismatch, char­ac­ter­ized by deficient demand for things requiring close physical in­ter­ac­tions among people and deficient supply of things com­pat­i­ble with social dis­tanc­ing, where ap­pro­pri­ate. Expansive macro­eco­nomic policy can stimulate aggregate demand, but when social dis­tanc­ing is enforced, it will not stimulate pro­duc­tion and con­sump­tion whenever this demand is satisfied through phys­i­cally in­ter­ac­tive ac­tiv­i­ties. To overcome the Great Economic Mismatch, “readap­ta­tion policies” are called for. In the medium run, these policies promote a redi­rec­tion of resources to ac­tiv­i­ties com­pat­i­ble with social dis­tanc­ing; the long run, these policies make economies more resilient to un­fore­seen shocks that generate a Great Economic Mismatch. Once the pandemic is over, a more profound re­think­ing of decision making – in public policy, business and civil society – is called for. First, decision makers will need to sup­ple­ment the current focus on economic ef­fi­ciency by greater emphasis on economic re­silience. Second, economic policies and business strate­gies will need to focus less on in­cen­tives for selfish in­di­vid­u­als and more on the mo­bi­liza­tion of people’s prosocial motives. Finally, to encourage people around the world to cooperate globally in tackling global problems, policy makers at local, national and global levels will need to encourage people around the world to cooperate globally in tackling global problems, with the aid of two powerful tools that humans through­out history have used to co­or­di­nate their efforts: identity-​shaping nar­ra­tives and in­sti­tu­tions of multi-​level gov­er­nance.
    1. Disease spread is in part a function of in­di­vid­ual behavior. We examine the factors pre­dict­ing in­di­vid­ual behavior during the Covid-19 pandemic in the United States using novel data collected by Belot et al. (2020). Among other factors, we show that people with lower income, less flexible work arrange­ments (e.g., an inability to tele-work) and lack of outside space at home are less likely to engage in behaviors, such as social dis­tanc­ing, that limit the spread of disease. We also find evidence that region, gender and beliefs predict behavior. Broadly, our findings align with typical re­la­tion­ships between health and socio-​economic status. Moreover, they suggest that the burden of measures designed to stem the pandemic are unevenly dis­trib­uted across socio-​demographic groups in ways that affect behavior and thus po­ten­tially the spread of illness. Policies that assume otherwise are unlikely to be effective or sus­tain­able.
    1. We in­ves­ti­gate the impacts of COVID-19 on domestic violence and family stress. Our empirical analysis relies on a unique online survey, Canadian Per­spec­tive Survey Series, that allow us to dis­en­tan­gle the mech­a­nisms through which COVID-19 may affect family stress and domestic violence. We find no evidence that em­ploy­ment status and work arrange­ments are related to higher self-​reported levels of family stress and violence in the home due to con­fine­ment, sug­gest­ing that remote working on a large scale does not lead to family violence. In contrast, we find that the inability to meet financial oblig­a­tions and main­tain­ing social ties sig­nif­i­cantly increase reported family stress and domestic violence. These findings are con­sis­tent with two al­ter­na­tive mech­a­nisms: social isolation and decreased bar­gain­ing power for women. Last, we provide sug­ges­tive evidence that receiving financial relief does not mitigate the effect of financial worries on domestic violence and family stress. We conclude that targeted programs sup­port­ing victims of domestic violence may be more effective.
    1. Worries about the impact of COVID-19 on pregnant mothers and their offspring are wide-​spread. As a com­par­i­son, the Spanish Flu pandemic had dev­as­tat­ing health impacts on pregnant mothers and in-utero exposure to influenza is known to have negative short- and long-term con­se­quences for children. The existing evidence from the COVID-19 pandemic, however, allows for cautious optimism about the impacts of COVID-19 on pregnant women and their children.
    1. This review of UK economic policy responses to the Covid-19 crisis iden­ti­fies serious problems with existing measures. We describe al­ter­na­tive policies which could alleviate hardship, protect business from de­struc­tion in the growing de­pres­sion, fa­cil­i­tate recovery with full em­ploy­ment in a Green New Deal, and re­dis­trib­ute income and power with economic democracy in the workplace. Only such policies can ensure high quality work for all, the natural rights of self-​determination at work, and equitable sharing of the surplus that is produced by all employees as in­ten­tional agents. The proposed reforms are opposed by the strong vested interests which currently hold most power, so mo­bil­is­ing popular support and achieving real change will require a long struggle, just as attaining political democracy a century ago did.
    1. In an effort to contain the spread of the COVID-19 pandemic, many countries around the globe adopted social dis­tanc­ing measures. Previous studies have relied on the ge­o­graph­i­cal and temporal variation in the adoption of non-​pharmaceutical in­ter­ven­tions (NPIs) to show that early adoption of NPIs is cor­re­lated to lower infection and mortality rates. However, due to the non-​random adoption of NPIs, the findings may not be in­ter­preted as causal. We address this lim­i­ta­tion using a different source of iden­ti­fi­ca­tion –namely, the regional variation in the placement on the pandemic curve at the time of a na­tion­wide lockdown. Our results reveal how, relative to regions for which the lockdown arrived 10+ days after the pandemic’s outbreak, regions where the outbreak had just started were able to lower their daily fatality rate by 2.5 deaths per 100,000 in­hab­i­tants. We also provide sug­ges­tive evidence of contagion de­cel­er­a­tion as the main mechanism behind the ef­fec­tive­ness of the early adoption of NPIs in lowering the death rate, rather than increased health­care capacity.
    1. Both the White House and state governors have ex­plic­itly linked thresh­olds of reduced COVID-19 case growth to the lifting of statewide shelter-​in-place orders (SIPOs). This “hardwired” policy en­do­gene­ity creates empirical chal­lenges in credibly isolating the causal effect of lifting a statewide SIPO on COVID-19-related health. To break this si­mul­tane­ity problem, the current study exploits a unique natural ex­per­i­ment generated by a Wisconsin Supreme Court decision. On May 13, 2020, the Wisconsin Supreme Court abolished the state’s “Safer at Home” order, ruling that the Wisconsin De­part­ment of Health Services un­con­sti­tu­tion­ally usurped leg­isla­tive authority to review COVID-19 reg­u­la­tions. We cap­i­tal­ize on this sudden, dramatic, and largely unan­tic­i­pated ter­mi­na­tion of a statewide SIPO to estimate its effect on social dis­tanc­ing and COVID-19 case growth. Using a synthetic control design, we find no evidence that the repeal of the state SIPO impacted social dis­tanc­ing, COVID-19 cases, or COVID-19-related mortality during the fortnight following enactment. Estimated effects were eco­nom­i­cally small and nowhere near sta­tis­ti­cally different from zero. We conclude that the impact of shelter-​in-place orders is likely not symmetric across enactment and lifting of the orders.
    1. The COVID-19 pandemic has resulted in income and em­ploy­ment loss in many countries around the world. Yet, hardly any formal study exists on household finance and future economic ex­pec­ta­tions in poorer countries. To fill in this gap, we im­ple­mented and analyzed a web-based rapid as­sess­ment survey im­me­di­ately after the removal of lockdown measures in Vietnam, a lower-​middle-income country that has received wide­spread recog­ni­tion for its suc­cess­ful fight against the pandemic. We find that having a job is strongly and pos­i­tively as­so­ci­ated with better finance and more income and savings, as well as more optimism about the re­silience of the economy. Further dis­ag­gre­gat­ing em­ploy­ment into different types of jobs such as self-​employment and jobs with permanent and short-​term contracts, we find those with permanent job contracts to be more strongly as­so­ci­ated with better as­sess­ments and fewer job worries. In­di­vid­u­als with good health and higher ed­u­ca­tional levels also have more positive eval­u­a­tions for their current and future finance. These findings are relevant for post-​outbreak economic policies, es­pe­cially regarding the labor market in a de­vel­op­ing country context
    1. This paper models the local and cross-​city trans­mis­sions of the novel coro­n­avirus in China between January 19 and February 29 in 2020. We examine the role of various so­cioe­co­nomic mediating factors, including public health measures that encourage social dis­tanc­ing in local com­mu­ni­ties. Weather char­ac­ter­is­tics two weeks ago are used as in­stru­men­tal variables for causal inference. Stringent quar­an­tine, city lockdown, and local public health measures imposed since late January sig­nif­i­cantly decreased the virus trans­mis­sion rate. The virus spread was contained by the middle of February. Pop­u­la­tion outflow from the outbreak source region posed a higher risk to the des­ti­na­tion regions than other factors including ge­o­graphic proximity and sim­i­lar­ity in economic con­di­tions. We quantify the effects of different public health measures in reducing the number of in­fec­tions through coun­ter­fac­tual analyses. Over 1.4 million in­fec­tions and 56,000 deaths could have been avoided as a result of the national and provin­cial public health measures imposed in late January in China.
    1. This note describes the con­tri­bu­tion of migrant workers to the ongoing effort to keep basic services running in the Union during the COVID-19 epidemic. We quantify the preva­lence of migrant workers in the so called “key pro­fes­sions” that the Com­mis­sion and Member States have iden­ti­fied using the most recent wave of the EU Labour Force Survey. Our results show that migrant “key workers” are essential for critical functions in European societies.
    1. We present real time survey evidence from the UK, US and Germany showing that the labor market impacts of COVID-19 differ con­sid­er­ably across countries. Employees in Germany, which has a well-​established short-​time work scheme, are sub­stan­tially less likely to be affected by the crisis. Within countries, the impacts are highly unequal and ex­ac­er­bate existing in­equal­i­ties. Workers in al­ter­na­tive work arrange­ments and in oc­cu­pa­tions in which only a small share of tasks can be done from home are more likely to have reduced their hours, lost their jobs and suffered falls in earnings. Less educated workers and women are more affected by the crisis.
    1. It is politi­cians who have to decide when to release the lockdown, and in what way. In doing so, they have to balance many con­sid­er­a­tions (as with any decision). Often the different con­sid­er­a­tions appear in­com­men­su­rable so that only the roughest of judge­ments can be made. For example, in the case of COVID-19, one has to compare the economic benefits of releasing the lockdown with the social and psy­cho­log­i­cal benefits, and then compare the total of these with the increase in deaths that would result from an early exit. We here propose a way of doing this more sys­tem­at­i­cally.
    1. Shelter in place orders (SIPOs) require residents to remain home for all but essential ac­tiv­i­ties such as pur­chas­ing food or medicine, caring for others, exercise, or traveling for em­ploy­ment deemed essential. Between March 19 and April 20, 2020, 40 states and the District of Columbia adopted SIPOs. This study explores the impact of SIPOs on health, with par­tic­u­lar attention to het­ero­gene­ity in their impacts. First, using daily state-​level social dis­tanc­ing data from SafeGraph and a difference-​in-differences approach, we document that adoption of a SIPO was as­so­ci­ated with a 5 to 10 percent increase in the rate at which state residents remained in their homes full-time. Then, using daily state-​level coro­n­avirus case data collected by the Centers for Disease Control and Pre­ven­tion, we find that ap­prox­i­mately three weeks following the adoption of a SIPO, cu­mu­la­tive COVID-19 cases fell by 44 percent. Event-​study analyses confirm common COVID-19 case trends in the week prior to SIPO adoption and show that SIPO-​induced case re­duc­tions grew larger over time. However, this average effect masks important het­ero­gene­ity across states — early adopters and high pop­u­la­tion density states appear to reap larger benefits from their SIPOs. Finally, we find that statewide SIPOs were as­so­ci­ated with a reduction in coronavirus-​related deaths, but estimated mortality effects were im­pre­cisely estimated.
    1. This note describes some of the early policy de­vel­op­ments in the UK and the way in which the framing and un­der­stand­ing of a novel economic problem evolved to include a focus on liveli­hoods combining social pro­tec­tion and business support ori­en­ta­tions. It high­lights various points including the rapid iterative nature of policy de­vel­op­ment based on con­sul­ta­tion in the face of un­cer­tainty, as well as a trade-off between risk-​sharing with com­mer­cial banks to limit adverse selection and the rapid pre­ven­tion of in­sol­ven­cies. We consider some of the policy-​making lessons to date and conclude with sug­ges­tions for issues that policy makers might consider to support workers in the near and medium term.
    1. In response to the COVID-19 pandemic, many states have adopted stay-​at-home orders, rendering a large segment of the workforce unable to continue doing their jobs. These policies have dis­tri­b­u­tional con­se­quences, as workers in some oc­cu­pa­tions may be better able to continue their work from home. I identify the segments of the U.S. workforce that can plausibly work from home by linking oc­cu­pa­tion data from O*NET to the American Community Survey. I find that lower-​wage workers are up to three times less likely to be able to work from home than higher-​wage workers. Those with lower levels of education, younger adults, ethnic mi­nori­ties, and im­mi­grants are also con­cen­trated in oc­cu­pa­tions that are less likely to be performed from home.
    1. We study how the dif­fer­en­tial timing of local lockdowns due to COVID-19 causally affects house­holds’ spending and macro­eco­nomic ex­pec­ta­tions at the local level using several waves of a cus­tomized survey with more than 10,000 re­spon­dents. About 50% of survey par­tic­i­pants report income and wealth losses due to the corona virus, with the average losses being $5,293 and $33,482 re­spec­tively. Aggregate consumer spending dropped by 31 log per­cent­age points with the largest drops in travel and clothing. We find that house­holds living in counties that went into lockdown earlier expect the un­em­ploy­ment rate over the next twelve months to be 13 per­cent­age points higher and continue to expect higher un­em­ploy­ment at horizons of three to five years. They also expect lower future inflation, report higher un­cer­tainty, expect lower mortgage rates for up to 10 years, and have moved out of foreign stocks into liquid forms of savings. The im­po­si­tion of lockdowns can account for much of the decline in em­ploy­ment in recent months as well as declines in consumer spending. While lockdowns have pro­nounced effects on local economic con­di­tions and house­holds’ ex­pec­ta­tions, they have little impact on approval ratings of Congress, the Fed, or the Treasury but lead to declines in the approval of the President.
    1. Using a large-​scale survey of U.S. house­holds during the Covid-19 pandemic, we study how new in­for­ma­tion about fiscal and monetary policy responses to the crisis affects house­holds’ ex­pec­ta­tions. We provide random subsets of par­tic­i­pants in the Nielsen Homescan panel with different com­bi­na­tions of in­for­ma­tion about the severity of the pandemic, recent actions by the Federal Reserve, stimulus measures, as well as rec­om­men­da­tions from health officials. This ex­per­i­ment allows us to assess to what extent these policy an­nounce­ments alter the beliefs and spending plans of house­holds. In short, they do not, contrary to the powerful effects they have in standard macro­eco­nomic models.
    1. Social contacts are a key trans­mis­sion channel of in­fec­tious diseases spread by the res­pi­ra­tory or close-​contact route, such as COVID-19. There is no evidence, however, on the question of whether the nature and the or­gan­i­sa­tion of work affect the spread of COVID-19 in different countries. I have developed a method­ol­ogy to measure country-​specific levels of oc­cu­pa­tional exposure to contagion driven by social contacts. I combined six in­di­ca­tors based on Oc­cu­pa­tion In­for­ma­tion Network (O*NET) and the European Working Condition Survey (EWCS) data. I then applied them to 26 European countries, and found sub­stan­tial cross-​country dif­fer­ences in levels of exposure to contagion in com­pa­ra­ble oc­cu­pa­tions. The resulting country-​level measures of levels of exposure to contagion (excluding health pro­fes­sions) predict the growth in COVID-19 cases, and the number of deaths from COVID-19 in the early stage of pandemic (up to four weeks after the 100th case). The re­la­tion­ship between levels of oc­cu­pa­tional exposure to contagion and the spread of COVID-19 is par­tic­u­larly strong for workers aged 45-64. I found that 20-25% of the cross-​country variance in numbers of COVID-19 cases and deaths can be at­trib­uted to cross-​country dif­fer­ences in levels of oc­cu­pa­tional exposure to contagion in European countries. My findings are robust to con­trol­ling for the strin­gency of con­tain­ment policies, such as lockdowns and school closures. They are also driven by country-​specific patterns of social contacts at work, rather than by oc­cu­pa­tional struc­tures. Thus, I conclude that measuring workplace in­ter­ac­tions may help to predict the next waves of the COVID-19 pandemic.
    1. While a con­sid­er­able number of employees across the globe are being forced to work from home due to the COVID-19 crisis, it is a guessing game as to how they are ex­pe­ri­enc­ing this current surge in telework. Therefore, we examined employee per­cep­tions of telework on various life and career aspects, dis­tin­guish­ing between typical and extended telework during the COVID-19 crisis. To this end, we conducted a state-​of-the-art web survey among Flemish employees. Notwith­stand­ing this ex­cep­tional time of sudden, oblig­a­tory and high-​intensity telework, our re­spon­dents mainly attribute positive char­ac­ter­is­tics to tele­work­ing, such as increased ef­fi­ciency and a lower risk of burnout. The results also suggest that the over­whelm­ing majority of the surveyed employees believe that tele­work­ing (85%) and digital con­fer­enc­ing (81%) are here to stay. In contrast, some fear that telework di­min­ishes their promotion op­por­tu­ni­ties and weakens ties with their col­leagues and employer.
    1. In light of the existing pre­lim­i­nary evidence of a link between Covid-19 and poor air quality, which is largely based upon cor­re­la­tions, we estimate the re­la­tion­ship between long term air pollution exposure and Covid-19 in 355 mu­nic­i­pal­i­ties in the Nether­lands. Using detailed secondary and ad­min­is­tra­tive data we find com­pelling evidence of a positive re­la­tion­ship between air pollution, and par­tic­u­larly PM2.5 con­cen­tra­tions, and Covid-19 cases, hospital ad­mis­sions and deaths. This re­la­tion­ship persists after con­trol­ling for a wide range of ex­plana­tory variables. Our results indicate that a 1 μ/m3 increase in PM2.5 con­cen­tra­tions is as­so­ci­ated with 9.4 more Covid-19 cases, 3.0 more hospital ad­mis­sions, and 2.3 more deaths. The re­la­tion­ship between Covid-19 and air pollution with­stands a number of sen­si­tiv­ity and ro­bust­ness exercises including in­stru­ment­ing pollution to mitigate potential en­do­gene­ity and modelling spatial spillovers using spatial econo­met­ric tech­niques.
    1. We explore the role of social capital in the spread of the recent Covid-19 pandemic in independent analyses for Austria, Germany, Italy, the Netherlands, Sweden, Switzerland and the UK. Exploiting within-country variation, we show that a one standard deviation increase in social capital leads to 12% and 32% fewer Covid-19 cases per capita accumulated from mid-March until mid-May. Using Italy as a case study, we find that high-social-capital areas exhibit lower excess mortality and a decline in mobility. Our results have important implications for the design of local containment policies in future waves of the pandemic.
    1. We consider several economic uncertainty indicators for the US and UK before and during the COVID-19 pandemic: implied stock market volatility, newspaper-based economic policy uncertainty, twitter chatter about economic uncertainty, subjective uncertainty about future business growth, and disagreement among professional forecasters about future GDP growth. Three results emerge. First, all indicators show huge uncertainty jumps in reaction to the pandemic and its economic fallout. Indeed, most indicators reach their highest values on record. Second, peak amplitudes differ greatly – from a rise of around 100% (relative to January 2020) in two-year implied volatility on the S&P 500 and subjective uncertainty around year-ahead sales for UK firms to a 20-fold rise in forecaster disagreement about UK growth. Third, time paths also differ: Implied volatility rose rapidly from late February, peaked in mid-March, and fell back by late March as stock prices began to recover. In contrast, broader measures of uncertainty peaked later and then plateaued, as job losses mounted, highlighting the difference in uncertainty measures between Wall Street and Main Street.