Showing papers in "Social Science Research Network in 2020"

Abstract: The outbreak of coronavirus named COVID-19 has disrupted the Chinese economy and is spreading globally. The evolution of the disease and its economic impact is highly uncertain which makes it difficult for policymakers to formulate an appropriate macroeconomic policy response. In order to better understand possible economic outcomes, this paper explores seven different scenarios of how COVID-19 might evolve in the coming year using a modelling technique developed by Lee and McKibbin (2003) and extended by McKibbin and Sidorenko (2006). It examines the impacts of different scenarios on macroeconomic outcomes and financial markets in a global hybrid DSGE/CGE general equilibrium model. The scenarios in this paper demonstrate that even a contained outbreak could significantly impact the global economy in the short run. These scenarios demonstrate the scale of costs that might be avoided by greater investment in public health systems in all economies but particularly in less developed economies where health care systems are less developed and popultion density is high.

Abstract: This report discusses the economic impact of the Coronavirus/COVID-19 crisis across industries, and countries. It also provides estimates of the potential global economic costs of COVID-19, and the GDP growth of different countries. The current draft includes estimates for 30 countries, under different scenarios. The report shows the economic effects of outbreak are currently being underestimated, due to over-reliance on historical comparisons with SARS, or the 2008/2009 financial crisis. At the date of this report, the duration of the lockdown, as well as how the recovery will take place is still unknown. That is why several scenarios are used. In a mild scenario, GDP growth would take a hit, ranging from 3-6% depending on the country. As a result, in the sample of 30 countries covered, we would see a median decline in GDP in 2020 of -2.8%. In other scenarios, GDP can fall more than 10%, and in some countries, more than 15%. Service-oriented economies will be particularly negatively affected, and have more jobs at risk. Countries like Greece, Portugal, and Spain that are more reliant on tourism (more than 15% of GDP) will be more affected by this crisis. This current crisis is generating spillover effects throughout supply chains. Therefore, countries highly dependent on foreign trade are more negatively affected. The results suggest that on average, each additional month of crisis costs 2.5-3% of global GDP.

Abstract: Background The COVID-19 pandemic caused by SARS-CoV-2 coronavirus threatens global public health. Currently, neutralizing antibodies (NAbs) versus this virus are expected to correlate with recovery and protection of this disease. However, the characteristics of these antibodies have not been well studied in association with the clinical manifestations in patients. Methods Plasma collected from 175 COVID-19 recovered patients with mild symptoms were screened using a safe and sensitive pseudotyped-lentiviral-vector-based neutralization assay. Spike-binding antibody in plasma were determined by ELISA using RBD, S1, and S2 proteins of SARS-CoV-2. The levels and the time course of SARS-CoV-2-specific NAbs and the spike-binding antibodies were monitored at the same time. Findings SARS-CoV-2 NAbs were unable to cross-reactive with SARS-CoV virus. SARS-CoV-2-specific NAbs were detected in patients from day 10-15 after the onset of the disease and remained thereafter. The titers of NAb among these patients correlated with the spike-binding antibodies targeting S1, RBD, and S2 regions. The titers of NAbs were variable in different patients. Elderly and middle-age patients had significantly higher plasma NAb titers (P<0.0001) and spike-binding antibodies (P=0.0003) than young patients. Notably, among these patients, there were ten patients whose NAb titers were under the detectable level of our assay (ID50: < 40); while in contrast, two patients, showed very high titers of NAb, with ID50 :15989 and 21567 respectively. The NAb titers were positive correlated with plasma CRP levels but negative correlated with the lymphocyte counts of patients at the time of admission, indicating an association between humoral response and cellular immune response. Interpretation The variations of SARS-CoV-2 specific NAbs in recovered COVID-19 patients may raise the concern about the role of NAbs on disease progression. The correlation of NAb titers with age, lymphocyte counts, and blood CRP levels suggested that the interplay between virus and host immune response in coronavirus infections should be further explored for the development of effective vaccine against SARS-CoV-2 virus. Furthermore, titration of NAb is helpful prior to the use of convalescent plasma for prevention or treatment. Funding Ministry of Science and Technology of China, National Natural Science Foundation of China, Shanghai Municipal Health Commission, and Chinese Academy of Medical Sciences

Abstract: On December 31, 2019, China reported to the World Health Organization (WHO) cases of pneumonia in Wuhan, Hubei Province, China, now designated 2019-nCoV. Mounting cases and deaths pose major public health and governance challenges. China’s imposition of an unprecedented cordon sanitaire (a guarded area preventing anyone from leaving) in Hubei Province has also sparked controversy concerning its implementation and effectiveness. Cases have now spread to 4 continents. We describe the current status of 2019-nCoV, assess the response, and offer proposals for bringing the outbreak under control.

Abstract: With the ongoing global pandemic of COVID-19, a question is whether the coming summer in the northern hemisphere will reduce the transmission intensity of COVID-19 with increased humidity and temperature. In this paper, we investigate this problem using the data from the cases with symptom-onset dates from January 19 to February 10, 2020 for 100 Chinese cities, and cases with confirmed dates from March 15 to April 25 for 1,005 U.S. counties. Statistical analysis is performed to assess the relationship between the transmissibility of COVID-19 and the temperature/humidity, by controlling for various demographic, socio-economic, geographic, healthcare and policy factors and correcting for cross-sectional correlation. We find a similar influence of the temperature and relative humidity on effective reproductive number (R values) of COVID-19 for both China and the U.S. before lockdown in both countries: one-degree Celsius increase in temperature reduces R value by about 0.023 (0.026 (95% CI [-0.0395,-0.0125]) in China and 0.020 (95% CI [-0.0311, -0.0096]) in the U.S.), and one percent relative humidity rise reduces R value by 0.0078 (0.0076 (95% CI [-0.0108,-0.0045]) in China and 0.0080 (95% CI [-0.0150,-0.0010]) in the U.S.). If assuming a 30 degree and 25 percent increase in temperature and relative humidity from winter to summer in the northern hemisphere, we expect the R values to decline about 0.89 (0.69 by temperature and 0.20 by humidity). Moreover, after the lockdowns in China and the U.S., temperature and relative humidity still play an important role in reducing the R values but to a less extent. Given the notion that the non-intervened R values are around 2.5 to 3, only weather factors cannot make the R values below their critical condition of R<1, under which the epidemic diminishes gradually. Therefore, public health intervention such as social distancing is crucial to block the transmission of COVID-19 even in summer.

Abstract: Assessing the economic impact of the COVID-19 pandemic is essential for policymakers, but challenging because the crisis has unfolded with extreme speed. We identify three indicators – stock market volatility, newspaper-based economic uncertainty, and subjective uncertainty in business expectation surveys – that provide real-time forward-looking uncertainty measures. We use these indicators to document and quantify the enormous increase in economic uncertainty in the past several weeks. We also illustrate how these forward-looking measures can be used to assess the macroeconomic impact of the COVID-19 crisis. Specifically, we feed COVID-induced first-moment and uncertainty shocks into an estimated model of disaster effects developed by Baker, Bloom and Terry (2020). Our illustrative exercise implies a year-on-year contraction in U.S. real GDP of nearly 11 percent as of 2020 Q4, with a 90 percent confidence interval extending to a nearly 20 percent contraction. The exercise says that about half of the forecasted output contraction reflects a negative effect of COVID-induced uncertainty.

Abstract: BACKGROUND: A significant number of infectious diseases display seasonal patterns in their incidence, including human coronaviruses Betacoronaviruses such as MERS-CoV and SARS-CoV are not thought to be seasonal METHODS: We examined climate data from cities with significant community spread of COVID-19 using ERA-5 reanalysis, and compared to areas that are either not affected, or do not have significant community spread FINDINGS: To date, Coronavirus Disease 2019 (COVID-19), caused by SARS-CoV-2, has established significant community spread in cities and regions along a narrow east west distribution roughly along the 30-50o N' corridor at consistently similar weather patterns consisting of average temperatures of 5-11oC, combined with low specific (3-6 g/kg) and absolute humidity (4-7 g/m3) There has been a lack of significant community establishment in expected locations that are based only on population proximity and extensive population interaction through travel INTERPRETATION: The distribution of significant community outbreaks along restricted latitude, temperature, and humidity are consistent with the behavior of a seasonal respiratory virus Additionally, we have proposed a simplified model that shows a zone at increased risk for COVID-19 spread Using weather modeling, it may be possible to predict the regions most likely to be at higher risk of significant community spread of COVID-19 in the upcoming weeks, allowing for concentration of public health efforts on surveillance and containment

Abstract: We study the optimal lockdown policy for a planner who wants to control the fatalities of a pandemic while minimizing the output costs of the lockdown. We use the SIR epidemiology model and a linear economy to formalize the planner's dynamic control problem. The optimal policy depends on the fraction of infected and susceptible in the population. We parametrize the model using data on the COVID19 pandemic and the economic breadth of the lockdown. The quantitative analysis identifies the features that shape the intensity and duration of the optimal lockdown policy. Our baseline parametrization is conditional on a 1% of infected agents at the outbreak, no cure for the disease, and the possibility of testing. The optimal policy prescribes a severe lockdown beginning two weeks after the outbreak, covers 60% of the population after a month, and is gradually withdrawn covering 20% of the population after 3 months. The intensity of the lockdown depends on the gradient of the fatality rate as a function of the infected, and on the assumed value of a statistical life. The absence of testing increases the economic costs of the lockdown, and shortens the duration of the optimal lockdown which ends more abruptly. Welfare under the optimal policy with testing is higher, equivalent to a one-time payment of 2% of GDP.

Abstract: Do non-pharmaceutical interventions (NPIs) aimed at reducing mortality during a pandemic necessarily have adverse economic effects? We use variation in the timing and intensity of NPIs across U.S. cities during the 1918 Flu Pandemic to examine their economic impact. While the pandemic itself was associated with economic disruptions in the short run, we find these disruptions were similar across cities with strict and lenient NPIs. In the medium run, we find suggestive evidence that, if anything, NPIs are associated with better economic outcomes. Our findings indicate that NPIs can reduce disease transmission without necessarily further depressing economic activity.

Abstract: Market reactions to the 2019 novel coronavirus disease (COVID-19) provide new insights into how real shocks and financial policies drive firm value. Initially, internationally oriented firms, especially those more exposed to trade with China, underperformed. As the virus spread to Europe and the United States, corporate debt and cash holdings emerged as important value drivers, relevant even after the Fed intervened in the bond market. The content and tone of conference calls mirror this development over time. Overall, the results illustrate how anticipated real effects from the health crisis, a rare disaster, were amplified through financial channels.

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

Abstract: This paper develops and implements a method to monetize the impact of moderate social distancing on deaths from COVID-19. Using the Ferguson et al. (2020) simulation model of COVID-19’s spread and mortality impacts in the United States, we project that 3-4 months of moderate distancing beginning in late March 2020 would save 1.7 million lives by October 1. Of the lives saved, 630,000 are due to avoided overwhelming of hospital intensive care units. Using the projected age-specific reductions in death and age-varying estimates of the United States Government’s value of a statistical life, we find that the mortality benefits of social distancing are about $8 trillion or $60,000 per US household. Roughly 90% of the monetized benefits are projected to accrue to people age 50 or older. Overall, the analysis suggests that social distancing initiatives and policies in response to the COVID-19 epidemic have substantial economic benefits.

Abstract: We make several contributions to understanding the socio-demographic divide in early labor market responses to the U.S. COVID-19 epidemic and its policies, benchmarked against two previous recessions. First, monthly Current Population Survey (CPS) data show greater declines in employment in April and May 2020 (relative to February) for Hispanics, younger workers, and those with high school degrees and some college. Between April and May, all the demographic subgroups considered regained some employment. Re-employment in May was broadly proportional to the employment drop that occurred through April, except for Blacks who experienced a smaller rebound. Further, we show that compared to the 2001 recession and the Great Recession, employment losses in the early COVID-19 recession were smaller for groups with very low or very high (vs. medium) education. Second, we show that job loss was larger in occupations that require more interpersonal contact and that cannot be performed remotely. Third, we find pre-COVID-19 sorting of workers into occupations and industries along demographic lines can explain a sizeable portion of the gender, race, and ethnic gaps in new unemployment. For example, while women did suffer more job losses than men, their disproportionate pre-epidemic sorting into remote work compatible occupations shielded women from what would have been even larger employment losses during the epidemic. However, there remain substantial gaps in employment losses across groups that cannot be explained by socio-economic differences. We find some larger gaps in labor market impacts when we consider the “employed but absent from work” measure present in the CPS, in addition to the more traditional employment and unemployment measures. We conclude with a discussion of policy lessons and future research needs implied by the disparities in early labor market losses from the COVID-19 crisis.

Abstract: This paper investigates the divergence of environmental, social, and governance (ESG) ratings. Based on data from six prominent rating agencies - namely, KLD (MSCI Stats), Sustainalytics, Vigeo Eiris (Moody's), RobecoSAM (SP Global), Asset4 (Refinitiv), and MSCI IVA- we decompose the divergence into three sources: different scope of categories, different measurement of categories, and different weights of categories. We find that scope and measurement divergence are the main drivers, while weights divergence is less important. In addition, we detect a rater effect where a rater's overall view of a firm influences the assessment of specific categories.

Abstract: We combine GPS data on changes in average distance traveled by individuals at the county level with COVID-19 case data and other demographic information to estimate how individual mobility is affected by local disease prevalence and restriction orders to stay-at-home. We find that a rise of local infection rate from 0% to 0.003% is associated with a reduction in mobility by 2.31%. An official stay-at-home restriction order corresponds to reducing mobility by 7.87%. Counties with larger shares of population over age 65, lower share of votes for the Republican Party in the 2016 Presidential Election, and higher population density are more responsive to disease prevalence and restriction orders.

Abstract: The novel coronavirus (2019-nCoV) has spread rapidly to multiple countries and has been declared a pandemic by the World Health Organization. While influenza virus has been shown to be affected by weather, it is unknown if COVID19 is similarly affected. In this work, we analyze the patterns in local weather of the regions affected by 2019-nCoV virus until March 22, 2020. So far, 83% of testing have been conducted in non-tropical countries (30N and above) and 90% of the 2019-nCoV cases have been recorded in the same countries within a temperature range of 3 to 17C. Similarly, ~72% of the measurements were done in countries with humidity between 3 and 9g/m3 and 90% of the cases were observed within the same range of absolute humidity (AH). The higher number of tests and global connectivity of the northern-cooler countries may explain the difference in number of confirmed 2019-nCoV cases between cooler and warmer-humid regions. Nonetheless, several countries between 30N and 30S such as Australia, UAE, Qatar, Singapore, Bahrain, Qatar and Taiwan have performed extensive testing per capita and the number of positive 2019-nCoV cases per capita are lower in these countries compared to several European countries and the US. Therefore, even though currently available data is skewed by minimal testing per capita in many tropical countries, it is possible that weather plays a role in the spread of 2019-nCoV which warrants an investigation. In the last 10 days, thousands of new cases have been documented in regions with T >18C suggesting that the role of warmer temperature in slowing the spread of the 2019-nCoV, as suggested earlier might only be observed, if at all, at much higher temperatures. Unlike temperature, however, the range of AH across which most of the cases have been documented has consistently been between 3 and 9g/m3​. Current data, although limited, suggests that it is extremely unlikely that the spread of 2019-nCoV would slow down in the USA or Europe, due to environmental factors, because a large number of cases have already been reported in the range of AH and T experienced by these regions for most part of the year. Given previous associations between viral transmission and humidity and the range of AH across which the majority of the 2019-nCoV cases have been observed till date, the role of absolute humidity merits further investigation with laboratory experiments studying the sensitivity of 2019-nCoV across a range of temperature and humidity conditions. On the other hand, if, new cases in April and May continue to cluster within the current observed range of AH i.e. 3 to 9g/m3, then the countries experiencing monsoon, i.e. having high absolute humidity (>10 g/m3) could see a slowdown in transmissions, due to climatic factors. The data analyzed here are rapidly changing and with several unknowns including how the virus is mutating and evolving, what are the reproductive numbers and the dominant way of spreading. If 2019-nCOV is indeed sensitive to environmental factors, then it could be used to optimize the 2019-nCoV mitigation strategies. Our results in no way suggest that 2019-nCoV would not spread in warm humid regions and effective public health interventions should be implemented across the world to slow down the transmission of 2019-nCoV.

Abstract: In addition to its impact on public health, COVID-19 has had a major impact on the economy To shed light on how COVID-19 is affecting small businesses – and on

Abstract: Background: In December 2019, a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan and rapidly spread throughout China. The immune response is likely to be highly involved in the pathological process of coronavirus disease 2019 (COVID-19). However, information on specific changes of immune response in COVID-19 are limited. Methods: Demographic and clinical data of all confirmed cases with COVID-19 on admission at Tongji Hospital from January 10 to February 12, 2020, were collected and analyzed. The expression of lymphocytes, lymphocyte subsets, infection related biomarkers and inflammatory cytokines were analyzed and compared between severe cases and non-severe patients. Findings: Of the 452 patients with COVID-19 recruited from January 10 to February 12, 2020, 286 were diagnosed as severe infection. The median age was 58 years and 235 were male. 201 patients had chronic diseases and a higher percentage in the severe cases. The most common symptoms were fever, shortness of breath, expectoration, and fatigue. Severe cases tend to have higher white blood cell and neutrophil lymphopenia ratio (NLR), as well as lower percentages of monocytes, eosinophils, and basophils. Most of severe cases demonstrated elevated levels of infection-related biomarkers, and inflammatory cytokines. The numbers of B cells, T cells and NK cells was significantly decreased in patients with COVID-19, and more severely decreased in the severe cases. T cells were shown to be most affected by SARS-CoV-2, and more hampered in severe cases. Both helper T cells and suppressor T cells in patients with COVID-19 were below normal levels. Helper T cells tend to be more affected in severe cases. The percentage of naive helper T cells increased and memory helper T cells decreased in severe cases. Patients with COVID-19 have lower level of regulatory T cells, and more obviously damaged in severe cases. Interpretation: SARS-CoV-2 might mainly act on lymphocytes, especially T lymphocytes, and induce a cytokine storm in the body, generate a series of immune responses. Surveillance of NLR and lymphocyte subsets is helpful in the early screening of critical illness, diagnosis and treatment of COVID-19. Funding Statement: None. Declaration of Interests: All authors declare no competing interests. Ethics Approval Statement: The study was performed in accordance with Tongji Hospital Ethics Committee (IRB ID: TJ-C20200121). Written informed consent was waived by the Ethics Commission of the designated hospital for emerging infectious disease.

Abstract: We use data on deaths in New York City, Madrid, Stockholm, and other world cities as well as in various U.S. states and various countries and regions to estimate a standard epidemiological model of COVID-19. We allow for a time-varying contact rate in order to capture behavioral and policy-induced changes associated with social distancing. We simulate the model forward to consider possible futures for various countries, states, and cities, including the potential impact of herd immunity on re-opening. Our current baselinemortality rate (IFR) is assumed to be 1.0% but we recognize there is substantial uncertainty about this number. Our model fits the death data equally well with alternative mortality rates of 0.5% or 1.2%, so this parameter is unidentified in our data. However, its value matters enormously for the extent to which various places can relax social distancing without spurring a resurgence of deaths.

Abstract: How did a health crisis translate to an economic crisis? Why did the spread of the coronavirus bring the global economy to its knees? The answer lies in two methods by which coronavirus stifled economic activities. First, the spread of the virus encouraged social distancing which led to the shutdown of financial markets, corporate offices, businesses and events. Second, the exponential rate at which the virus was spreading, and the heightened uncertainty about how bad the situation could get, led to flight to safety in consumption and investment among consumers, investors and international trade partners. We focus on the period from the start of 2020 through March when the coronavirus began spreading into other countries and markets. We draw on real-world observations in assessing the restrictive measures, monetary policy measures, fiscal policy measures and the public health measures that were adopted during the period. We empirically examine the impact of social distancing policies on economic activities and stock market indices. The findings reveal that the increasing number of lockdown days, monetary policy decisions and international travel restrictions severely affected the level of economic activities and the closing, opening, lowest and highest stock price of major stock market indices. In contrast, the imposed restriction on internal movement and higher fiscal policy spending had a positive impact on the level of economic activities, although the increasing number of confirmed coronavirus cases did not have a significant effect on the level of economic activities.

Abstract: Between December 1, 2019 and January 26, 2020, nearly 3000 cases of respiratory illness caused by a novel coronavirus originating in Wuhan, China have been reported. In this short analysis, we combine publicly available cumulative case data from the ongoing outbreak with phenomenological modeling methods to conduct an early transmissibility assessment. Our model suggests that the basic reproduction number associated with the outbreak (at time of writing) may range from 2.0 to 3.1. Though these estimates are preliminary and subject to change, they are consistent with previous findings regarding the transmissibility of the related SARS-Coronavirus and indicate the possibility of epidemic potential.

Abstract: We use data from the aggregate stock and dividend futures markets to quantify how investors' expectations about economic growth evolve across horizons in response to the new coronavirus (COVID-19) outbreak and subsequent policy responses until July 2020. Dividend futures, which are claims to dividends on the aggregate stock market in a particular year, can be used to directly compute a lower bound on growth expectations across maturities or to estimate expected growth using a forecasting model. We show how the actual forecast and the bound evolve over time. As of July 20, our forecast of annual growth in dividends points to a decline of 8% in both the US and Japan and a 14% decline in the EU compared to January 1. Our forecast of GDP growth points to a decline of 2% in the US and Japan and 3% in the EU. The lower bound on the change in expected dividends is -17% in the US and Japan and -28% in the EU at the 2-year horizon. News about fiscal stimulus around March 24 boosts the stock market and long-term growth but did little to increase short-term growth expectations. Expected dividend growth has improved since April 1 in all geographies.

Abstract: 2019-nCoV is a novel coronavirus named in 2019. The number of people suffering from the virus kept increasing from China to the world. The initial infection characters of 2019-nCoV has been reported, including the symptoms and blood test results. Cell pyroptosis is a novel inflammatory form of programmed cell death, which has been largely studied recently. Here we noted that some of the 2019-nCoV results could be matched to the cell pyroptosis. This paper is aimed to discuss the relationship between 2019-nCoV infection and cell pyroptosis and put forward a potential hypothesis.

Abstract: The COVID-19 pandemic continues to grow in the United States and, in the absence of a vaccine or effective treatment, social distancing measures are essential to slow the spread of this disease. Using cellular mobility data from 2019 and 2020, I demonstrate that there have been substantial increases in social distancing since the start of the pandemic. Rates of voluntary, as opposed to mandatory, social distancing varies by county characteristics, including partisanship, media consumption, and racial and ethnic composition. Mandatory measures to increase social distancing appear to be effective, most notably stay at home orders which increase the share of devices at home by 2 percentage points. Social distancing orders also appear to have substantial informational content and, in the case of mask mandates, the informational content appears to be greater than the gross effect of mask mandates on behavior. These results provide insight into the importance of communicating the threat posed by COVID-19, since most changes in social distancing appear to be voluntary, plausibly reflecting beliefs about disease risk.

Abstract: Permissionless blockchains require a protocol to generate consensus. Many prominent permissionless blockchains employ Proof-of-Work (PoW) for that purpose, but PoW possesses significant shortcomings. Various alternatives have been proposed. This paper provides the first formal economic model of the most famous alternative, Proof-of-Stake (PoS), and establishes conditions under which PoS generates consensus. A sufficiently modest reward schedule not only implies the existence of an equilibrium in which consensus obtains as soon as possible but also precludes a persistent forking equilibrium. The latter result arises because PoS, unlike PoW, requires that validators are also stakeholders.

Abstract: The virus that triggered a localized shock in China is now delivering a significant global shock. This study simulates the potential impact of COVID-19 on gross domestic product and trade, using a standard global computable general equilibrium model. It models the shock as underutilization of labor and capital, an increase in international trade costs, a drop in travel services, and a redirection of demand away from activities that require proximity between people. A baseline global pandemic scenario sees gross domestic product fall by 2 percent below the benchmark for the world, 2.5 percent for developing countries, and 1.8 percent for industrial countries. The declines are nearly 4 percent below the benchmark for the world, in an amplified pandemic scenario in which containment is assumed to take longer and which now seems more likely. The biggest negative shock is recorded in the output of domestic services affected by the pandemic, as well as in traded tourist services. Since the model does not capture fully the social isolation induced independent contraction in demand and the decline in investor confidence, the eventual economic impact may be different. This exercise is illustrative, because it is still too early to make an informed assessment of the full impact of the pandemic. But it does convey the likely extent of impending global economic pain, especially for developing countries and their potential need for assistance.

Abstract: Recent successes in the field of machine learning, as well as the availability of increased sensing and computational capabilities in modern control systems, have led to a growing interest in learn...

Abstract: Background: Patients with obesity are at increased risk of exacerbations from viral respiratory infections. However, the association of obesity with severity of corona virus disease 2019 (COVID-19) is unclear. We hereby examined this association using data from the only referral hospital in Shenzhen, China. Methods: 383 COVID-19 patients admitted from 11 January to 16 February 2020 in the Third People’s Hospital of Shenzhen, China were included. Underweight was defined by body mass index (BMI) lower than 18·5 kg/m2, normal weight by 18·5-23·9 kg/m2 , overweight by 24·0- 27·9 kg/m2 and obesity as ≥28 kg/m2. Findings: Of them, 53·1% were normal weight, 4·2% were underweight, 32·0% were overweight, and 10·7% were obese. Patients with obesity, versus without, were tended to have cough (P=0·03) and fever (P=0·06). After adjusting for potential confounders, compared to normal weight, overweight showed 86% higher, and obesity group showed 2·42-fold higher odds of developing severe pneumonia. Despite a non-significant sex interaction was found (P=0·09), the association appeared to be more pronounced in men than in women. The odds ratios (95% confidence intervals) for severe pneumonia in overweight and obesity was 1·96 (0·78-4·98) and 5·70 (1·83-17·76) in men, and 1·51 (0·57-4·01) and 0·71 (0·07-7·3) in women, respectively. Interpretation: This is the first study showing that obesity, especially in men, significantly increases the risk of developing severe pneumonia in COVID-19 patients. As the 2019n-Cov may continue to spread worldwide, clinicians should maintain a high level of attention in obese patients. Obese patients should be carefully managed with prompt and aggressive treatment. Funding Statement: Sanming Project of Medicine in Shenzhen (SZSM201412003, SZSM201512005) and Bill & Melinda Gates Foundations, Shenzhen Science and Technology Research and Development Project (202002073000001). Declaration of Interests: All authors declare no competing interests. Ethics Approval Statement: This study was approved by the Ethics Committee of The Third People’s Hospital of Shenzhen (2020 108). All patients provided signed informed consent at admission.

Abstract: 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.