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Showing papers in "Social Science Research Network in 2020"


Journal ArticleDOI
TL;DR: In this article, the authors explore 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) and examine the impacts of different scenarios on macroeconomic outcomes and financial markets in a global hybrid DSGE/CGE general equilibrium model.
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.

1,270 citations


Journal ArticleDOI
TL;DR: In this paper, the authors discuss the economic impact of the Coronavirus/COVID-19 crisis across industries, and countries, and provide estimates of the potential global economic costs of COVID-2019, and the GDP growth of different countries.
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.

1,207 citations


Journal ArticleDOI
TL;DR: Patients with COVID-19 have lower level of regulatory T cells, and more obviously damaged in severe cases, compared with non-severe patients, which suggests surveillance of NLR and lymphocyte subsets is helpful in the early screening of critical illness, diagnosis and treatment of CO VID-19.
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.

907 citations


ReportDOI
TL;DR: In this article, the authors identify three indicators (i.e., stock market volatility, newspaper-based economic uncertainty, and subjective uncertainty in business expectation surveys) that provide real-time forward-looking uncertainty measures.
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.

773 citations


Journal ArticleDOI
TL;DR: Mental health in the UK deteriorated compared to trends pre-Covid, particularly in young people, women and those living with young children, and inequalities may widen over time, as in other causes of recessions.
Abstract: Background: There is growing global concern about the potential impact of the Covid-19 pandemic on population mental health. We examine changes in adult mental health in the UK population before and during the lockdown. Methods: Secondary analysis of the UK Household Longitudinal Study Waves 6 (2014/15) to 9 (2018/19), matched to the Covid-19 web-survey completed by 17,452 panel members 23-29 April 2020. Mental health was assessed using the 12-item General Health Questionnaire (GHQ). Repeated cross-sectional analyses were conducted to examine annual temporal trends. Fixed effects regression models were fitted to identify within-person change compared to preceding trends. Findings: Mean population GHQ-12 score increased from 11·5 (95% confidence interval: 11·3–11·6) in 2018/19 to 12·6 (12·5–12·8) in April 2020, one month into lockdown. This was 0·48 (0·07-0·90) points higher than expected when accounting for prior upward trends between 2013 and 2019. Comparing scores within-individuals, adjusting for time-trends and predictors, increases were greatest in 18-24-year-olds (2·7, 1·89-3·48), 25-34-year-olds (1·6, 0·96-2·18), women (0·9, 0·50-1·35), and people living with young children (1·45, 0·79-2·12). People employed before the pandemic averaged a notable increase (0·6; 0·20-1·06). Interpretation: In late April 2020, mental health in the UK deteriorated compared to trends pre-Covid, particularly in young people, women and those living with young children. Those in employment before the pandemic also experienced greater deterioration one month into lockdown, perhaps due to actual or anticipated redundancy. While deterioration occurred across income groups, we anticipate inequalities may widen over time, as in other causes of recessions. Funding Statement: This study was unfunded. Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: The data used are publicly available via UK Data Service repository (study numbers 6614 and 8644), and do not require ethical assessment for academic research purposes.

762 citations


Posted Content
TL;DR: The current status of 2019-nCoV, the response, and proposals for bringing the outbreak under control are described and offered.
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.

712 citations


Posted ContentDOI
TL;DR: 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.
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

639 citations


Journal ArticleDOI
TL;DR: There are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak, and the government need pay more attention to mental health issues, especially depression and anxiety among general population and combating with “infodemic” while combating during public health emergency.
Abstract: Background: Huge citizens expos social media during a novel coronavirus disease (COVID-19) outbroke in Wuhan, China. We assess the prevalence of mental health problems and examine their association with social media exposure. Methods: We conducted a cross-sectional study among Chinese citizens aged ≥18 years old during Jan 31 to Feb 2, 2019. Online survey was used to do rapid assessment. Total of 4872 participants from 31 provinces and autonomous regions were involved in the current study. Besides demographics and social media exposure (SME), depression was assessed by The Chinese version of WHO-Five Well-Being Index (WHO-5) and anxiety was assessed by Chinese version of generalized anxiety disorder scale (GAD-7). multivariable logistic regressions were used to identify associations between social media exposure with mental health problems after controlling for covariates. Findings: The prevalence of depression, anxiety and combination of depression and anxiety (CDA) was 48.3% (95%CI: 46.9%-49.7%), 22.6% (95%CI: 21.4%-23.8%) and 19.4% (95%CI: 18.3%-20.6%) during COVID-19 outbroke in Wuhan, China. More than 80% (95%CI:80.9%-83.1%) of participants reported frequently exposed to social media. After controlling for covariates, frequently SME was positively associated with high odds of anxiety (OR=1.72, 95%CI: 1.31-2.26) and CDA (OR=1.91, 95%CI: 1.52-2.41) compared with less SME. Interpretation: Our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health problems, especially depression and anxiety among general population and combating with “infodemic” while combating during public health emergency. Funding Statement: National key R&D Program of China (grant no. 2018YFC2002000 & 2018YFC2002001) and National Natural Science Foundation of China (grant no. 71573048). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This study has been approved by the Institutional Review Board of Fudan University, School of Public Health (IRB#2020-01-0800).

610 citations


Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper investigated the relationship between the transmissibility of COVID-19 and the temperature/humidity, by controlling for various demographic, socioeconomic, geographic, healthcare and policy factors and correcting for cross-sectional correlation.
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.

556 citations


ReportDOI
TL;DR: In this paper, the authors report the results of a nationally-representative sample of the US population during the COVID-19 pandemic, which ran in two waves from April 1-5, 2020 and May 2-8, 2020.
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.

475 citations


Journal ArticleDOI
TL;DR: The COVID-19 pandemic, caused by SARS-CoV-2, is of a scale not seen since the 1918 influenza pandemic and so much of the population infected, the overall number of neurological patients, and their associated health, social and economic costs, may be large.
Abstract: Background: The COVID-19 pandemic, caused by SARS-CoV-2, is of a scale not seen since the 1918 influenza pandemic. Although the predominant clinical presentation is with respiratory disease, neurological manifestations are being recognised increasingly. Based on knowledge of other coronaviruses, especially those that caused the SARS and MERS epidemics, we might expect to see rare cases of central nervous system (CNS) and peripheral nervous system (PNS) disease caused by SARS-CoV-2. Recent developments: A growing number of case reports and series describe a wide array of neurological manifestations, but many lack detail, reflecting the challenge of studying such patients. Encephalopathy is relatively common, being reported for 93 patients in total, including 16 (7.5%) of 214 hospitalised COVID-19 patients in Wuhan, China, and 40 (69%) of 58 in intensive care with COVID-19 in France. Encephalitis has been described in 8 patients to date, and Guillain-Barre syndrome in 19 patients. SARS-CoV-2 is detected in the cerebrospinal fluid of some patients. Anosmia and ageusia are common and may occur in the absence of other clinical features. Unexpectedly, acute cerebrovascular disease is also emerging as an important complication, with cohort studies reporting stroke in 1.6-6% of hospitalised COVID-19 cases. So far, 88 patients have been described, mostly with ischaemic stroke, who frequently have vascular events in the context of a pro-inflammatory hypercoagulable state with elevated CRP, D-dimer, and ferritin. Where next?: Careful clinical, diagnostic and epidemiological studies are needed to help define the manifestations and burden of neurological disease caused by SARS-CoV-2. Precise case definitions must be used to distinguish non-specific complications of severe disease, such as hypoxic encephalopathy and critical care neuropathy, from those caused directly or indirectly by the virus; these include infectious, para- and post-infectious encephalitis, hypercoagulable states leading to stroke, and acute neuropathies such as Guillain-Barre syndrome. Recognising SARS-CoV-2 neurological disease in patients whose respiratory infection is mild or asymptomatic may prove challenging, especially if the primary COVID-19 illness occurred weeks earlier. The proportion of infections leading to neurological disease will remain small. However, these patients may be left with severe neurological sequelae. With so much of the population infected, the overall number of neurological patients, and their associated health, social and economic costs, may be large. Healthcare planners and policymakers must prepare for this eventuality. The many ongoing studies investigating the neurological association will increase our knowledge base.

ReportDOI
TL;DR: The optimal lockdown policy for a planner who wants to control the fatalities of a pandemic while minimizing the output costs of the lockdown is studied using the SIR epidemiology model and a linear economy to formalize the planner's dynamic control problem.
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.

Journal ArticleDOI
TL;DR: This research presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and cataloging individual neurons to provide real-time information about their levels of activity.
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...

Journal ArticleDOI
TL;DR: In this article, the authors analyzed the connectedness between the recent spread of COVID-19, oil price volatility shock, the stock market, geopolitical risk and economic policy uncertainty in the US within a time-frequency framework.
Abstract: In this paper, we analyze the connectedness between the recent spread of COVID-19, oil price volatility shock, the stock market, geopolitical risk and economic policy uncertainty in the US within a time-frequency framework. The coherence wavelet method and the wavelet-based Granger causality tests applied to US recent daily data unveil the unprecedented impact of COVID-19 and oil price shocks on the geopolitical risk levels, economic policy uncertainty and stock market volatility over the low frequency bands. The effect of the COVID-19 on the geopolitical risk substantially higher than on the US economic uncertainty. The COVID-19 risk is perceived differently over the short and the long-run and may be firstly viewed as an economic crisis. Our study offers several urgent prominent implications and endorsements for policymakers and asset managers

ReportDOI
TL;DR: In addition to its impact on public health, COVID-19 has had a major impact on the economy as mentioned in this paper, and the authors shed light on how COVID19 is affecting small businesses.
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

Journal ArticleDOI
TL;DR: In this article, the authors examined the impact of social distancing policies on economic activities and stock market indices and found that the increasing number of lockdown days, monetary policy decisions and international travel restrictions severely affected the level of economic activities.
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.

Journal ArticleDOI
TL;DR: In this article, the authors investigated the divergence of environmental, social, and governance (ESG) ratings from six prominent rating agencies, namely, KLD, Sustainalytics, Vigeo Eiris (Moody's), RobecoSAM (SP Global), Asset4 (Refinitiv), and MSCI IVA.
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.

Journal ArticleDOI
TL;DR: This article used variation in the timing and intensity of non-pharmaceutical interventions (NPIs) across U.S. cities during the 1918 flu pandemic to examine their economic impact.
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.

Journal ArticleDOI
TL;DR: 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: 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

Journal ArticleDOI
TL;DR: In the context of robotics and automation, learning from demonstration (LfD) is the paradigm in which robots acquire new skills by learning to imitate an expert.
Abstract: In the context of robotics and automation, learning from demonstration (LfD) is the paradigm in which robots acquire new skills by learning to imitate an expert. The choice of LfD over other robot ...

Journal ArticleDOI
TL;DR: The authors examine corporate green bonds, whose proceeds finance climate-friendly projects, and find that investors respond positively to the issuance announcement, a response that is stronger for first-time issuers and bonds certified by third parties.
Abstract: I examine corporate green bonds, whose proceeds finance climate-friendly projects. These bonds have become more prevalent over time, especially in industries where the environment is financially material to firm operations. I document that investors respond positively to the issuance announcement, a response that is stronger for first-time issuers and bonds certified by third parties. The issuers improve their environmental performance post issuance (i.e., higher environmental ratings and lower CO2 emissions), and experience an increase in ownership by long-term and green investors. Overall, the findings are consistent with a signaling argument—by issuing green bonds, companies credibly signal their commitment towards the environment.

Journal ArticleDOI
TL;DR: This effort uncovered a growing consensus around eight key thematic trends: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and promotion of human values.
Abstract: The rapid spread of artificial intelligence (AI) systems has precipitated a rise in ethical and human rights-based frameworks intended to guide the development and use of these technologies. Despite the proliferation of these "AI principles," there has been little scholarly focus on understanding these efforts either individually or as contextualized within an expanding universe of principles with discernible trends. To that end, this white paper and its associated data visualization compare the contents of thirty-six prominent AI principles documents side-by-side. This effort uncovered a growing consensus around eight key thematic trends: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and promotion of human values. Underlying this “normative core,” our analysis examined the forty-seven individual principles that make up the themes, detailing notable similarities and differences in interpretation found across the documents. In sharing these observations, it is our hope that policymakers, advocates, scholars, and others working to maximize the benefits and minimize the harms of AI will be better positioned to build on existing efforts and to push the fractured, global conversation on the future of AI toward consensus.

ReportDOI
TL;DR: In this paper, the authors make several contributions to understand the socio-demographic divide in early labor market responses to the U.S. COVID-19 epidemic and its policies, benchmarked against two previous recessions.
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.

Journal ArticleDOI
TL;DR: In this paper, the authors developed and implemented a method to monetize the impact of moderate social distancing on deaths from COVID-19 using the Ferguson et al. (2020) simulation model.
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.

BookDOI
TL;DR: In this paper, the authors simulate the potential impact of COVID-19 on gross domestic product and trade, using a standard global computable general equilibrium model, and show that the largest negative effect is experienced by domestic services affected by the pandemic.
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.


Journal ArticleDOI
TL;DR: The frontline nurses experienced a variety of mental health challenges, especially burnout and fear, which warrant attention and support from policymakers and future interventions at the national and organisational levels are needed.
Abstract: Background: During the Coronavirus Disease 2019 (COVID-19) pandemic, frontline nurses face enormous mental health challenges. Epidemiological data on the mental health statuses of frontline nurses remain unknown. The aim of this study was to examine mental health (burnout, anxiety, depression, and fear) and their associated factors among frontline nurses who were caring for COVID-19 patients in Wuhan, China. Methods: A big-scale cross-sectional, descriptive, correlational study design was used. A total of 2,014 eligible frontline nurses from two hospitals in Wuhan, China, participated in the study. Besides sociodemographic and background data, a set of valid and reliable instruments were used to measure outcomes of burnout, anxiety, depression, fear, skin lesion, self-efficacy, resilience, and social support via the online survey in February 2020. Findings: On average, the participants had a moderate level of burnout and a high level of fear. About half of the nurses reported moderate and high work burnout, as shown in emotional exhaustion (n=1,218, 60.5%), depersonalization (n=853, 42.3%), and personal accomplishment (n=1,219, 60.6%). The findings showed that 288 (14.3%), 217 (10.7%), and 1,837 (91.2%) nurses reported moderate and high levels of anxiety, depression, and fear, respectively. The majority of the nurses (n=1,910, 94.8%) had one or more skin lesions, and 1,950 (96.8%) nurses expressed their frontline work willingness. Mental health outcomes were statistically positively correlated with skin lesion and negatively correlated with self-efficacy, resilience, social support, and frontline work willingness. Interpretation: The frontline nurses experienced a variety of mental health challenges, especially burnout and fear, which warrant attention and support from policymakers. Future interventions at the national and organisational levels are needed to improve mental health during this pandemic by preventing and managing skin lesions, building self-efficacy and resilience, providing sufficient social support, and ensuring frontline work willingness. Funding Statement: 2020 COVID-19 Emergency Response Special Fund from XMU & HUST Declaration of Interests: None. Ethics Approval Statement: Ethical approval was obtained from the participating hospitals’ ethical review boards as well as the last author’s university. All nurses provided consent by ticking the “yes” box to indicate their willingness to participate in the online survey. Voluntary participation and data confidentiality were emphasized. A token of appreciation of 50 RMB (equivalent to 7 USD) was provided to each participant via the WeChat red packet on the completion of the online survey.

Journal ArticleDOI
TL;DR: Sensitivity analyses reveal that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with the effect of travel restriction of Wuhan on 2019-nCov infection in Beijing being almost equivalent to increasing quarantine by 100-thousand baseline value.
Abstract: English Abstract: Background: Since the emergence of the first pneumonia cases in Wuhan, China, the novel coronavirus (2019-nCov) infection has been quickly spreading out to other provinces and neighbouring countries. Estimation of the basic reproduction number by means of mathematical modelling can be helpful for determining the potential and severity of an outbreak, and providing critical information for identifying the type of disease interventions and intensity. Methods: A deterministic compartmental model was devised based on the clinical progression of the disease, epidemiological status of the individuals, and the intervention measures. Findings: The estimation results based on likelihood and model analysis reveal that the control reproduction number may be as high as 6.47 (95% CI 5.71-7.23). Sensitivity analyses reveal that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with the effect of travel restriction of Wuhan on 2019-nCov infection in Beijing being almost equivalent to increasing quarantine by 100-thousand baseline value. Interpretation: It is essential to assess how the expensive, resource-intensive measures implemented by the Chinese authorities can contribute to the prevention and control of the 2019-nCov infection, and how long should be maintained. Under the most restrictive measures, the outbreak is expected to peak within two weeks (since January 23rd 2020) with significant low peak value. With travel restriction (no imported exposed individuals to Beijing), the number of infected individuals in 7 days will decrease by 91.14% in Beijing, compared with the scenario of no travel restriction. Mandarin Abstract: 背景:自从中国武汉出现第一例肺炎病例以来,新型冠状病毒(2019-nCov)感染已迅速传播到其他省份和周边国家。通过数学模型估计基本再生数,有助于确定疫情爆发的可能性和严重性,并为确定疾病干预类型和强度提供关键信息。 方法:根据疾病的临床进展,个体的流行病学状况和干预措施,设计确定性的仓室模型。 结果:基于似然函数和模型分析的估计结果表明,控制再生数可能高达6.47(95%CI 5.71-7.23)。敏感性分析显示,密集接触追踪和隔离等干预措施可以有效减少控制再生数和传播风险,武汉封城措施对北京2019-nCov感染的影响几乎等同于增加隔离措施10万的基线值。 解释:必须评估中国当局实施的昂贵,资源密集型措施如何有助于预防和控制2019-nCov感染,以及应维持多长时间。在最严格的措施下,预计疫情将在两周内(自2020年1月23日起)达到峰值,峰值较低。与没有出行限制的情况相比,有了出行限制(即没有输入的潜伏类个体进入北京),北京的7天感染者数量将减少91.14%。

Journal ArticleDOI
TL;DR: In this article, market reactions to the 2019 novel coronavirus disease (COVID-19) provide new insights into how real shocks and financial policies drive firm value, and the results illustrate how anticipated real effects from the health crisis, a rare disaster, were amplified through financial channels.
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.

Journal ArticleDOI
TL;DR: The authors found that stocks of firms with higher total CO2 emissions (and changes in emissions) earn higher returns, controlling for size, book-to-market, and other return predictors.
Abstract: We study whether carbon emissions affect the cross-section of US stock returns We find that stocks of firms with higher total CO2 emissions (and changes in emissions) earn higher returns, controlling for size, book-to-market, and other return predictors We cannot explain this carbon premium through differences in unexpected profitability or other known risk factors We also find that institutional investors implement exclusionary screening based on direct emission intensity (the ratio of total emissions to sales) in a few salient industries Overall, our results are consistent with an interpretation that investors are already demanding compensation for their exposure to carbon emission risk