Lessons on the COVID-19 pandemic: who are the most affected.

The COVID-19 pandemic has led to significant changes in work and lifestyle, impacting occupational mental health. This study examines the time and individual heterogeneity in the pandemic's effects on occupational mental health using panel data from job stress checks spanning 2018 to 2021. On average, there was an initial alleviation of high-stress risk in 2020, followed by a deterioration in 2021. Based on the job demand-resource theory, we identify the group of employees most affected by the pandemic. The findings highlight that employees in unfavorable workplace conditions are more likely to experience substantial adverse impacts. Adequate workplace support, including factors like interpersonal relationships, managerial support, job meaning, control, and work-life balance, is crucial for mitigating high-stress risk. Additionally, during the early phase of the pandemic, engaged employees experienced a slight decline in occupational mental health, while those lacking job resources at their worksite faced higher levels of occupational stress in the subsequent year. These findings offer practical suggestions for person-centered coping strategies to mitigate the pandemic's adverse impact.

Natural land cover positively correlates with COVID-19 health outcomes.

BACKGROUND: The coronavirus disease 2019 (COVID-19) poses special challenges for societies, as the disease causes millions of deaths. Although the direct prevention measures affect the prevalence and mortality the most, the other indirect factors, including natural environments and economics, could not be neglected. Evaluating the effect of natural land cover on COVID-19 health outcomes is an urgent and crucial public health topic. METHODS: Here, we examine the relationships between natural land cover and the prevalence and mortality of COVID-19 in the United States. To probe the effects of long-term living with natural land cover, we extract county-level land cover data from 2001 to 2019. Based on statistically spatial tests, we employ the Spatial Simultaneous Autoregressive (SAC) Model to estimate natural land cover's impact and monetary values on COVID-19 health outcomes. To examine the short-term effects of natural environments, we build a seasonal panel data set about the greenery index and COVID-19 health outcomes. The panel SAC model is used to detect the relationship between the greenery index and seasonal COVID-19 health outcomes. RESULTS: A 1% increase in open water or deciduous forest is associated with a 0.004-death and 0.163-conformed-case, or 0.006-death and 0.099-confirmed-case decrease in every 1,000 people. Converting them into monetary value, for the mortality, a 1% increase in open water, deciduous forest, or evergreen forest in a county is equivalent to a 212-, 313-, or 219-USD increase in household income in the long term. Moreover, for the prevalence, a 1% change in open water, deciduous forest, or mixed forest is worth a 382-, 230-, or 650-USD increase in household income. Furthermore, a rational development intensity is also critical to reduce the risk of the COVID-19 pandemic. More greenery in the short term is also linked to lower prevalence and mortality. CONCLUSIONS: Our study underscores the importance of incorporating natural land cover as a means of mitigating the risks and negative consequences of future pandemics like COVID-19 and promoting overall public health.

COVID-19, stigma, and habituation: evidence from mobility data.

BACKGROUND: The Japanese government has restricted people's going-out behavior by declaring a non-punitive state of emergency several times under COVID-19. This study aims to analyze how multiple policy interventions that impose non-legally binding restrictions on behavior associate with people's going-out. THEORY: This study models the stigma model of self-restraint behavior under the pandemic with habituation effects. The theoretical result indicates that the state of emergency's self-restraint effects weaken with the number of times. METHODS: The empirical analysis examines the impact of emergency declarations on going-out behavior using a prefecture-level daily panel dataset. The dataset includes Google's going-out behavior data, the Japanese government's policy interventions based on emergency declarations, and covariates that affect going-out behavior, such as weather and holidays. RESULTS: First, for multiple emergency declarations from the beginning of the pandemic to 2021, the negative association between emergency declarations and mobility was confirmed in a model that did not distinguish the number of emergency declarations. Second, in the model that considers the number of declarations, the negative association was found to decrease with the number of declarations. CONCLUSION: These empirical analyses are consistent with the results of theoretical analyses, which show that the negative association between people's going-out behavior and emergency declarations decreases in magnitude as the number of declarations increases.

Children mirror adults for the worse: evidence of suicide rates due to air pollution and unemployment.

BACKGROUND: Every year, more than 700,000 people die due to suicide, one of the most common reasons for youth death. While many studies have revealed two main factors for suicidal behavior: impulsive suicidal behavior due to mental illness and financial stress, it is not clear what happens if individuals face deterioration of mental health and economic recession. This paper attempts to answer this question and how suicide rates are correlated with these factors. METHODS: We empirically investigate whether economic recessions and air pollution trigger suicides by examining Japan, a country with one of the highest suicide rates, from 2014 to 2021. We take advantage of the characteristics of the COVID-19 pandemic and the periods before the pandemic, when both economic recessions and reductions in air pollution occurred simultaneously. Using monthly and municipal- level data, we construct a triple difference model that takes air pollution and unemployment as treatments. RESULTS: Our findings show that high (upper half of each period) levels of air pollution and unemployment have substantial impacts on the suicide rates of adults (22.9% in the short term) and children (42.7% in the short term, 36.0% in the long term), indicating that the increase in suicide rates among children is almost twice as high as that among adults. Our study finds that unemployment and air pollution alone are not associated with increased suicide rates but their simultaneous occurrence triggers suicides during the pandemic. CONCLUSIONS: Our study urges suicide prevention, particularly among children, as an essential consideration for public health. Furthermore, our results indicate the need for the government to allocate resources to recover air quality and the economy simultaneously during a recession to reduce suicide mortality of both child and adults.

Occupational stress: evidence from industries affected by COVID-19 in Japan.

BACKGROUND: This study provides objective evidence on the impact of COVID-19 based on employee occupational stress reported from 13 different industries, and examines the determinants of employee psychological well-being. As the economic and social impacts of the COVID-19 pandemic continue, governments should consider industry-level differences when making support decisions concerning public resource allocation to corporations. However, little evidence exists regarding the differences in occupational stress across industries. METHODS: Employee occupational stress data (N = 673,071) was derived from workers in Japan from 2018 to 2020. The sample comprises workers from 13 industries, including civil services, service industry (other), real estate, medical/welfare, wholesale/retail, academic research, and accommodation/restaurant business. A logit model is employed to investigate the differences in employees' psychological well-being before and during the pandemic. RESULTS: In 2020, 11 out of 12 industries had significantly worse occupational stress compared to employees engaged in civil services. Over 23% of employees from the wholesale/retail and accommodation/restaurant industries were observed as high-stress employees. Improved compensation policies supporting these industries are suggested. In contrast, reduced occupational stress was found among employees in the transportation/postal and information/communication industries. Among the 13 industries, aside from high job demands, tough inter-person relationships in the workplace became the most significant stressors during the pandemic. CONCLUSIONS: The results confirm that the pandemic has had a heterogeneous effect on employee occupational stress across industries, thus suggesting that the level of compensation given to different industries during the COVID-19 pandemic should be discussed and approved by the Japanese government. Additionally, support for the wholesale/retail and accommodation/restaurant industries during the pandemic should be improved.

COVID-19 and Stigma: Evolution of Self-restraint Behavior.

Social stigma can effectively prevent people from going out and possibly spreading COVID-19. Using the framework of replicator dynamics, we analyze the interaction between self-restraint behavior, infection with viruses such as COVID-19, and stigma against going out. Our model is analytically solvable with respect to an interior steady state in contrast to the previous model of COVID-19 with stigma. We show that a non-legally binding policy reduces the number of people going out in a steady state.

COVID-19 and Stigma: Evolution of Self-restraint Behavior

Social stigma can effectively prevent people from going out and possibly spreading COVID-19. Using the framework of replicator dynamics, we analyze the interaction between self-restraint behavior, infection with viruses such as COVID-19, and stigma against going out. Our model is analytically solvable with respect to an interior steady state in contrast to the previous model of COVID-19 with stigma. We show that a non-legally binding policy reduces the number of people going out in a steady state.

Impacts of air pollution on COVID-19 case fatality rate: a global analysis.

The coronavirus disease 2019 (COVID-19) pandemic is still rapidly spreading globally. To probe high-risk cities and the impacts of air pollution on public health, this study explores the relationship between the long-term average concentration of air pollution and the city-level case fatality rate (CFR) of COVID-19 globally. Then, geographically weighted regression (GWR) is applied to examine the spatial variability of the relationships. Six air pollution factors, including nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), PM2.5 (particles with diameter ≤2.5 µm), PM10 (particles with diameter ≤10 µm), and air quality index (AQI), are positively associated with the city-level COVID-19 CFR. Our results indicate that a 1-unit increase in NO2 (part per billion, PPB), SO2 (PPB), O3 (PPB), PM2.5 (microgram per cubic meter, µg/m3), PM10 (µg/m3), AQI (score), is related to a 1.450%, 1.005%, 0.992%, 0.860%, 0.568%, and 0.776% increase in the city-level COVID-19 CFR, respectively. Additionally, the effects of NO2, O3, PM2.5, AQI, and probability of living with poor AQI on COVID-19 spatially vary in view of the estimation of the GWR. In other words, the adverse impacts of air pollution on health are different among the cities. In summary, long-term exposure to air pollution is negatively related to the COVID-19 health outcome, and the relationship is spatially non-stationary. Our research sheds light on the impacts of slashing air pollution on public health in the COVID-19 pandemic to help governments formulate air pollution policies in light of the local situations.

Oil price, US stock market and the US business conditions in the era of COVID-19 pandemic outbreak.

This paper contributes to Covid-19 outbreak impacts literature. We investigate the connectedness between stock market and oil prices under bullish and bearish economic conditions and uncertainty level at different investment horizons. We applied the wavelet framework on daily dataset cover the pre-COVID-19 and COVID-19 period. We find that the linkage between the economic and financial pairs is characterized by significant changes over the time during the sample period, where the huge co-movements has been identified during the pandemic period at the low scale. We show that due to lockdown policy and oil price shock, the stock return decline, the aggregate business conditions reached its lowest level and the uncertainty increase. The result indicates that the COVID-19 outbreak negatively affects the economy and the financial markets and support the sensitivity, especially between oil-stock, and economic condition and uncertainty.

Lockdowns Save People from Air Pollution: Evidence from Daily Global Tropospheric NO2 Satellite Data

Motivated by the global fear of the Coronavirus-19 (COVID-19) pandemic, we investigated whether lockdowns save people from air pollution, notably from Nitrogen Dioxide (NO2). Using daily satellite data from the National Aeronautics and Space Administration (NASA), we first found that the global NO2 tropospheric vertical column density (TVCD) decreased by 16.5% after the Coronavirus-19 (COVID-19) outbreak. Then, we calculated the global health benefits, as the monetized value of life, using the value of a statistical life (VSL). The total global health benefits were approximately 8.73 trillion USD, accounting for 10% of the global GDP;such benefits would be the largest in China, followed by the United States, Japan and Germany. Our results suggest that lockdowns may bring benefits to countries that policy interventions cannot easily bring, thus highlighting the importance of social distancing.

Does sustainability activities performance matter during financial crises? Investigating the case of COVID-19.

As a market for sustainability investing is growing rapidly, understanding the impact of environmental, social, and governance (ESG) activities on firms' financial performance is becoming increasingly important. In this study, we examine the effect of ESG performance on stock returns and volatility during the financial crisis resulting from the coronavirus (COVID-19) pandemic. To quantify the impact, we use company-level daily ESG score data and United Nations Global Compact (GC) score data. In our dataset, ESG scores indicate ESG performance that is deemed important to financial materiality, and the GC score indicates the firm reputation for following UN rules. Our results indicate that during the pandemic, an increase in the ESG score, especially the E score component, is related to higher returns and lower volatility. Conversely, increasing GC scores is correlated with lower stock returns and higher volatility. In addition, we find that firms in lower return groups benefit more than other firms. Focusing on energy sector impacts, we show that although the non-energy sector benefits more than the energy sector from increasing E scores, energy sector firms can still reduce their stock price volatility by increasing these scores. Our study offers significant implications for ESG investment strategies during financial crises.

The role of social capital in COVID-19 deaths.

BACKGROUND: The COVID-19 pandemic has shown a continuously increasing trend with a large variation in the number of COVID-19 deaths across countries. In response, many countries have implemented non pharmaceutical methods of intervention, such as social distancing and lockdowns. This study aims to investigate the relationship of four dimensions of social capital (community attachment, social trust, family bond, and security) and several control variables with COVID-19 deaths. METHODS: We retrieved data from open access databases and a survey. COVID-19 death-related data were collected from the website "Centre for Systems Science and Engineering (CSSE) at Johns Hopkins University". Social capital-related data were collected from a large-scale survey that included web-based and face-to-face surveys covering 100,956 respondents across all regions/provinces/states of 37 countries in 2017. Data regarding population density, number of hospital beds, and population aged 65 or older were retrieved from the World Development Indicators (WDIs). Data on country lockdowns were obtained from the website "National responses to the 2019-20 coronavirus pandemic". Linear regressions were applied to identify the relationship between social capital and COVID-19 deaths. RESULTS: We found that COVID-19 deaths were associated with social capital both positively and negatively. Community attachment and social trust were associated with more COVID-19 deaths, and family bond and security were associated with fewer deaths. COVID-19 deaths were positively associated with population density, ageing population, and interactions between four dimensions of social capital-related factors and the ageing population. Furthermore, the number of hospital beds and early lockdown policy were negatively associated with COVID-19 deaths. CONCLUSIONS: The results indicate that the role of social capital in dynamically evolving threats, such as the current COVID-19 pandemic, is not always negative or positive. Therefore, people's behaviour should be changed to support countries' response to the COVID-19 threat.

Global supply constraints from the 2008 and COVID-19 crises

The analysis of specific economic indexes suggests that the economic damage from the 2020 COVID-19 crisis (coronavirus pandemic, apparently first spread from Wuhan, China) may exceed that of the 2008 global financial crisis dating to around September 15, 2008. Thus, by comparing the first four months after these crises, the purpose of this study is to estimate the economic damage of the supply-chain disruptions (i.e., the supply constraints) in the mining and manufacturing (M&M) sectors. Employing the supply-driven input–output (IO) model for the world (35 countries in 56 sectors), the results show that the supply-chain damage from COVID-19 is 1.248%, when compared to the annual gross domestic production (GDP), in the overall sectors, 4.443% in the M&M sectors, and 0.362% in other sectors, which are approximately 1.4 times the figures from the 2008 crisis.

Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster

The ongoing COVID-19 pandemic has caused global health impacts, and governments have restricted movements to a certain extent. Such restrictions have led to disruptions in economic activities. In this paper, the GDP figures for the April–June quarter of 2020 for eight countries, namely, the United States, Mexico, Germany, Italy, Spain, France, India, and Japan, are forecasted. Considering that artificial neural network models have higher forecasting accuracy than statistical methods, a multilayer artificial neural network model is developed in this paper. This model splits the dataset into two parts: the first with 80% of the observations and the second with 20%. The model then uses the first part to optimize the forecasting accuracy and then applies the optimized parameters to the second part of the dataset to assess the model performance. A forecasting error of less than 2% is achieved by the model during the testing procedure. The forecasted GDP figures show that the April–June quarter of the current year experienced sharp declines in GDP for all countries. Moreover, the annualized GDP growth is expected to reach double-digit negative growth rates. Such alarming prospects require urgent rescue actions by governments.

COVID-19 with Stigma: Theory and Evidence from Mobility Data.

This study conducts both theoretical and empirical analyses of how non-legally-binding COVID-19 policies affect people's going-out behavior. The theoretical analysis assumes that under a declared state of emergency, the individual going out suffers psychological costs arising from both the risk of infection and the stigma of going out. Our hypothesis states that under a declared state of emergency people refrain from going out because it entails a strong psychological cost. Then, this study estimates a model using regional mobility data and emergency declarations data to analyze self-restraint behavior under a non-legally binding emergency declaration. The results show that, compared with before the declaration of the state of emergency, going-out behavior was suppressed under the state of emergency and after it was lifted even when going out did not result in penalties, which is consistent with the theoretical analysis.

Does Stringency of Lockdown Affect Air Quality? Evidence from Indian Cities.

The precipitous spread of COVID-19 has created a conflict between human health and economic well-being. To contain the spread of its contagious effect, India imposed a stringent lockdown, and then the stringency was relaxed to some extent in its succeeding phases. We measure social benefits of the lockdown in terms of improved air quality in Indian cities by quantifying the effects with city-specific slope coefficients. We find that the containment measures have resulted in improvement in air quality, but it is not uniform across cities and across pollutants. The level of PM2.5 decreases from about 6 to 25% in many cities. Moreover, we observe that partial relaxations do not help in resuming economic and social activities. It should also be noted that counter-virus measures could not bring levels of the emissions to WHO standards; it highlights the importance of role of green production and consumption activities.

Global mortality benefits of COVID-19 action.

The rapid spread of COVID-19 motivated countries worldwide to mitigate mortality through actions including social distancing, home quarantine, school closures, and case isolation. We estimate the global mortality benefits of these actions. We use county-level data on COVID-19 from January 2020, project the number of mortalities until September 2020, and calculate the global mortality benefits using the age- and country-specific value of a statistical life (VSL). Implementing all four types of actions above would save approximately 40.76 trillion USD globally, with social distancing accounting for 55% of the benefits. The monetary benefit would be the largest in the US, Japan and China. Our findings indicate that global actions during COVID-19 have substantial economic benefits and must be implemented in response to COVID-19.

Airport risk of importation and exportation of the COVID-19 pandemic.

On March 11, 2020, the Director-General of the World Health Organization (WHO) characterized the spread of the coronavirus disease, COVID-19, as a pandemic on the basis of "alarming levels of spread and severity, and by the alarming levels of inaction." Hence, it is urgent and imperative to evaluate the risk of COVID-19 for as many global locations as possible. This study calculates the relative risk of the importation and exportation of the COVID-19 virus. The study's most important contribution is the calculation of the overall relative risk of the importation and exportation of COVID-19 from every airport in local municipalities around the world, based on global spatial and mapping information. Three scenarios of air travel restriction are considered, and the change in the risk of importation and exportation of COVID-19 is calculated. The relative risk of importation and exportation of COVID-19 clearly shows that not only China, Europe, Middle East, and East Asia, but also the U.S., Australia, and countries in northeast Asia and Latin America are subject to risk. Further, a larger reduction in air travel through airports in a large part of the cumulative incidence area would lead to a gradual decrease in the risk flow. Importantly, the exportation risk of the disease from some airports in China, Iran, and European countries has a higher global spread than the importation risk during the pandemic stage. Therefore, every airport, or government with airports in their jurisdiction, should implement strict countermeasures. It is also indispensable for these countries to undertake countermeasures for COVID-19, such as home quarantine within each country and restricting infected or suspected individuals from flying on airplanes.