Tracking the impact of COVID-19 on economic inequality at high frequency.
Ontology highlight
ABSTRACT:
SUBMITTER: Aspachs O
PROVIDER: S-EPMC8012053 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The implementation of large-scale containment measures by governments to contain the spread of the COVID-19 virus has resulted in large impacts to the global economy. Here, we derive a new high-frequency indicator of economic activity using empirical vessel tracking data, and use it to estimate the global maritime trade losses during the first eight months of the pandemic. We go on to use this high-frequency dataset to infer the effect of individual non-pharmaceutical interventions on maritime exports, which we use as a proxy of economic activity. Our results show widespread port-level trade losses, with the largest absolute losses found for ports in China, the Middle-East and Western Europe, associated with the collapse of specific supply-chains (e.g. oil, vehicle manufacturing). In total, we estimate that global maritime trade reduced by -7.0% to -9.6% during the first eight months of 2020, which is equal to around 206-286 million tonnes in volume losses and up to 225-412 billion USD in value losses. We find large sectoral and geographical disparities in impacts. Manufacturing sectors are hit hardest, with losses up to 11.8%, whilst some small islands developing states and low-income economies suffered the largest relative trade losses. Moreover, we find a clear negative impact of COVID-19 related school and public transport closures on country-wide exports. Overall, we show how real-time indicators of economic activity can inform policy-makers about the impacts of individual policies on the economy, and can support economic recovery efforts by allocating funds to the hardest hit economies and sectors.
| S-EPMC8046185 | biostudies-literature
Project description:OBJECTIVES:There is preliminary evidence of racial and social economic disparities in the population infected by and dying from COVID-19. The goal of this study is to report the associations of COVID-19 with respect to race, health, and economic inequality in the United States. METHODS:We performed an ecological study of the associations between infection and mortality rate of COVID-19 and demographic, socioeconomic, and mobility variables from 369 counties (total population, 102,178,117 [median, 73,447; IQR, 30,761-256,098]) from the seven most affected states (Michigan, New York, New Jersey, Pennsylvania, California, Louisiana, Massachusetts). RESULTS:The risk factors for infection and mortality are different. Our analysis shows that counties with more diverse demographics, higher population, education, income levels, and lower disability rates were at a higher risk of COVID-19 infection. However, counties with higher proportion with disability and poverty rates had a higher death rate. African Americans were more vulnerable to COVID-19 than other ethnic groups (1981 African American infected cases versus 658 Whites per million). Data on mobility changes corroborate the impact of social distancing. CONCLUSION:Our study provides evidence of racial, economic, and health inequality in the population infected by and dying from COVID-19. These observations might be due to the workforce of essential services, poverty, and access to care. Counties in more urban areas are probably better equipped at providing care. The lower rate of infection, but a higher death rate in counties with higher poverty and disability could be due to lower levels of mobility, but a higher rate of comorbidities and health care access.
| S-EPMC7462354 | biostudies-literature
Project description:Throughout the 21st century, economic inequality is predicted to increase as we face new challenges, from changes in the technological landscape to the growing climate crisis. It is crucial we understand how these changes in inequality may affect how people think and behave. We propose that economic inequality threatens the social fabric of society, in turn increasing moralization-that is, the greater tendency to employ or emphasize morality in everyday life-as an attempt to restore order and control. Using longitudinal data from X, formerly known as Twitter, our first study demonstrates that high economic inequality is associated with greater use of moral language online (e.g. the use of words such as "disgust", "hurt", and "respect'). Study 2 then examined data from 41 regions around the world, generally showing that higher inequality has a small association with harsher moral judgments of people's everyday actions. Together these findings demonstrate that economic inequality is linked to the tendency to see the world through a moral lens.
| S-EPMC11229818 | biostudies-literature
Project description:In less than two decades, the world has experienced three outbreaks of deadly Coronaviruses, including the recent pandemic of Coronavirus Disease 2019 (COVID-19) in China. COVID-19 posed an emergency of international concerns, and cases have been reported in more than 200 countries/regions that resulted in health, lives, and economic losses. China's economic growth is projected to fall to 5.6% this year, the International Monetary Fund (IMF) projected that policy investment and tax policies to implement $3.3 trillion and contributes further $4.5 trillion. IMF forecasts grow from 3.7% of global gross domestic product (GDP) in 2019 to 9.9% in 2020. GDP ratio projected from 3.0% in 2019 to grow 10.7% in 2020, the US ratio expected to increase from 5.8% to 15.7%. France, Germany, Italy, Japan, and the United Kingdom (UK) each reported public sector funding programs totalling > 10% of their yearly GDP. There is a dire need for regional and international co-operation to extend hands to prevent further spreading of COVID-19.
| S-EPMC7306969 | biostudies-literature
Project description:This study investigates how American adults' personality and financial self-efficacy (FSE) beliefs contributed to how they used their COVID-19 CARES Act Economic Impact Payment (EIP) for spending needs, spending wants, and financial transactions (save, invest, debt repayment). The results from a sample of 1172 Amazon MTurk users collected in July 2020 suggest that both personality traits and FSE beliefs were associated with EIP use. Specifically, this study finds that FSE and conscientiousness emerged as the most robust predictors of EIP use across all categories of financial behavior with a greater allocation of EIP funds to saving and less to spending needs and debt repayment. Additionally, greater FSE is associated with investing, while greater conscientiousness is connected to more spending on wants. The results suggest that saving habits associated with personality and FSE persist in a crisis environment, and pre-crisis preparedness may allow for greater spending flexibility on wants. Significant relationships were also found for openness, extraversion, agreeableness, and neuroticism. The findings highlight how people use unexpected financial windfalls during crises and uncertainty and how personal characteristics contribute to this decision making.Supplementary informationThe online version contains supplementary material available at 10.1007/s10834-021-09804-1.
| S-EPMC8605780 | biostudies-literature
Project description:In response to the rapid spread of COVID-19, governments across the globe have implemented local lockdowns that have led to increased unemployment and have disrupted local and international transport routes and supply chains. Whilst such efforts aim to slow or stop the spread of the SARS-CoV-2 virus, they have also resulted in increased food insecurity, whether due to reduced incomes or increased food prices. This is the first paper to track food insecurity and its determinants during the pandemic using multi-country and multi-wave evidence. Using data from 11 countries and up to 6 waves of High-Frequency Phone Survey data (household-level surveys) on COVID-19 and its impacts, we use a fixed-effects linear probability model to investigate the socioeconomic determinants of food insecurity during the pandemic for each country using household-level data over multiple waves. We control for socioeconomic characteristics including gender and education of the household head; income and poverty status of the households during the pandemic; safety nets in the form of cash and food assistance; coping strategies adopted by households; and price effects of major food items. Our findings suggest that cash safety nets appear to have been more effective than food in terms of reducing food insecurity during the pandemic; and that those particularly hard hit are female headed-households (highest in Malawi: 0.541, 95% CI 0.516, 0.569; lowest in Cambodia: 0.023, 95% CI 0.022, 0.024), the less educated (highest in Djibouti: - 0.232, 95% CI - 0.221, - 0.244; lowest in Nigeria: 0.006, 95% CI - 0.005, - 0.007), and poorer households (highest in Mali: 0.382, 95% CI 0.364, 0.402; lowest in Chad: 0.135, 95% CI 0.129, 0.142). In line with the existing literature, our results show that, even controlling for income loss and poverty status, those households who had to borrow rather than rely on savings had a higher probability of suffering from food insecurity. Distinct differences in the efficacy of safety nets across the 11 countries, and the differential impact of the pandemic on different groups within societies, suggest in-depth country-specific studies are needed to understand why some countries have coped better than others. Our paper highlights the importance of improving household resilience to future systemic crises, and using evidence-based best practice in the design of relevant policy instruments.
| S-EPMC8814158 | biostudies-literature
Project description:This research measures the epidemiological and economic impact of COVID-19 spread in the US under different mitigation scenarios, comprising of non-pharmaceutical interventions. A detailed disease model of COVID-19 is combined with a model of the US economy to estimate the direct impact of labor supply shock to each sector arising from morbidity, mortality, and lockdown, as well as the indirect impact caused by the interdependencies between sectors. During a lockdown, estimates of jobs that are workable from home in each sector are used to modify the shock to labor supply. Results show trade-offs between economic losses, and lives saved and infections averted are non-linear in compliance to social distancing and the duration of the lockdown. Sectors that are worst hit are not the labor-intensive sectors such as the Agriculture sector and the Construction sector, but the ones with high valued jobs such as the Professional Services, even after the teleworkability of jobs is accounted for. Additionally, the findings show that a low compliance to interventions can be overcome by a longer shutdown period and vice versa to arrive at similar epidemiological impact but their net effect on economic loss depends on the interplay between the marginal gains from averting infections and deaths, versus the marginal loss from having healthy workers stay at home during the shutdown.
| S-EPMC8517017 | biostudies-literature
Project description:The COVID-19 pandemic has prompted vaccine development efforts on an unprecedented scale. Vaccines based on mRNA technology have emerged as particularly attractive due to their high efficacy and short development timelines. However, relatively little is known about the factors contributing to the development of protective immunity by this new class of vaccines. We employed a high-temporal-resolution transcriptome profiling approach to investigate responses to COVID-19 mRNA vaccination. A cohort of 23 subjects was recruited and changes in blood transcript abundance were measured daily for 9 days post-priming and post-booster vaccination via RNA sequencing. Antibody responses were measured on days 7 and 14 post-vaccination using a custom multiplex assay. Marked differences were observed between responses to the priming and booster doses, with the latter inducing widespread changes in blood transcript abundance consistent with those found in patients with acute viral respiratory infections. The delineation of interferon responses at a high-temporal frequency also suggested that the priming and booster doses elicited distinct types of responses that peaked on day 2 post-priming dose and day 1 post-booster dose. The booster dose also induced inflammation on day 1 and erythroid cell signatures as well as an atypical plasmablast signature on day 4. Notably, this plasmablast signature, together with the post-booster interferon response signature, correlated with the antibody response levels induced on day 14 after the booster dose. Taken together, this work provides a detailed map of the antibody and transcriptional responses to the first and second doses of a new class of vaccine and yields important insights into the mechanisms underlying their immunogenicity. Furthermore, our results suggest that implementing high-temporal-frequency immune profiling protocols may provide an opportunity to better resolve the immune responses elicited by the growing number of available COVID-19 vaccines.
2022-12-09 | GSE190001 | GEO
Project description:Payments systems generate vast amounts of naturally occurring transaction data rarely used for constructing official statistics. We consider billions of transactions from card data from a large bank, Banco Bilbao Vizcaya Argentaria, as an alternative source of information for measuring consumption. We show, via validation against official consumption measures, that transaction data complements national accounts and consumption surveys. We then analyse the impact of COVID-19 in Spain, and document: (i) strong consumption responses to business closures, but smaller effects for capacity restrictions; (ii) a steeper decline in spending in rich neighbourhoods; (iii) higher mobility for residents of lower-income neighbourhoods, correlating with increased disease incidence.
| S-EPMC8355671 | biostudies-literature
Project description:Research on social class and generosity suggests that higher-income individuals are less generous than poorer individuals. We propose that this pattern emerges only under conditions of high economic inequality, contexts that can foster a sense of entitlement among higher-income individuals that, in turn, reduces their generosity. Analyzing results of a unique nationally representative survey that included a real-stakes giving opportunity (n = 1,498), we found that in the most unequal US states, higher-income respondents were less generous than lower-income respondents. In the least unequal states, however, higher-income individuals were more generous. To better establish causality, we next conducted an experiment (n = 704) in which apparent levels of economic inequality in participants' home states were portrayed as either relatively high or low. Participants were then presented with a giving opportunity. Higher-income participants were less generous than lower-income participants when inequality was portrayed as relatively high, but there was no association between income and generosity when inequality was portrayed as relatively low. This research finds that the tendency for higher-income individuals to be less generous pertains only when inequality is high, challenging the view that higher-income individuals are necessarily more selfish, and suggesting a previously undocumented way in which inequitable resource distributions undermine collective welfare.
| S-EPMC4702979 | biostudies-other