Economic impact payment, human mobility and COVID-19 mitigation in the USA.
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ABSTRACT: Supplementary information
The online version supplementary material available at 10.1007/s00181-021-02117-0.
SUBMITTER: Zhang R
PROVIDER: S-EPMC8378116 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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 coronavirus disease 2019 (COVID-19) pandemic, several national governments have applied lockdown restrictions to reduce the infection rate. Here we perform a massive analysis on near-real-time Italian mobility data provided by Facebook to investigate how lockdown strategies affect economic conditions of individuals and local governments. We model the change in mobility as an exogenous shock similar to a natural disaster. We identify two ways through which mobility restrictions affect Italian citizens. First, we find that the impact of lockdown is stronger in municipalities with higher fiscal capacity. Second, we find evidence of a segregation effect, since mobility contraction is stronger in municipalities in which inequality is higher and for those where individuals have lower income per capita. Our results highlight both the social costs of lockdown and a challenge of unprecedented intensity: On the one hand, the crisis is inducing a sharp reduction of fiscal revenues for both national and local governments; on the other hand, a significant fiscal effort is needed to sustain the most fragile individuals and to mitigate the increase in poverty and inequality induced by the lockdown.
| S-EPMC7355033 | biostudies-literature
Project description:BackgroundColleges in the United States are determining how to operate safely amid the coronavirus disease 2019 (COVID-19) pandemic.ObjectiveTo examine the clinical outcomes, cost, and cost-effectiveness of COVID-19 mitigation strategies on college campuses.DesignThe Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation model, was used to examine alternative mitigation strategies. The CEACOV model tracks infections accrued by students and faculty, accounting for community transmissions.Data sourcesData from published literature were used to obtain parameters related to COVID-19 and contact-hours.Target populationUndergraduate students and faculty at U.S. colleges.Time horizonOne semester (105 days).PerspectiveModified societal.InterventionCOVID-19 mitigation strategies, including social distancing, masks, and routine laboratory screening.Outcome measuresInfections among students and faculty per 5000 students and per 1000 faculty, isolation days, tests, costs, cost per infection prevented, and cost per quality-adjusted life-year (QALY).Results of base-case analysisAmong students, mitigation strategies reduced COVID-19 cases from 3746 with no mitigation to 493 with extensive social distancing and masks, and further to 151 when laboratory testing was added among asymptomatic persons every 3 days. Among faculty, these values were 164, 28, and 25 cases, respectively. Costs ranged from about $0.4 million for minimal social distancing to about $0.9 million to $2.1 million for strategies involving laboratory testing ($10 per test), depending on testing frequency. Extensive social distancing with masks cost $170 per infection prevented ($49 200 per QALY) compared with masks alone. Adding routine laboratory testing increased cost per infection prevented to between $2010 and $17 210 (cost per QALY gained, $811 400 to $2 804 600).Results of sensitivity analysisResults were most sensitive to test costs.LimitationData are from multiple sources.ConclusionExtensive social distancing with a mandatory mask-wearing policy can prevent most COVID-19 cases on college campuses and is very cost-effective. Routine laboratory testing would prevent 96% of infections and require low-cost tests to be economically attractive.Primary funding sourceNational Institutes of Health.
| S-EPMC7755069 | biostudies-literature
Project description:To prevent the outbreak of the Coronavirus disease (COVID-19), many countries around the world went into lockdown and imposed unprecedented containment measures. These restrictions progressively produced changes to social behavior and global mobility patterns, evidently disrupting social and economic activities. Here, using maritime traffic data collected via a global network of Automatic Identification System (AIS) receivers, we analyze the effects that the COVID-19 pandemic and containment measures had on the shipping industry, which accounts alone for more than 80% of the world trade. We rely on multiple data-driven maritime mobility indexes to quantitatively assess ship mobility in a given unit of time. The mobility analysis here presented has a worldwide extent and is based on the computation of: Cumulative Navigated Miles (CNM) of all ships reporting their position and navigational status via AIS, number of active and idle ships, and fleet average speed. To highlight significant changes in shipping routes and operational patterns, we also compute and compare global and local vessel density maps. We compare 2020 mobility levels to those of previous years assuming that an unchanged growth rate would have been achieved, if not for COVID-19. Following the outbreak, we find an unprecedented drop in maritime mobility, across all categories of commercial shipping. With few exceptions, a generally reduced activity is observable from March to June 2020, when the most severe restrictions were in force. We quantify a variation of mobility between -5.62 and -13.77% for container ships, between +2.28 and -3.32% for dry bulk, between -0.22 and -9.27% for wet bulk, and between -19.57 and -42.77% for passenger traffic. The presented study is unprecedented for the uniqueness and completeness of the employed AIS dataset, which comprises a trillion AIS messages broadcast worldwide by 50,000 ships, a figure that closely parallels the documented size of the world merchant fleet.
| S-EPMC8433355 | biostudies-literature
Project description:Mobility restrictions have been identified as key non-pharmaceutical interventions to limit the spread of the SARS-COV-2 epidemics. However, these interventions present significant drawbacks to the social fabric and negative outcomes for the real economy. In this paper we propose a real-time monitoring framework for tracking the economic consequences of various forms of mobility reductions involving European countries. We adopt a granular representation of mobility patterns during both the first and second waves of SARS-COV-2 in Italy, Germany, France and Spain to provide an analytical characterization of the rate of losses of industrial production by means of a nowcasting methodology. Our approach exploits the information encoded in massive datasets of human mobility provided by Facebook and Google, which are published at higher frequencies than the target economic variables, in order to obtain an early estimate before the official data becomes available. Our results show, in first place, the ability of mobility-related policies to induce a contraction of mobility patterns across jurisdictions. Besides this contraction, we observe a substitution effect which increases mobility within jurisdictions. Secondly, we show how industrial production strictly follows the dynamics of population commuting patterns and of human mobility trends, which thus provide information on the day-by-day variations in countries' economic activities. Our work, besides shedding light on how policy interventions targeted to induce a mobility contraction impact the real economy, constitutes a practical toolbox for helping governments to design appropriate and balanced policy actions aimed at containing the SARS-COV-2 spread, while mitigating the detrimental effect on the economy. Our study reveals how complex mobility patterns can have unequal consequences to economic losses across countries and call for a more tailored implementation of restrictions to balance the containment of contagion with the need to sustain economic activities.
| S-EPMC8219782 | biostudies-literature
Project description:Human mobility networks are crucial for a better understanding and controlling the spread of epidemics. Here, we study the impact of human mobility networks on the COVID-19 onset in 203 different countries. We use exponential random graph models to perform an analysis of the country-to-country global spread of COVID-19. We find that most countries had similar levels of virus spreading, with only a few acting as the main global transmitters. Our evidence suggests that migration and tourism inflows increase the probability of COVID-19 case importations while controlling for contiguity, continent co-location and sharing a language. Moreover, we find that air flights were the dominant mode of transportation while male and returning travellers were the main carriers. In conclusion, a mix of mobility and geography factors predicts the COVID-19 global transmission from one country to another. These findings have implications for non-pharmaceutical public health interventions and the management of transborder human circulation.
| S-EPMC7989546 | biostudies-literature
Project description:BackgroundPreliminary studies have suggested a link between socio-economic characteristics and COVID-19 mortality. Such studies have been carried out on particular geographies within the USA or selective data that do not represent the complete experience for 2020.MethodsWe estimated COVID-19 mortality rates, number of years of life lost to SARS-CoV-2 and reduction in life expectancy during each of the three pandemic waves in 2020 for 3144 US counties grouped into five socio-economic status categories, using daily death data from the Johns Hopkins University of Medicine and weekly mortality age structure from the Centers for Disease Control.ResultsDuring March-May 2020, COVID-19 mortality was highest in the most socio-economically advantaged quintile of counties and lowest in the two most-disadvantaged quintiles. The pattern reversed during June-August and widened by September-December, such that COVID-19 mortality rates were 2.58 times higher in the bottom than in the top quintile of counties. Differences in the number of years of life lost followed a similar pattern, ultimately resulting in 1.002 (1.000, 1.004) million years in the middle quintile to 1.381 (1.378, 1.384) million years of life lost in the first (most-disadvantaged) quintile during the whole year.ConclusionsDiverging trajectories of COVID-19 mortality among the poor and affluent counties indicated a progressively higher rate of loss of life among socio-economically disadvantaged communities. Accounting for socio-economic disparities when allocating resources to control the spread of the infection and to reinforce local public health infrastructure would reduce inequities in the mortality burden of the disease.
| S-EPMC8755340 | biostudies-literature
Project description:Given that real-world infection-spread scenarios pose many uncertainties, and predictions and simulations may differ from reality, this study explores factors essential for more realistically describing an infection situation. It furnishes three approaches to the argument that human mobility can create an acceleration of the spread of COVID-19 infection and its cyclicality under the simultaneous relationship. First, the study presents a dynamic model comprising the infection-mobility trade-off and mobility demand, where an increase in human mobility can cause infection explosion and where, conversely, an increase in new infections can be made temporary by suppressing mobility. Second, using time-series data for Japan, it presents empirical evidence for a stochastic trend and cycle in new infection cases. Third, it employs macroeconometrics to ascertain the feasibility of our model's predictions. Accordingly, from March 2020 to May 2021, the sources of COVID-19 infection spread in Japan varied significantly over time, and each change in the trend and cycle of new infection cases explained approximately half the respective variation.
| S-EPMC8840825 | 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 develops a holistic view of the novel coronavirus (COVID-19) spread worldwide through a spatial–temporal model with network dynamics. By using a unique human mobility dataset containing 547 166 flights with a total capacity of 101 455 913 passengers from January 22 to April 24, 2020, we analyze the epidemic correlations across 22 countries in six continents and particularly the changes in such correlations before and after implementing the international travel restriction policies targeting different countries. Results show that policymakers should move away from the previous practices that focus only on restricting hotspot areas with high infection rates. Instead, they should develop a new holistic view of global human mobility to impose the international movement restriction. The study further highlights potential correlations between international human mobility and focal countries’ epidemic situations in the global network of COVID-19 pandemic. Electronic supplementary material The online version of this article (10.1007/s40305-020-00317-6) contains supplementary material, which is available to authorized users.
| S-EPMC7396460 | biostudies-literature