Dataset Information

Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic.

ABSTRACT: Covid-19 interventions are greatly affecting patterns of human mobility. Changes in mobility during Covid-19 have differed across socio-economic gradients during the first wave. We use fine-scale network mobility data in Ontario, Canada to study the association between three different mobility measures and four socio-economic indicators throughout the first and second wave of Covid-19 (January to December 2020). We find strong associations between mobility and the socio-economic indicators and that relationships between mobility and other socio-economic indicators vary over time. We further demonstrate that understanding how mobility has changed in response to Covid-19 varies considerably depending on how mobility is measured. Our findings have important implications for understanding how mobility data should be used to study interventions across space and time. Our results support that Covid-19 non-pharmaceutical interventions have resulted in geographically disparate responses to mobility and quantifying mobility changes at fine geographical scales is crucial to understanding the impacts of Covid-19.

SUBMITTER: Long JA

PROVIDER: S-EPMC8514267 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic.

Long Jed A JA Ren Chang C

Computers, environment and urban systems 20210901

Covid-19 interventions are greatly affecting patterns of human mobility. Changes in mobility during Covid-19 have differed across socio-economic gradients during the first wave. We use fine-scale network mobility data in Ontario, Canada to study the association between three different mobility measures and four socio-economic indicators throughout the first and second wave of Covid-19 (January to December 2020). We find strong associations between mobility and the socio-economic indicators and t ...[more]

PMID: 34663997

Similar Datasets

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.

Project description:Previous pandemics have rarely affected everyone equally and, so far, the COVID-19 pandemic is no exception. Emerging evidence has shown that incidence rate, hospitalisation rate, and mortality due to COVID-19 are higher among people in lower socio-economic position (SEP). In addition, first investigations indicate that not everyone is equally affected by this pandemic's collateral public health damage. Using a stratified random sample of 1,004 participants living in Vienna, a Central European city with approximately 1.9 million inhabitants, this study analysed the distribution of 10 adverse health-related and socio-economic outcomes attributable to the COVID-19 pandemic across socio-economic strata. To this end, we estimated differences in the incidence rate of these outcomes by SEP and each of its indicators using zero-inflated Poisson and logistic regression models, adjusted for age and gender. Data were collected during first lockdown measures between 27 April and 17 May 2020. Differences in the incidence rate between the two lowest and two highest SEP groups were clearly visible. Participants in the lowest SEP category had a 32.96% higher incidence rate (IRR = 1.333 [95% CI: 1.079-1.639]), and participants in the second lowest SEP category had a 44.69% higher incidence rate (IRR = 1.447 [95% CI: 1.190-1.760]) compared with participants in the highest SEP category. In sum, 6 out of 10 adverse COVID-19-related outcomes were, to a greater or lesser extent, disproportionately experienced by Viennese residents in lower SEP. Inequalities were most visible between income groups and for the outcomes job loss, worsening of the financial situation, and worse mental health. These results strengthen and extend the current evidence on the unequally distributed burden of the COVID-19 pandemic. In light of effect heterogeneity across SEP indicators, we encourage future investigators to pay increased attention to their operationalisation of SEP. Such awareness will help to correctly identify those in most urgent need of supportive polices.

Project description:BackgroundIn many countries, the worldwide spread of COVID-19 has led to a near total stop of non-urgent, elective surgeries across all specialties during the first wave's peak of the pandemic. For providers of aesthetic surgery procedures or minimal invasive cosmetic treatments, this led to a huge socio-economic impact worldwide. In order to evaluate valid clinical management strategies for future pandemic events and to overcome the challenges imposed by the current pandemic, it is paramount to analyse the socio-economic effects caused by the COVID-19 crisis.MethodsAn online survey comprising 18 questions was sent out five times by e-mail to all members of the International Society of Aesthetic Plastic Surgery (ISAPS) between June and August 2020. The data set was statistically analyzed and grouped into an overall group and into subgroups of countries with high (n = 251) vs. low (n = 440) gross domestic product per capita (GDP p.c.) and five defined world regions (Europe (n = 214); North America (NA; n = 97); South America (SA; n = 206); Asia and Oceania (Asia + OC; n = 99); Africa and Middle East (Africa + ME; n = 75)).ResultsA total of 691 recipients completed the survey. The majority of the participants experienced severe operating restrictions resulting in a major drop of income from surgical patients. Low GDP p.c. countries experienced a bigger negative economic impact with less aesthetic (non-) surgical procedures, whereas the high GDP p.c. subgroup was less affected by the COVID-19 crisis. Most of the survey participants had already adopted the ISAPS guidelines for patient (pre-) appointment screening and clinical/patient-flow management. For surgical and non-surgical aesthetic procedures, in the high GDP p.c. subgroup more basic-level PPE (surgical mask) was used, whereas the low GDP p.c. subgroup relied more on advanced-level PPE (N-95 respirator mask or higher). Comparing the different world regions, Europe and Africa used more basic-level PPE.ConclusionsMeasurable differences in the socio-economic impact and in the adaptation of safety protocols between high and low GDP p.c. subgroups and between different world regions were present. Since the COVID-19 pandemic is an international crisis, aligned, expedient and universal actions should be taken.Level of evidence vThis journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine Ratings, please refer to Table of Contents or online Instructions to Authors www.springer.com/00266 .

Project description:BackgroundPublic health measures for COVID-19 containment have implied economic and social life disruptions, which have been particularly deleterious in low- and middle-income countries (LMIC) due to high rates of informal employment, overcrowding, and barriers to accessing health services, amongst others social determinants. Mexico, a LMIC, is a country with a high COVID-19 mortality in which there has been a very limited governmental response to help mitigate such COVID-related disruptions. This study analyzes the association of the first wave of the COVID-19 crisis in Mexico with four well-being indicators: income, employment, anxiety, and food security.MethodsIt uses pooled cross-sectional data (n = 5453) of five monthly nationally representative surveys collected between April and August 2020. Probit models are estimated to assess the association of the pandemic with job loss and anxiety; a multinomial logistic regression is estimated for food security, and an ordinary least squares regression assesses the association between the pandemic and changes in household's income.ResultsFemales were significantly associated with worse outcomes for the 4 well-being measures with an average reduction of 2.3% in household income compared to pre-COVID-19 levels, an increased probability (6.4 pp) of being in a household that had lost jobs, decreased probability of food security (6.9 pp), and an increased risk of anxiety symptoms (8.5 pp). In addition, those with lower SES and household with children also reported worse outcomes for employment, income and food security. The month variable was also statistically significant in these models suggesting that as more months of the pandemic elapsed the effects persisted.ConclusionThe currents study documents how the COVID-19 pandemic is associated with different well-being indicators in a LMIC. It suggests the urgent need to take actions to support vulnerable groups, particularly women, households with children and those in the lowest SES. If policy actions are not taken, the pandemic will increase social and gender disparities, and will jeopardize childhood development.

Dataset Information

Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic.

Publications

Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets