scholarly journals Using volunteered geographic information to assess mobility in the COVID-19 pandemic context: cross-city time series analysis of 41 cities in 22 countries from March 2nd to 26th 2020

2020 ◽  
Author(s):  
Matia Vanoni ◽  
Martin McKee ◽  
Chris Bonell ◽  
Jan Semenza ◽  
David Stuckler
Keyword(s):  
Public Transport ◽  
Fixed Effects ◽  
International Travel ◽  
Population Mobility ◽  
Mobility Index ◽  
Mass Gatherings ◽  
Government Response ◽  
Policy Interventions ◽  
Before And After ◽  
The Impact

Abstract Objectives: Restricting mobility is a central aim for lowering contact rates and preventing COVID-19 transmission. Yet the impact on mobility of different non-pharmaceutical countermeasures in the earlier stages of the pandemic is not well-understood.Design: Trends were evaluated using Citymapper’s mobility index covering 2nd to 26th March 2020, expressed as percentages of typical usage periods from 0% as the lowest and 100% as normal. China and India were not covered. Multivariate fixed effects models were used to estimate the association of policies restricting movement on mobility before and after their introduction. Policy restrictions were assessed using the Oxford COVID-19 Government Response Stringency Index as well as measures coding the timing and degree of school and workplace closures, transport restrictions, and cancellation of mass gatherings.Setting: 41 cities worldwideMain outcome measures: Citymapper’s mobility indexResults: Mobility declined in all major cities throughout March. Larger declines were seen in European than Asian cities. The COVID-19 Government Response Stringency Index was strongly associated with declines in mobility (r = -0.75, p<0.001). After adjusting for time-trends, we observed that implementing non-pharmaceutical countermeasures was associated with a decline of mobility of 10.0% for school closures (95% CI: 4.36% to 15.7%), 15.0% for workplace closures (95% CI: 10.2% to 19.8%), 7.09% for cancelling public events (95% CI: 1.98% to 12.2%), 18.0% for closing public transport (95% CI: 6.74% to 29.2%), 13.3% for restricting internal movements (95% CI: 8.85% to 17.8%) and 5.30% for international travel controls (95% CI: 1.69 to 8.90). In contrast, as expected, there was no association between population mobility changes and fiscal or monetary measures or emergency healthcare investment.Conclusions: Understanding the effect of public policy on mobility in the early stages is crucial to slowing and reducing COVID-19 transmission. By using Citymapper’s mobility index, this work provides the first evidence about trends in mobility and the impacts of different policy interventions, suggesting that closure of public transport, workplaces and schools are particularly impactful.Summary boxWhat is already known on this topic?Governments across the global are experimenting with a range of policy interventions to restrict movement in populations. Yet their impact is not well understood. There is an urgent need to understand how alternative policy approaches to restricting movement can impact on population mobility trends. What this study addsOur study finds that policy restrictions markedly reduced population-wide mobility. Closing public transport, workplaces and schools have among the largest associations with mobility declines.

scholarly journals Using volunteered geographic information to assess mobility in the COVID-19 pandemic context: cross-city time series analysis of 41 cities in 22 countries from March 2nd to 26th 2020

2020 ◽  
Author(s):  
Matia Vanoni ◽  
Martin McKee ◽  
Chris Bonell ◽  
Jan Semenza ◽  
David Stuckler
Keyword(s):  
Public Transport ◽  
Fixed Effects ◽  
International Travel ◽  
Population Mobility ◽  
School Closures ◽  
Mobility Index ◽  
Mass Gatherings ◽  
Government Response ◽  
Before And After ◽  
The Impact

Abstract Background: Restricting mobility is a central aim for lowering contact rates and preventing COVID-19 transmission. Yet the impact on mobility of different policies of restriction is not well-understood.Methods: Trends were evaluated using Citymapper’s mobility index covering 41 cities worldwide between 2nd and 26th March 2020, expressed as percentages of typical usage periods from 0% as the lowest and 100% as normal. China and India were not covered. Multivariate fixed effects models were used to estimate the association of policies restricting movement on mobility before and after their introduction. Policy restrictions were assessed using the Oxford COVID-19 Government Response Stringency Index as well as measures coding the timing and degree of school and workplace closures, transport restrictions, and cancellation of mass gatherings. Results: Mobility declined in all major cities throughout March. Larger declines were seen in European than Asian cities. The COVID-19 Government Response Stringency Index was strongly associated with declines in mobility (r = -0.75, p<0.001). After adjusting for time-trends, we observed that implementing a mobility restriction to the recommended level was associated with a decline of mobility of 10.0% for school closures (95% CI: 4.36% to 15.7%), 15.0% for workplace closures (95% CI: 10.2% to 19.8%), 7.09% for cancelling public events (95% CI: 1.98% to 12.2%), 18.0% for closing public transport (95% CI: 6.74% to 29.2%), 13.3% for restricting internal movements (95% CI: 8.85% to 17.8%) and 5.30% for international travel controls (95% CI: 1.69 to 8.90). In contrast, as expected, there was no association between population mobility changes and fiscal or monetary measures or emergency healthcare investment.Conclusions: Understanding the effect of public policy on mobility is crucial to slowing and reducing COVID-19 transmission. By using Citymapper’s mobility index, this work provides the first evidence about trends in mobility and the impacts of different policy interventions, suggesting that closure of public transport, workplaces and schools are particularly impactful.

scholarly journals Using volunteered geographic information to assess mobility in the early phases of the COVID-19 pandemic: a cross-city time series analysis of 41 cities in 22 countries from March 2nd to 26th 2020

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Matia Vannoni ◽  
Martin McKee ◽  
Jan C. Semenza ◽  
Chris Bonell ◽  
David Stuckler
Keyword(s):  
Public Transport ◽  
Fixed Effects ◽  
International Travel ◽  
Population Mobility ◽  
School Closures ◽  
Mobility Index ◽  
Mass Gatherings ◽  
Government Response ◽  
Before And After ◽  
The Impact

Abstract Objectives Restricting mobility is a central aim for lowering contact rates and preventing COVID-19 transmission. Yet the impact on mobility of different non-pharmaceutical countermeasures in the earlier stages of the pandemic is not well-understood. Design Trends were evaluated using Citymapper’s mobility index covering 2nd to 26th March 2020, expressed as percentages of typical usage periods from 0% as the lowest and 100% as normal. China and India were not covered. Multivariate fixed effects models were used to estimate the association of policies restricting movement on mobility before and after their introduction. Policy restrictions were assessed using the Oxford COVID-19 Government Response Stringency Index as well as measures coding the timing and degree of school and workplace closures, transport restrictions, and cancellation of mass gatherings. Setting 41 cities worldwide. Main outcome measures Citymapper’s mobility index. Results Mobility declined in all major cities throughout March. Larger declines were seen in European than Asian cities. The COVID-19 Government Response Stringency Index was strongly associated with declines in mobility (r = − 0.75, p < 0.001). After adjusting for time-trends, we observed that implementing non-pharmaceutical countermeasures was associated with a decline of mobility of 10.0% for school closures (95% CI: 4.36 to 15.7%), 15.0% for workplace closures (95% CI: 10.2 to 19.8%), 7.09% for cancelling public events (95% CI: 1.98 to 12.2%), 18.0% for closing public transport (95% CI: 6.74 to 29.2%), 13.3% for restricting internal movements (95% CI: 8.85 to 17.8%) and 5.30% for international travel controls (95% CI: 1.69 to 8.90). In contrast, as expected, there was no association between population mobility changes and fiscal or monetary measures or emergency healthcare investment. Conclusions Understanding the effect of public policy on mobility in the early stages is crucial to slowing and reducing COVID-19 transmission. By using Citymapper’s mobility index, this work provides the first evidence about trends in mobility and the impacts of different policy interventions, suggesting that closure of public transport, workplaces and schools are particularly impactful.

scholarly journals Domestic and international mobility trends in the United Kingdom during the COVID-19 pandemic: an analysis of facebook data

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Harry E. R. Shepherd ◽  
Florence S. Atherden ◽  
Ho Man Theophilus Chan ◽  
Alexandra Loveridge ◽  
Andrew J. Tatem
Keyword(s):  
United Kingdom ◽  
Spatial Scales ◽  
International Travel ◽  
Population Mobility ◽  
International Mobility ◽  
Mobility Patterns ◽  
Social Distancing ◽  
The United Kingdom ◽  
The Uk ◽  
The Impact

Abstract Background Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which resulted in changes to mobility across different regions. An understanding of how these policies impacted travel patterns over time and at different spatial scales is important for designing effective strategies, future pandemic planning and in providing broader insights on the population geography of the country. Crowd level data on mobile phone usage can be used as a proxy for population mobility patterns and provide a way of quantifying in near-real time the impact of social distancing measures on changes in mobility. Methods Here we explore patterns of change in densities, domestic and international flows and co-location of Facebook users in the UK from March 2020 to March 2021. Results We find substantial heterogeneities across time and region, with large changes observed compared to pre-pademic patterns. The impacts of periods of lockdown on distances travelled and flow volumes are evident, with each showing variations, but some significant reductions in co-location rates. Clear differences in multiple metrics of mobility are seen in central London compared to the rest of the UK, with each of Scotland, Wales and Northern Ireland showing significant deviations from England at times. Moreover, the impacts of rapid changes in rules on international travel to and from the UK are seen in substantial fluctuations in traveller volumes by destination. Conclusions While questions remain about the representativeness of the Facebook data, previous studies have shown strong correspondence with census-based data and alternative mobility measures, suggesting that findings here are valuable for guiding strategies.

scholarly journals Changes of the urban population mobility at the development of infrastructure for public transport, cyclists and pedestrians

2020 ◽  
Vol 17 (5) ◽  
pp. 187-193
Author(s):  
D. A. Zakharov ◽  
◽  
A. A. Fadyushin ◽  
Keyword(s):  
Public Transport ◽  
Transport Model ◽  
Large City ◽  
Population Mobility ◽  
Passenger Traffic ◽  
City Population ◽  
Private And Public ◽  
Transportation Routes ◽  
The Impact ◽  
Parking Facilities

The article examines the mobility of the large city population with 800 thousand inhabitants where there is no off-street transport. As a result of simulation modeling with a macroscopic transport model of the city, there was established the influence of the chargeable parking facilities` cost, the length of lanes for public transport and bike paths on the share of movements by private and public transport, cycling, pedestrian movements. An estimation of changes in passenger turnover at bus stops and passenger traffic was performed. The impact of the new pedestrian bridge across the river Tura is demonstrated in relation to the resident transportation routes change.

scholarly journals Impact of Covid-19 in Bangladesh Stock Market

2020 ◽  
Vol 4 (2) ◽  
pp. 22-23
Author(s):  
Sunjida Haque ◽  
Tanbir Ahmed Chowdhury
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Exchange ◽  
Potential Consequence ◽  
Economic Activities ◽  
Market Data ◽  
Policy Interventions ◽  
The World ◽  
Before And After ◽  
The Impact

The world's big economies are roiled and going under a devastating threat amid the impact of the COVID-19 pandemic. No country will be safe as this virus will eventually outbreak everywhere, regardless of how countries prepare to avoid it. The economic ramification as well as the stock market crisis will be uncertain due to the extended suspension of economic activities in almost every country. No wonder, the clattered stock markets of Bangladesh which have already got the adjective of “the worst stock market in the world” because of inefficient and irrational fluctuations in previous years will experience a colossal crisis due to the pandemic. The article provides an investigation on comparable analysis of the impact on stock markets of Bangladesh, Dhaka stock exchange, and Chittagong stock exchange, before and after the pandemic situation with current market data. We also examine the potential consequence of policy interventions to the market and the investors during a pandemic.

How the peer-to-peer market for tourist accommodation has responded to COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Beatriz Benítez-Aurioles
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Design Methodology ◽  
Peer To Peer ◽  
Content Type ◽  
Public Managers ◽  
Before And After ◽  
Tourist Accommodation ◽  
The Impact ◽  
Practical Implications

Purpose This study aims to analyze the COVID-19 pandemic’s impact on the peer-to-peer (p2p) market for tourist accommodation. Design/methodology/approach Using monthly panel data from Airbnb listings in 22 cities worldwide, the authors run a differences-in-differences analysis comparing the period of February–October 2020 to the previous year. Findings Besides a decline in accommodation supply, the pandemic made prices and demand fall in all cities significantly, after controlling for room characteristics, host traits, booking policies and individual fixed effects. There is also evidence of an alteration of the influence on prices of certain variables such as superhost and instant booking. Research limitations/implications The main limitations are related to the reference spatial and temporal environment. Besides, the samples are limited to listings that stayed before and after the pandemic; therefore, it is possible that the real effect on review growth and/or prices is actually more negative. Practical implications The analysis performed shows a scenario that represents an opportunity for public managers to test more imaginative regulations that overcome the limitations of those implemented so far. Likewise, hosts who aspire to make their accommodations profitable must adapt to the conditions imposed by the economic environment of the cities in which they operate. Originality/value This is the first study to econometrically estimate the impact of COVID-19 on prices in the p2p market for tourist accommodation in a set of cities worldwide.

scholarly journals Evaluating Social Distancing Measures and Their Association with the Covid-19 Pandemic in South America

2021 ◽  
Vol 10 (3) ◽  
pp. 121
Author(s):  
Gisliany Lillian Alves de Oliveira ◽  
Luciana Lima ◽  
Ivanovitch Silva ◽  
Marcel da Câmara Ribeiro-Dantas ◽  
Kayo Henrique Monteiro ◽  
...  
Keyword(s):  
South America ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Mobility Index ◽  
Social Distancing ◽  
Government Response ◽  
Community Mobility ◽  
Data Driven Approach ◽  
Local Moran ◽  
Global And Local

Social distancing is a powerful non-pharmaceutical intervention used as a way to slow the spread of the SARS-CoV-2 virus around the world since the end of 2019 in China. Taking that into account, this work aimed to identify variations on population mobility in South America during the pandemic (15 February to 27 October 2020). We used a data-driven approach to create a community mobility index from the Google Covid-19 Community Mobility and relate it to the Covid stringency index from Oxford Covid-19 Government Response Tracker (OxCGRT). Two hypotheses were established: countries which have adopted stricter social distancing measures have also a lower level of circulation (H1), and mobility is occurring randomly in space (H2). Considering a transient period, a low capacity of governments to respond to the pandemic with more stringent measures of social distancing was observed at the beginning of the crisis. In turn, considering a steady-state period, the results showed an inverse relationship between the Covid stringency index and the community mobility index for at least three countries (H1 rejected). Regarding the spatial analysis, global and local Moran indices revealed regional mobility patterns for Argentina, Brazil, and Chile (H1 rejected). In Brazil, the absence of coordinated policies between the federal government and states regarding social distancing may have played an important role for several and extensive clusters formation. On the other hand, the results for Argentina and Chile could be signals for the difficulties of governments in keeping their population under control, and for long periods, even under stricter decrees.

scholarly journals Early social distancing policies in Europe, changes in mobility & COVID-19 case trajectories: Insights from Spring 2020

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253071
Author(s):  
Liana R. Woskie ◽  
Jonathan Hennessy ◽  
Valeria Espinosa ◽  
Thomas C. Tsai ◽  
Swapnil Vispute ◽  
...  
Keyword(s):  
Comprehensive Evaluation ◽  
Population Mobility ◽  
School Closures ◽  
Social Distancing ◽  
Government Response ◽  
Mobility Data ◽  
Aggregate Population ◽  
The Impact ◽  
The Relationship ◽  
At Home

Background Social distancing have been widely used to mitigate community spread of SARS-CoV-2. We sought to quantify the impact of COVID-19 social distancing policies across 27 European counties in spring 2020 on population mobility and the subsequent trajectory of disease. Methods We obtained data on national social distancing policies from the Oxford COVID-19 Government Response Tracker and aggregated and anonymized mobility data from Google. We used a pre-post comparison and two linear mixed-effects models to first assess the relationship between implementation of national policies and observed changes in mobility, and then to assess the relationship between changes in mobility and rates of COVID-19 infections in subsequent weeks. Results Compared to a pre-COVID baseline, Spain saw the largest decrease in aggregate population mobility (~70%), as measured by the time spent away from residence, while Sweden saw the smallest decrease (~20%). The largest declines in mobility were associated with mandatory stay-at-home orders, followed by mandatory workplace closures, school closures, and non-mandatory workplace closures. While mandatory shelter-in-place orders were associated with 16.7% less mobility (95% CI: -23.7% to -9.7%), non-mandatory orders were only associated with an 8.4% decrease (95% CI: -14.9% to -1.8%). Large-gathering bans were associated with the smallest change in mobility compared with other policy types. Changes in mobility were in turn associated with changes in COVID-19 case growth. For example, a 10% decrease in time spent away from places of residence was associated with 11.8% (95% CI: 3.8%, 19.1%) fewer new COVID-19 cases. Discussion This comprehensive evaluation across Europe suggests that mandatory stay-at-home orders and workplace closures had the largest impacts on population mobility and subsequent COVID-19 cases at the onset of the pandemic. With a better understanding of policies’ relative performance, countries can more effectively invest in, and target, early nonpharmacological interventions.

The Effects of Parental Job Loss on Children’s Outcomes

2021 ◽  
Author(s):  
Jenifer Ruiz-Valenzuela
Keyword(s):  
Production Function ◽  
Fixed Effects ◽  
Job Loss ◽  
Negative Impact ◽  
Child Outcomes ◽  
Spillover Effects ◽  
Health Production ◽  
Negative Consequences ◽  
Before And After ◽  
The Impact

Severe economic downturns are typically characterized by a high incidence of job losses. The available evidence suggests that job losers suffer short-run earning losses that persist in the long run, are more likely to remain unemployed, suffer negative health impacts, and experience an increased likelihood of divorce. Job losses have therefore the potential to generate spillover effects for other members of the household, including children. This comes about because most of the negative consequences of job loss have a direct effect on variables that enter both the production function of cognitive achievement and the health production function. Workers who lose their jobs are likely different from those who remain employed in ways that are unobserved to the researcher and that might, in turn, affect child outcomes. Omitted variable bias poses a challenge to obtaining causal estimates of parental job loss. The way the literature has tried to approximate the ideal experiment has mainly depended on whether the child outcome under analysis could be observed both before and after the shock (i.e., both before and after parental job loss), normally relying on job losses coming from plant closures or downsizes and/or individual fixed effects. A survey of the literature shows that father’s job losses seem to have a detrimental impact on outcomes measuring children’s health and school performance. The impact of mother’s job losses on these same outcomes is mixed (including negative, null, and positive impacts). The impact on more long-term outcomes is less clear, with very mixed findings when it comes to the effect of parental job loss on college enrollment, and small impacts on earnings. In many studies, though, average effects mask important differences across subgroups: the negative impact of parental job loss seems to be mostly concentrated on disadvantaged households.

scholarly journals Metro and elderly health in Hong Kong: protocol for a natural experiment study in a high-density city

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e043983
Author(s):  
Guibo Sun ◽  
Yao Du ◽  
Michael Y Ni ◽  
Jianting Zhao ◽  
Chris Webster
Keyword(s):  
Hong Kong ◽  
Health Outcomes ◽  
Public Transport ◽  
Social Inclusion ◽  
Natural Experiment ◽  
Well Being ◽  
Transport Infrastructure ◽  
Before And After ◽  
Elderly Health ◽  
The Impact

IntroductionPublic transport accessible to older people may offer a transformative solution to achieving healthy ageing. However, the evidence to support such transport infrastructure modifications is unclear. Previous studies on public transport use and elderly health were mostly observational studies using cross-sectional data. Few studies have examined the before-and-after effects of a new metro, for example, to see if it leads to improved elderly health.Methods and analysisWe use a new metro line in Hong Kong as a natural experiment to examine the impact of the metro-led public transport intervention on elderly health. In Hong Kong, more than 90% of daily travels are made by public transport. The public transport modifications consist of the new metro line with eight stations and changes in the walking environment and bus services around the stations. We will look at the before-and-after differences in public transport use and health outcomes between elderly participants living in treatment neighbourhoods (400 m walking buffered areas of the new metro stations) and in control groups (living in comparable areas but unaffected by the new metro). Questionnaire-based baseline data were collected in 2019 before the COVID-19 pandemic, while some qualitative interviews are ongoing. Amid the pandemic, we conducted a quick telephone-based survey of COVID-19’s potential impact on public transport use behaviours of our elderly cohort in September 2020. Note there is no lockdown in Hong Kong until the writing of the paper (January 2021). After the new metro opens, we will conduct a follow-up survey, tentatively in late 2022. We aim to investigate if the new metro and the associated changes in the built environment have any effects on public transport use behaviours, physical activity and wider health outcomes among the elderly (eg, social inclusion, quality of life, subjective well-being).Ethics and disseminationThe Human Research Ethics Committee of the University of Hong Kong reviewed and approved the study procedures and materials (reference number: EA1710040). Results will be communicated through scientific papers and research reports.

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