Effects of COVID-19 on temporal urban diversity : A quantitative study using mobile phone data as a proxy for human mobility patterns

The present paper examines possible changes in temporal urban diversity caused by the COVID-19 pandemic in Stockholm and Uppsala metropolitan areas. In addition to general changes in diversity, potential differences of diversity levels at locations with varying socioeconomic characteristics are examined. The diversity levels are calculated based on mobile phone data and defined by the inflow and distribution of individuals to locations. The time frame involves eight study dates and extends from January to April 2020. The paper reaches the following conclusions. (1) Diversity levels display a general decline during the pandemic, with one exception - Easter Holidays. (2) Individuals residing in areas with high proportions of highly educated individuals or visible minorities experience a decrease in diversity whereas the opposite is true for areas with high proportions of low-income earners or senior citizens (3) The increase in diversity in the two last mentioned areas, which are located in remote parts of the metropolitan area, coincide with decreasing levels of diversity in the central parts of the metropolitan area. It is possible that changes in diversity levels in these areas can be explained by changes in general behavioural trends, e.g. incentives to avoid crowded city center areas

Effects of COVID-19 on temporal urban diversity : A quantitative study using mobile phone data as a proxy for human mobility patterns

The present paper examines possible changes in temporal urban diversity caused by the COVID-19 pandemic in Stockholm and Uppsala metropolitan areas. In addition to general changes in diversity, potential differences of diversity levels at locations with varying socioeconomic characteristics are examined. The diversity levels are calculated based on mobile phone data and defined by the inflow and distribution of individuals to locations. The time frame involves eight study dates and extends from January to April 2020. The paper reaches the following conclusions. (1) Diversity levels display a general decline during the pandemic, with one exception - Easter Holidays. (2) Individuals residing in areas with high proportions of highly educated individuals or visible minorities experience a decrease in diversity whereas the opposite is true for areas with high proportions of low-income earners or senior citizens (3) The increase in diversity in the two last mentioned areas, which are located in remote parts of the metropolitan area, coincide with decreasing levels of diversity in the central parts of the metropolitan area. It is possible that changes in diversity levels in these areas can be explained by changes in general behavioural trends, e.g. incentives to avoid crowded city center areas

Modeling life expectancies : A spatial analysis

In the present paper, we examine the effect of socioeconomic characteristics on the life expectancy of men and women in the Stockholm metropolitan area. Detailed individual data allows for a novel approach where observations can be displayed in high resolution. As is often the case with geographical data, the variables display high spatial autocorrelations, which imply that observations in proximity are more, or less, similar than what could be expected under the assumption of independent and identically distributed observations. Presence of spatial autocorrelation makes conventional regression models nonfunctional, and a model that accounts for this is therefore specified. In addition, a distance-band which reflects the distance and association between observations is determined. Lagrange Multiplier tests, AIC, log-likelihood, and the Schwarz criterion suggest that a spatial error model with a 300-meter distance band is appropriate for the data at hand. The findings suggest that: (1) Belonging to a minority group has the strongest effect on life expectancies and (2) the effect is negative for both genders, although the negative impact is stronger for males. Tests for spatial autocorrelation on the residuals suggest that the adopted spatial error model captures nearly all spatial autocorrelation in the data, compared to alternative models

Modeling life expectancies : A spatial analysis

In the present paper, we examine the effect of socioeconomic characteristics on the life expectancy of men and women in the Stockholm metropolitan area. Detailed individual data allows for a novel approach where observations can be displayed in high resolution. As is often the case with geographical data, the variables display high spatial autocorrelations, which imply that observations in proximity are more, or less, similar than what could be expected under the assumption of independent and identically distributed observations. Presence of spatial autocorrelation makes conventional regression models nonfunctional, and a model that accounts for this is therefore specified. In addition, a distance-band which reflects the distance and association between observations is determined. Lagrange Multiplier tests, AIC, log-likelihood, and the Schwarz criterion suggest that a spatial error model with a 300-meter distance band is appropriate for the data at hand. The findings suggest that: (1) Belonging to a minority group has the strongest effect on life expectancies and (2) the effect is negative for both genders, although the negative impact is stronger for males. Tests for spatial autocorrelation on the residuals suggest that the adopted spatial error model captures nearly all spatial autocorrelation in the data, compared to alternative models

Segregation and the pandemic: The dynamics of daytime social diversity during COVID-19 in Greater Stockholm

In this study, we set out to understand how the changes in daily mobility of people during the first wave of the COVID-19 pandemic in spring 2020 influenced daytime spatial segregation. Rather than focusing on spatial separation, we approached this task from the perspective of daytime socio-spatial diversity – the degree to which people from socially different neighbourhoods share urban space during the day. By applying mobile phone data from Greater Stockholm, Sweden, the study examines weekly changes in 1) daytime social diversity across different types of neighbourhoods, and 2) population groups' exposure to diversity in their main daytime activity locations. Our findings show a decline in daytime diversity in neighbourhoods when the pandemic broke out in mid-March 2020. The decrease in diversity was marked in urban centres, and significantly different in neighbourhoods with different socio-economic and ethnic compositions. Moreover, the decrease in people's exposure to diversity in their daytime activity locations was even more profound and long-lasting. In particular, isolation from diversity increased more among residents of high-income majority neighbourhoods than of low-income minority neighbourhoods. We conclude that while some COVID-19-induced changes might have been temporary, the increased flexibility in where people work and live might ultimately reinforce both residential and daytime segregation.Peer reviewe