Mobility and Mortality During the COVID-19 Pandemic

Pedestrian Deaths During the COVID-19 Pandemic

The COVID pandemic provides a natural experiment examining how a 50-60% reduction in pedestrian activity might lead to a reduction in pedestrian deaths. We assessed whether the reduction in pedestrian deaths was proportional to a one-to-one matching presumed in statistics correlating mobility with fatality. The primary analysis examined New York (largest city in US), and the validation analysis examined Toronto (largest city in Canada). We identified pedestrian activity in each location from the Apple Mobility database, normalized to the baseline in January 2020. We calculated monthly pedestrian deaths from the Vision Zero database in each city with baseline data from 3 prior years. We found a large initial reduction in pedestrian deaths during the lockdown in New York that was transient and not statistically significant during the summer and autumn despite sustained reductions in pedestrian activity. Similarly, we found a large initial reduction in pedestrian deaths during the lockdown in Toronto that was transient and not sustained. Together, these data suggest the substantial reductions in pedestrian activity during the COVID pandemic have no simple correlation with pedestrian fatality counts in the same locations. An awareness of this finding emphasizes the role of unmeasured modifiable individual factors beyond pedestrian infrastructure or other structural contributors.

Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal

This study examines the possibility of correlation between the data on human mobility restrictions and the COVID-19 infection rates in two European countries: Poland and Portugal. The aim of this study is to verify the correlation and causation between mobility changes and the infection spread as well as to investigate the impact of the introduced restrictions on changes in human mobility. The data were obtained from Google Community Mobility Reports, Apple Mobility Trends Reports, and The Humanitarian Data Exchange along with other reports published online. All the data were organized in one dataset, and three groups of variables were distinguished: restrictions, mobility, and intensity of the disease. The causal-comparative research design method is used for this study. The results show that in both countries the state restrictions reduced human mobility, with the strongest impact in places related to retail and recreation, grocery, pharmacy, and transit stations. At the same time, the data show that the increase in restrictions had strong positive correlation with stays in residential places both in Poland and Portugal.

Novel mobility index tracks COVID-19 transmission following stay-at-home orders

Considering the emergence of SARS-CoV-2 variants and low vaccine access and uptake, minimizing human interactions remains an effective strategy to mitigate the spread of SARS-CoV-2. Using a functional principal component analysis, we created a multidimensional mobility index (MI) using six metrics compiled by SafeGraph from all counties in Illinois, Ohio, Michigan and Indiana between January 1 to December 8, 2020. Changes in mobility were defined as a time-updated 7-day rolling average. Associations between our MI and COVID-19 cases were estimated using a quasi-Poisson hierarchical generalized additive model adjusted for population density and the COVID-19 Community Vulnerability Index. Individual mobility metrics varied significantly by counties and by calendar time. More than 50% of the variability in the data was explained by the first principal component by each state, indicating good dimension reduction. While an individual metric of mobility was not associated with surges of COVID-19, our MI was independently associated with COVID-19 cases in all four states given varying time-lags. Following the expiration of stay-at-home orders, a single metric of mobility was not sensitive enough to capture the complexity of human interactions. Monitoring mobility can be an important public health tool, however, it should be modelled as a multidimensional construct.