The Impacts of Mobility on Covid-19 Dynamics: Using Soft and Hard Data

TL;DR

This study analyzes how mobility reductions, measured via soft and hard data, significantly decreased Covid-19 cases and deaths during 2020-2021, highlighting the importance of behavioral factors and mobility restrictions.

Contribution

It introduces the use of Google Trends and News indexes as controls to better identify the causal impact of mobility on Covid-19 spread.

Findings

A 1% increase in residential mobility reduces cases by at least 3.02% and deaths by 2.43%.

Mobility restrictions in 2020 had significant effects on reducing Covid-19 spread.

Reductions in workplace mobility also decreased cases by about 1% and deaths by 2%.

Abstract

This paper has the goal of evaluating how changes in mobility has affected the infection spread of Covid-19 throughout the 2020-2021 years. However, identifying a "clean" causal relation is not an easy task due to a high number of non-observable (behavioral) effects. We suggest the usage of Google Trends and News-based indexes as controls for some of these behavioral effects and we find that a 1\% increase in residential mobility (i.e. a reduction in overall mobility) have significant impacts for reducing both Covid-19 cases (at least 3.02\% on a one-month horizon) and deaths (at least 2.43\% at the two-weeks horizon) over the 2020-2021 sample. We also evaluate the effects of mobility on Covid-19 spread on the restricted sample (only 2020) where vaccines were not available. The results of diminishing mobility over cases and deaths on the restricted sample are still observable (with similar magnitudes in terms of residential mobility) and cumulative higher, as the effects of restricting workplace mobility turns to be also significant: a 1\% decrease in workplace mobility diminishes cases around 1\% and deaths around 2\%.