Relationship between population mobility, waves of COVID-19 cases, and hospital admissions for the disease: an analysis using the Google Mobility Index

BACKGROUND AND OBJECTIVE. The COVID-19 pandemic obliged public health authorities to restrict population mobility in ways that had never before been done in Spain. The restrictions aimed to reduce pressure on the public health system. This study aimed to analyze population mobility in the Spanish autonomous community of Asturias to detect a possible impact on waves of the pandemic.
MATERIAL AND METHODS. Descriptive statistics were compiled and multivariate analysis was performed with 6 independent mobility variables, namely travel to shops and places of leisure, residential areas, parks, workplaces, supermarkets and pharmacies, and transportation hubs. Data for these variables were provided by the Google Mobility Index. We explored their relationships to 3 dependent variables, as follows: daily case counts, daily hospital admissions, and daily intensive care unit admissions. These statistics were provided by the Health Observatory of the Principality of Asturias. The period studied was from March 1 to December 31, 2020.
RESULTS. Population mobility decreased nearly 100% during the first and second waves. When restrictions were relaxed in the summer, displacement to open air spaces, such as parks, increased by 333%. Nine linear regression models detected significant associations between 5 of the 6 mobility variables (R2 = 0.6) and variables reflecting the waves of infection. The 5 variables, depending on the type of mobility involved, predicted increases or decreases in daily cases or admissions for COVID-19.
CONCLUSIONS. The restrictions were widely followed by the population. Mobility indexes can be used to predict hospital admissions. We observed that although displacement toward parks and workplaces does not increase hospitalization rates, increased use of means of transport does have an impact on hospitalizations.