Global and local mobility as a barometer for COVID-19 dynamics

Global and local mobility as a barometer for COVID-19 dynamics

Publication date: Jun 15, 2020

The spreading of infectious diseases including COVID-19 depends on human interactions. In an environment where behavioral patterns and physical contacts are constantly evolving according to new governmental regulations, measuring these interactions is a major challenge. Mobility has emerged as an indicator for human activity and, implicitly, for human interactions. Here we study the coupling between mobility and COVID-19 dynamics and show that variations in global air traffic and local car traffic mobility can be used to stratify different disease phases. Our study shows that, for 26 European countries, maximal correlation between driving mobility and disease dynamics follows a normal distribution with a 17-day mean and two-day standard deviation. Our findings suggests that local mobility can serve as a quantitative metric to forecast future reproduction numbers and identify the final stages of the pandemic when mobility and reproduction become decorrelated.

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Concepts Keywords
A604 Ofnon pharmaceutical interventions
Adjacency Matrix Compartment network
Air Travel frequency countries
Apple Maps Reduction car
Austria Travel coefficient normal
Barometer Articles
Bayesian Global health
Carnival Pandemic
Carnivals Mobility model
China Cellular telephone
Cologne Simulation
Convergence
Correlation
Coupling
Cross Correlation
Cyprus
Dashboard
Decorrelated
Denmark
Diffusive
Endemic
Epidemic
Epidemiology
Equilibrium
Eurocontrol
Europe
European Union
Evolution
Exponential
Exponential Growth
Finland
Forecasting
France
Frequency
Gaussian Process
Germany
Heatmap
Heinsberg
Herd Immunity
Hotspot
Hungary
Indi
Individual Mobility
Inertia
Infection
Infectious Disease
Infectious Diseases
Inference
Inflection Point
Interact
Ireland
Italy
Latent Period
Latent Variable
Lockdown
Magnitude
Mail
Malta
Metric
Mirror
Mobile Phone
Ordinary Differential Equations
Oxford
Pandemic
Pathogenicity
Peak
Pharmaceutical
Phase III
Phase Transition
Plateau
Simulation
Slovakia
Social Behavior
Social Learning
Spain
Standard Deviation
Stanford
Stochastic
Sweden
Symmetry
Transition Rates
United Kingdom
Vaccine
Virus
Yesterdays

Semantics

Type Source Name
disease MESH infectious diseases
drug DRUGBANK Medical air
pathway REACTOME Reproduction
drug DRUGBANK Fenamole
disease MESH habits
disease MESH infection
disease MESH growth
disease MESH community
drug DRUGBANK Pentaerythritol tetranitrate
drug DRUGBANK Albendazole
drug DRUGBANK Acetylsalicylic acid
disease MESH uncertainty
drug DRUGBANK Aspartame
drug DRUGBANK Spinosad
drug DRUGBANK Coenzyme M
drug DRUGBANK Troleandomycin
disease MESH pneumonia

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