Monitoring the Spatial Spread of COVID-19 and Effectiveness of Control Measures Through Human Movement Data: Proposal for a Predictive Model Using Big Data Analytics.

ABSTRACT:

Background

Human movement is one of the forces that drive the spatial spread of infectious diseases. To date, reducing and tracking human movement during the COVID-19 pandemic has proven effective in limiting the spread of the virus. Existing methods for monitoring and modeling the spatial spread of infectious diseases rely on various data sources as proxies of human movement, such as airline travel data, mobile phone data, and banknote tracking. However, intrinsic limitations of these data sources prevent us from systematic monitoring and analyses of human movement on different spatial scales (from local to global).

Objective

Big data from social media such as geotagged tweets have been widely used in human mobility studies, yet more research is needed to validate the capab

SUBMITTER: Li Z 

PROVIDER: S-EPMC7752182 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature