Inferences about spatiotemporal variation in dengue virus transmission are sensitive to assumptions about human mobility: a case study using geolocated tweets from Lahore, Pakistan.

ABSTRACT: Billions of users of mobile phones, social media platforms, and other technologies generate an increasingly large volume of data that has the potential to be leveraged towards solving public health challenges. These and other big data resources tend to be most successful in epidemiological applications when utilized within an appropriate conceptual framework. Here, we demonstrate the importance of assumptions about host mobility in a framework for dynamic modeling of infectious disease spread among districts within a large urban area. Our analysis focused on spatial and temporal variation in the transmission of dengue virus (DENV) during a series of large seasonal epidemics in Lahore, Pakistan during 2011-2014. Similar to many directly transmitted diseases, DENV transmission occurs primari

SUBMITTER: Kraemer MUG 

PROVIDER: S-EPMC6404370 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature