MEDCollector: Multisource Epidemic Data Collector

Abstract

Abstract. This paper analyzes the requirements and presents a novel approach to the development of a system for epidemiological data collection and integration based on the principles of interoperability and modularity. Accurate and timely epidemic models require the integration of large, fresh datasets. Thus, from an e-science perspective, collected data should be shared seamlessly across multiple applications. This is addressed by our approach, MEDCollector, trough workflow design enables the extraction of data from multiple Web sources. The mapping of extracted entities to ontologies will guarantee the consistency within gathered datasets, and therefore enhance epidemic modeling tools.

Tracking employment shocks using mobile phone data

“…Prior work has linked news stories with stock prices [19][20][21] and used web search or social media data to forecast labor markets [22][23][24][25][26], consumer behavior [27,28], automobile demand, vacation destinations [15,29]. Research on social media, search, and surfing behavior have been shown to signal emerging public health problems [30][31][32][33][34][35][36][37]; although for a cautionary tale see [38]. And recent efforts have even been made towards leveraging Twitter to detect and track earthquakes in real-time detection faster than seismographic sensors [39][40][41].…”