Paper Info
Title
Forecasting the Spread of Mosquito-Borne Disease using Publicly Accessible Data: A Case Study in Chikungunya.
Abstract
Mosquito-borne diseases account for multiple public health challenges in our modern world. The international health community has seen a number of mosquito-borne diseases come to the forefront in recent years, including West Nile virus, Chikungunya virus, and currently, Zika virus. Predicting the spread of mosquito-borne disease can aid early decision support for when and how to employ public health interventions within a community; however, accurate and fast predictions, months into the future, are difficult to achieve in urgent scenarios, particularly when little information is known about infection rates. New sources of information including social media have been proposed to accelerate the development of predictive models of disease progression. In this research, we adapted a previously described model for the spread of mosquito-borne disease using open intelligence sources. The novel implementation of a mixed-model for mosquito-borne disease was capable of being executed in minimal runtime. The results indicate that this model yields fast and relevant results with acceptable margins of error.
Year
Venue
Field
2016
AMIA
Mosquito-borne disease,Biology,Chikungunya,Virology
DocType
Volume
Citations 
Conference
2016
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Kathryn M. Cooper100.68
Dhundy Bastola211017.73
Robin Gandhi300.68
Dario Ghersi4667.04
Steven H. Hinrichs5263.84
Marsha Morien600.34
Ann L. Fruhling76418.25