@inproceedings{1f519ef05ed647bc859731d59d4391a0,
title = "Visualizing Malaria Spread Under Climate Variability",
abstract = "In order to better control and prevent the infectious diseases, measures of vulnerability and risk to increased infectious disease outbreaks have been explored. Research investigating possible links between variations in climate and transmission of infectious diseases has led to a variety of predictive models for estimating the future impact of infectious disease under projected climate change. Underlying all of these approaches is the connection of multiple data sources and the need for computational models that can capture the spatio-temporal dynamics of emerging infectious diseases and climate variability, especially as the impact of climate variability on the land surface is becoming increasingly critical in predicting the geo-temporal evolution of infectious disease outbreaks. This paper presents an initial visualization prototype that combines data from population and climate simulations as inputs to a patch-based mosquito spread model for analyzing potential disease spread vectors and their relationship to climate variability.",
author = "X. Liang and R. Aggarwal and A. Cherif and A. Gumel and G. Mascaro and R. Maciejewski",
note = "Publisher Copyright: {\textcopyright} 2016 The Author(s) Eurographics Proceedings {\textcopyright} 2016 The Eurographics Association.; 4th Workshop on Visualisation in Environmental Sciences, EnvirVis 2016 at EuroVis 2016 ; Conference date: 06-06-2016 Through 07-06-2016",
year = "2016",
doi = "10.2312/envirvis.20161104",
language = "English (US)",
series = "EnvirVis 2016 - Workshop on Visualisation in Environmental Sciences",
publisher = "The Eurographics Association",
pages = "29--33",
editor = "Dieter Fellner",
booktitle = "EnvirVis 2016 - Workshop on Visualisation in Environmental Sciences",
}