Abstract
Epidemics have disturbed human lives for centuries causing massive numbers of deaths and illness among people and animals. Due to increase in urbanization, the possibility of worldwide epidemic is growing too. Infectious diseases like Ebola remain among the world’s leading causes of mortality and years of life lost. Addressing the significant disease burdens, which mostly impact the world’s poorest regions, is a huge challenge which requires new solutions and new technologies. This paper describes some of the models and mobile applications that can be used in determining the transmission, predicting the outbreak and preventing from an Ebola epidemic.
This chapter has been developed by Jesse Shaw and Flavio Villanustre, LexisNexis Risk Solutions, and Borko Furht, Ankur Agarwal, and Abhishek Jain, Florida Atlantic University.
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Acknowledgments
This work has been funded by the NSF Award No. CNS 1512932 RAPID: Modelling Ebola Spread and Developing Decision Support System Using Big Data Analytics, 2015–2016.
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© 2016 Springer International Publishing Switzerland
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Shaw, J., Villanustre, F., Furht, B., Agarwal, A., Jain, A. (2016). Modeling Ebola Spread and Using HPCC/KEL System. In: Big Data Technologies and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-44550-2_14
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DOI: https://doi.org/10.1007/978-3-319-44550-2_14
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