Abstract
The current outbreak of Ebola virus disease (EVD) in West Africa has caused around 23000 infections by middle of Feburary 2015, with a death rate of 40%. The cases have been imported into developed countries, e.g., Spain and US, through travelers and returning healthcare workers. It is clear that the virus is a threat to public health worldwide. Given the absence of vaccine and effective treatment, response has focused so far on containment and education for prophylaxis. In studying the effects of human behavioral response to contain the current Ebola transmission, we built an epidemiological model in Spatio-Temporal Epidemiological Modeler (STEM), an open source platform. We simulate the course of the infection under various conditions from public available data and realistic assumptions about the disease dynamics. We ran this spatially extended simulation in three hardest-hit countries (i.e., Liberia, Sierra Leone and Guinea) in West Africa. A series of sensitivity analysis was performed to get insights of the likely human behavioral response to the change of disease epidemic, which helps understand the determinants of disease control. Our analysis suggests the reproductive number for the disease can be driven below 1.0 and effective control is possible if hospitalization occurs within 60 hours and/or if proper burials are processed within 34 hours. We also calibrated our model using processive period of reference data starting from March 14 reported by the WHO. We have an observation of gradual human behavior changes in the affected countries in response to the epidemic outbreak.
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Hu, K., Bianco, S., Edlund, S., Kaufman, J. (2015). The Impact of Human Behavioral Changes in 2014 West Africa Ebola Outbreak. In: Agarwal, N., Xu, K., Osgood, N. (eds) Social Computing, Behavioral-Cultural Modeling, and Prediction. SBP 2015. Lecture Notes in Computer Science(), vol 9021. Springer, Cham. https://doi.org/10.1007/978-3-319-16268-3_8
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DOI: https://doi.org/10.1007/978-3-319-16268-3_8
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