Risk assessment of Ebola virus disease spreading in Uganda using a multilayer temporal network
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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
bioRxiv
Abstract
Network-based modelling of infectious diseases apply compartmental models on a contact network, which makes the epidemic
process crucially dependent on the network structure. For highly contagious diseases such as Ebola virus disease (EVD), the
inter-personal contact plays the most vital role in the human to human transmission. Therefore, for accurate representation
of the EVD spreading, the contact network needs to resemble the reality. Prior research work has mainly focused on static
networks (only permanent contacts) or activity driven networks (only temporal contacts) for Ebola spreading. A comprehensive
network for EVD spreading should include both these network structures, as there are always some permanent contacts
together with temporal contacts. Therefore, we propose a multilayer temporal network for Uganda, which is at risk of Ebola
outbreak from the neighboring Democratic Republic of Congo (DRC) epidemic. The network has a permanent layer representing
permanent contacts among individuals within family level, and a data driven temporal network for human movements motivated
by cattle trade, fish trade, or general communications. We propose a Gillespie algorithm with the susceptible-infected-recovered
(SIR) compartmental model to simulate the evolution of the EVD spreading as well as to evaluate the risk throughout our
network. As an example, we applied our method to a multilayer network consisting of 23 districts along different movement
routes in Uganda starting from bordering districts of DRC to Kampala. Simulation results shows that some regions are at
higher risk of infection, suggesting some focal points for Ebola preparedness and providing direction to inform interventions in
the field. Simulation results also shows that decreasing physical contacts as well as increasing preventive measures result in
a reduction of chances to develop an outbreak. Overall, the main contribution of this paper lies in the novel method for risk
assessment, the accuracy of which can be increased by increasing the amount and the accuracy of the data used to build the
network and the model.
Description
Keywords
Risk assessment, Ebola virus disease, Uganda
Citation
Riad, M. H., Sekamatte, M., Ocom, F., Makumbi, I., & Scoglio, C. M. (2019). Risk assessment of Ebola virus disease spreading in Uganda using a multilayer temporal network. bioRxiv, 645598. https://doi.org/10.1101/645598