Universidad Complutense de Madrid
E-Prints Complutense

Be-CoDiS: A mathematical model to predict the risk of human diseases spread between countries. Validation and application to the 2014-2015 Ebola Virus Disease epidemic

Impacto

Downloads

Downloads per month over past year

Ivorra, Benjamin and Ngom, Diène and Ramos del Olmo, Ángel Manuel (2015) Be-CoDiS: A mathematical model to predict the risk of human diseases spread between countries. Validation and application to the 2014-2015 Ebola Virus Disease epidemic. Bulletin of mathematical biology, 77 (9). pp. 1668-1704. ISSN 0092-8240 (Submitted)

[img]
Preview
PDF
531kB
[img] PDF
Restringido a Repository staff only

1MB

Official URL: http://link.springer.com/article/10.1007%2Fs11538-015-0100-x


URLURL Type
http://arxiv.orgOrganisation
http://link.springer.comPublisher


Abstract

Ebola virus disease is a lethal human and primate disease that currently requires a particular attention from the international health authorities due to important outbreaks in some Western African countries and possible spread to other continents, which has already occurred in the USA and Spain. Regarding the emergency of this situation, there is a need of development of decision tools to assist the authorities to focus their efforts in important factors to eradicate Ebola. In particular, mathematical modelling can help to predict the possible evolution of the Ebola outbreaks and to give some recommendations about surveillance. In this work, we propose a novel spatial and temporal model, called Be-CoDiS (BetweenCOuntries Disease Spread), to study the evolution of human diseases between countries. The goal is to simulate the spread of a particular disease and identify risk zones worldwide. The main interesting characteristics of Be-CoDiS are the consideration of the migratory flux between countries and control measure effects and the use of time dependent coefficients adapted to each country. First, we focus on the mathematical formulation of each component of the model. Next, in order to validate our approach, we consider various numerical experiments regarding the 2014 Ebola epidemic. In particular, we study the ability of the model in predicting the EVD evolution at 30 days and until the end of the epidemic. The results are compared to real data and other models outputs found in the literature. Finally, a brief parameter sensitivity analysis is done.


Item Type:Article
Uncontrolled Keywords:Epidemiological modelling; Ebola Virus Disease
Subjects:Sciences > Mathematics > Operations research
Medical sciences > Medicine > Communicable diseases
Medical sciences > Biology > Biomathematics
ID Code:28809
Deposited On:26 Feb 2015 07:54
Last Modified:12 Dec 2018 15:06

Origin of downloads

Repository Staff Only: item control page