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

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 isolated cases in the UK, the USA and Spain. Regarding the emergency of this situation, there is a need for the development of decision tools, such as mathematical models, to assist the authorities to focus their efforts in important factors to eradicate Ebola. In this work, we propose a novel deterministic spatial-temporal model, called Between-Countries Disease Spread (Be-CoDiS), to study the evolution of human diseases within and between countries. The main interesting characteristics of Be-CoDiS are the consideration of the movement of people between countries, the 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 and explain how its parameters and inputs are obtained. Then, in order to validate our approach, we consider two numerical experiments regarding the 2014-2015 Ebola epidemic. The first one studies the ability of the model in predicting the EVD evolution between countries starting from the index cases in Guinea in December 2013. The second one consists of forecasting the evolution of the epidemic by using some recent data. The results obtained with Be-CoDiS are compared to real data and other model outputs found in the literature. Finally, a brief parameter sensitivity analysis is done. A free MATLAB version of Be-CoDiS is available at: http://www.mat.ucm.es/momat/software.htm.

IoT-based cloud framework to control Ebola virus outbreak

“…Browne et al (2015) proposed SEIR model of contact tracing for the monitoring of Ebola outbreaks using effective reproduction number. Ivorra et al (2015) designed a model to analyze the spread of infectious diseases within and between countries. They used the deterministic spatial-temporal and SEIHRDB methods to predict and control the Ebola outbreak.…”

Modeling spatial invasion of Ebola in West Africa

“…Several papers have noted that Guinea’s peculiar outbreak curve is difficult to fit using simple models, due to the plateau in cumulative incidence between growth periods [18, 25, 43]. However, including spatial interaction between countries allowed the model to capture Guinea’s outbreak dynamics (Figure 2).…”

“…Several spatial EVD models have been developed to examine local spatial spread within Liberia [14, 21–23] and evaluate the potential risk of international spread using data such as airline traffic patterns [21, 24, 25]. For instance, Merler et al [21] developed a model of Ebola within Liberia using an agent-based spatial model in which the country is represented by a grid with varying population densities.…”

Predicting the spread of epidemiological diseases by using a multi-objective algorithm

“…In 2014, the Ebola virus outbreak led to a serious concern about the authorities capacity for predicting and controlling the epidemic diseases and their spread between countries. In this context, some new approaches for modelling those situations emerged, as the Between-Countries Disease Spread (Be-CoDiS) proposed at [1]. In spite of the accurate predictions achieved with this model, it highlighted the challenge of adjusting the values for the involved epidemiological parameters.…”

“…This work aims to achieve a global fitting methodology, where a set of countries linked by their migratory movements are considered. To do that, the Be-CoDiS model [1] is used and a multi-objective problem is defined. When the spread of the disease is numerically simulated according to this model, it returns the evolution of the infection.…”