Testing Modeling Assumptions in the West Africa Ebola Outbreak

TL;DR

This paper evaluates common assumptions in Ebola outbreak models in West Africa, revealing that disease spread is non-homogeneous, influenced by migration and strain differences, which can improve modeling accuracy.

Contribution

It introduces methods to test key assumptions about disease transmission, migration effects, and strain transmissibility in Ebola modeling.

Findings

EVD does not homogeneously mix but spreads predictably via migration.

Initial growth rate decreases with population density.

Certain Ebola strains are more transmissible than others.

Abstract

The Ebola virus in West Africa has infected almost 30,000 and killed over 11,000 people. Recent models of Ebola Virus Disease (EVD) have often made assumptions about how the disease spreads, such as uniform transmissibility and homogeneous mixing within a population. In this paper, we test whether these assumptions are necessarily correct, and offer simple solutions that may improve disease model accuracy. First, we use data and models of West African migration to show that EVD does not homogeneously mix, but spreads in a predictable manner. Next, we estimate the initial growth rate of EVD within country administrative divisions and find that it significantly decreases with population density. Finally, we test whether EVD strains have uniform transmissibility through a novel statistical test, and find that certain strains appear more often than expected by chance.