Exploring the human-animal interface of Ebola virus disease outbreaks in Central and West Africa

Abstract

Ebola Virus Disease (EVD) continues to be a severe issue to this day, as proven by the ongoing outbreak in the Democratic Republic of Congo. So far, there have been over 30,000 confirmed cases of EVD and over 13,000 deaths resulting from EVD in Central and West Africa alone. Whereas the prevention and treatment of EVD have been well studied after the 2013-16 outbreak in West Africa, the emergence of human outbreaks and their mechanisms have yet to be explored in detail. In particular, it has yet to be clarified whether the emergence records offer any theoretical insight into the changing interface between humans and animal reservoirs or vectors. Here I explore the epidemiological records of emergence, investigating predominant causes of the introduction of EVD into the human population, their characteristics, and frequencies. I reviewed literature on every documented outbreak in the world, then narrowed down my point of interest to only the literature pertaining to West and Central African outbreaks and outbreaks outside of Africa infected by strains of the virus that originated in Africa. Next, I noted every outbreak that can be traced back to a single zoonotic spillover to include the animal source of infection in my analyses. Through statistical analysis, I have shown that (i) the leading cause of emergence was eating and hunting habits, (ii) primates act as the main source of zoonotic spillover, and (iii) Zaire ebolavirus is the most virulent type of ebolaviruses. Moreover, the trend of emergence was demonstrated to follow a more skewed distribution than a Poisson process, indicating that some unknown, underlying, non-random mechanisms are likely to govern the spillover events. In the Democratic Republic of Congo, an increasing emergence trend was favored compared with a purely random emergence model. Outbreak event data and their causative viruses should be explored biologically and epidemiologically to possibly predict future outbreak events. Future work could investigate the mechanisms that are governing the increasing trend in spillovers happening in the DRC.