Impact of global change on future Ebola emergence and epidemic potential in Africa

Abstract

Animal-borne or zoonotic human diseases (e.g., SARS, Rabies) represent major health and economic burdens throughout the world, disproportionately impacting poor communities. In 2013-2016, an outbreak of the Ebola virus disease (EVD), a zoonotic disease spread from animal reservoirs caused by the Zaire Ebola virus (EBOV), infected approximately 30,000 people, causing considerable negative social and economic impacts in an unexpected geographical location(Sierra Leone, Guinea, and Liberia). It is not known whether the spatial distribution of this outbreak and unprecedented severity was precipitated by environmental changes and, if so, which areas might be at risk in the future. To better address the major health and economic impacts of zoonotic diseases we develop a system-dynamics approach to capture the impact of future climate, land use and human population change on Ebola (EVD). We create future risk maps for affected areas and predict between a 1.75-3.2 fold increase in EVD outbreaks per year by 2070. While the best case future scenarios we test saw a reduction in the likelihood of epidemics, other future scenarios with high human population growth and low rates of socioeconomic development saw a fourfold increase in the risk of epidemics occurring and almost 50% increase in the risk of catastrophic epidemics. As well as helping to target where health infrastructure might be further developed or vaccines best deployed, our modelling framework can be used to target global interventions and forecast risk for many other zoonotic diseases.\n\nSignificance StatementDespite the severe health and economic impacts of outbreaks of diseases like SARS or Zika, there has been surprisingly little progress in predicting where and when human infectious disease outbreaks will occur next. By modelling the impacts of future climate, land use and human population change on one particular disease Ebola, we develop future risk maps for the affected areas and predict 1.7-3.2 times as many human Ebola outbreaks per year by 2070, and a 50% increase in the chance that these outbreaks will become epidemics. As well as helping to target where health infrastructure might be further developed or vaccines deployed, our approach can also be used to target actions and predict risk hotspots for many other infectious diseases.