Agent-based Modelling for Ebola Risk Reduction: Understanding and Mitigating the Potential for Global Transportation-fuelled Epidemics (ABMERR)

点击翻译按钮获取中文摘要

Outbreaks of Ebola have gripped the world's attention in recent years, from the Western Africa Ebola epidemic of 2013-2016 to the ongoing outbreak in Democratic Republic of Congo (DRC). The first outbreak of the Ebola virus was recorded in 1976 in what was then called Zaire (now the Democratic Republic of Congo); 318 cases were identified, of which 280 people died. Since that time, changes to infrastructure, travel patterns, population density, and climate have led to larger and more frequent epidemic outbreaks of the disease. The Western Africa Ebola epidemic saw cases spread as far as Italy, Spain, and the United States. The outbreak in DRC is now in its 11th month with no signs of abating and extensive disruptions and cost for local people. Humanitarian groups including Médecins Sans Frontières (MSF) and the British Red Cross (BRC) are organising local responses to the crisis, but the magnitude of the problem is so great that there are no established techniques for resolving it. Humanitarians are in urgent need of operational intelligence in order to fight increasingly large epidemics. To that end, this fellowship aims to develop a simulation of the spread of Ebola through a region as a function of human behaviour and movement. I will undertake this work in conjunction with partners from MSF's Manson Unit for Innovation and BRC's GIS team. The project will create and make use of an agent based model (ABM) to simulate the interactions and choices of individual people living, working, and moving within Ebola-effected areas. By capturing the ways in which Ebola is transmitted between people through funerary practices, caring relationships, and the seeking of medical care, the simulation will help the project's humanitarian partners understand how different interventions may influence the spread of disease in these social contexts. The research will particularly focus on analysing and visualising the results in ways that are accessible to the humanitarian project partners.The work will make use of open source data to estimate populations and recreate transportation networks. These synthetically generated datasets will be fed into the ABM, giving more insight into where outbreaks may flare up and where they may travel next based on appropriate local behaviours and choices. In turn, the software developed as part of the project will be made open source. By making the simulation software freely available, the research will be accessible to the humanitarian partners, but also government organisations and other researchers. The toolkits will be developed with the needs of non-specialists in mind, so that they are suitable for users with potentially sensitive datasets and without high-powered machines or constant access to the internet. The project aims to strengthen the ties between academics and humanitarians, and to make cutting edge methodologies available to non-specialists.The fellowship will provide resources to help humanitarians and government to understand their options in the fight against Ebola. It will also make these new tools available to other researchers, propagating outward and facilitating new work. Finally, it will allow me to establish myself as an internationally recognised leader in the field of ABM for humanitarian modelling, allowing me to push this line of research forward in the future.