The latest Ebola threat presents a challenge for geographers in trying to understand how it is to be mapped. Media reporting on the topic has been dominated by infographics and maps that show the global map according to traditional geographic mapping, for example the BBC and healthmap.org. These geographical representations of the spread of Ebola are problematic for understanding the spread and risk of the disease. In an international world it seems ineffective to use the traditional state map when dealing with a threat that has little regard for such spatialities. The transport and communication networks that connect us involve a spatio-temporal complexity that makes the spread of diseases and their perceived risk a hugely complex one. In order to fully understand the geography of Ebola, a mapping needs to occur that counters these traditional geographic representations. Physicist Dirk Brockmann offers a new way of understanding, calculating and visualising the spread of pandemics in an interconnected global transport network. Brockmann has developed the idea of quantitative epidemiology as a way of quantifying the risk of pandemics. Through a reimagination of the geography of diseases, Brockmann calculates how the spread of pandemics can follow a logical and predictable path. The nature of this spread is one that is visualised by Brockmann in the video posted below. Using computational and statistical models Brockmann calculates how, when and where an outbreak is most likely to develop. Brockmann has applied this network analysis model, most recently, to map out the spread of Ebola. The screen shot above is of an interactive map that has been produced as a prototype to help aid public scientists on how to understand and mitigate the spread of diseases. This map shows the nodes, hubs and connections that constitute the geographic potential of the Ebola network. This tool allows for different airports and transport hubs to be assigned distances and times from the original outbreak. Moreover, the effects on the network of removing or reducing capacity at particular hubs can be calculated, providing pragmatic risk calculations for decision makers. A particularly productive concept in Brockmann’s model is one of ‘effective distance’. Effective distance is a distance calculated from traffic flux in air-transportation networks. It seeks to understand the spread of disease outbreaks as an alternative to traditional geographical distance. “In a nutshell, places that exchange lots of passengers are closer than places that exchange a few”. Effective distance is used to predict the relative arrival times of spreading pandemics. This an idea that could be productive in areas of political geography, such as cultural identities, migration, and terrorism. The underlying geographic idea behind Brockmann’s work is that “geographic distance in a globally connected world is no longer a good indicator of how “far” locations are effectively separated from one another”. This observation will chime with geographers who are familiar with David Harvey’s concept of ‘time-space compression’. This idea, developed by other writers like Paul Virilio and Doreen Massey, observes that technological innovations condense temporal and spatial distances, altering the relationship between space and time. It seems to me that this idea is one that should be heavily reconsidered in public reporting of the latest Ebola outbreak. This interactive mapping is just one example of how such a methodology can provide both a reimagination of the networked nature of the globe, but also how it can provide a tool for helping mitigate the risks that we face in such an environment.
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August 2015
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