THE DEVELOPMENT OF A GLOBAL CONFLICT INDEX AND WEB GIS TO MAP THE INDIRECT IMPACTS OF ARMED CONFLICT

The aim of the research is to create a Conflict Index and web GIS that would enable humanitarian agencies to increase their conflict competencies on a global scale. This idea of creating a ‘Conflict Index’ was initiated by Concern Worldwide as a result of an in-house investigation into how they might become better at responding to the effects of armed conflict, and prevent it becoming a mitigating factor in their ability to deliver effective programs.

Currently, there is no method of quantifying the number of people affected by conflict or the severity of their needs. There are several databases and indices that track the location, duration and intensity of conflicts worldwide, however, there is no estimate of the overall human cost of violent or armed conflict on civilian populations.

As conflict cannot be fully captured by one individual indicator, a simple three-dimensional topology; Security & Social, Coping Capacity, and Consequences, is proposed to measure the indirect impacts of armed conflict on a population/area. This multilayer topology builds up a conflict profile by bringing together ten components and twenty-eight different indicators.

The conflict score is then calculated using the Weighted Sum tool in the Spatial Analyst Toolbox of ArcMap, where each of the three dimensions are treated with equal weight and importance.

The final web GIS will act as an interactive conflict tool that will aid in informing humanitarian organisations on their security planning, decision making and program design, and in turn increase their program competencies in conflict affected countries.

1           Introduction

1.1         Background

Conflict, in comparison even to hunger, climate change or natural disasters, is an unparalleled hazard in its destructive impact on human development. It holds around one fifth of the world’s population under the threat of large-scale organised violence (Beatty 2016).

Armed conflict in particular, which is defined by the Uppsala Conflict Data Program as “a contested incompatibility that concerns government and/or territory where the use of armed force between two parties, of which at least one is the government of a state, results in at least 25 battle-related deaths in one calendar year”, can cause catastrophic impacts in a country by “trapping populations in situations of protracted disaster and the cumulative impacts of impoverishment and vulnerability” (Raleigh et al. 2010; Wallensteen and Sollenberg 1998).

Multiple studies have shown that the impact of armed conflict goes far beyond battle related deaths, and will extend to a breakdown of supply lines, increased endemic hunger and malnutrition by depleting food stocks and absent harvests, loss of assets, mass displacement, deterioration of health services, as well as serious psycho-social trauma to civilians (De Groeve et al. 2016b).

These impacts, if left unaided, pose catastrophic humanitarian risk, which in turn can lead to debilitating transgenerational impacts with the potential to reverse development gains by up to twenty years (Beatty 2016). In a very simplistic view, the poorest regions on the world will be those most affected by armed conflict, and as approximately half of the worlds global poor are currently living in conflict affected zones (The World Bank 2011), it is clear that the need to work more effectively with conflict data has never been more crucial.

The idea of creating a ‘Conflict Index’ using the extensive amount of available conflict data, was initiated by Concern as a result of an ongoing in-house investigation into how field teams might become better at responding to the effects of armed conflict.

Concern, through partnership with the International Food Policy Research Institute (IFPRI), has an existing data-driven publication; The Global Hunger Index (GHI), (Towey et al. 2016). This index is a flagship document in the hunger/nutrition world that uses data gathered from a cross-section of indicators to generate ‘hunger’ scores for every country (Ward and Beatty 2016).

There is currently no definitive method of quantifying the number