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A multi-layer network approach to model the situation before and after the occurrence of humanitarian crisis

Abstract : The complexity of the situation during a humanitarian crisis makes its overall vision difficult. The response to crisis involves many heterogeneous entities, including a high diversity of field actors (international organizations, local NGOs, army), infrastructures (air, health, water, road, telecom), transportation means (vehicles), affected populations and available resources. Data available in real time is often incomplete and dynamic. For example, some roads or other logistical infrastructure may be destroyed by the disaster and need to be fixed to facilitate humanitarian response operations. Collecting and updating data takes time and is therefore not always considered as a priority, especially in this specific context where resources are scare and population needs are critical. Despite their high impact, both in lives and in dollar, few paper actually studied humanitarian crisis with a complex network approach. While all provide elements to better analyze the situation, they all focus on specific, limited scopes. The complexity and the overall understanding of the situation is therefore limited. This is the limitation we focus on: providing an exhaustive view of the situation, combining various elements. We propose to model the response to a humanitarian crisis with a multi-layer network approach. The model can provide useful insights during operations, to better understand what is going on, and simulate various response scenarios to choose the best way to utilize the resources available. It can also be used in the preparedness phase, to propose ways to improve the resilience of the actual network.
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Contributor : Aurelie Charles Connect in order to contact the contributor
Submitted on : Friday, February 18, 2022 - 9:57:56 AM
Last modification on : Saturday, September 24, 2022 - 2:28:05 PM


  • HAL Id : hal-03579441, version 1


Aurelie Charles, Chantal Cherifi, Guillaume Bouleux. A multi-layer network approach to model the situation before and after the occurrence of humanitarian crisis. EURO-Hope 2021, Nov 2021, Helsinki, France. ⟨hal-03579441⟩



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