Informed decision-making on healthcare facility locations in expanding refugee camps

Researching the interplay between healthcare facility locations and refugee settlement behavior

Master Thesis (2020)
Author(s)

M.M.T. Nering Bögel (TU Delft - Technology, Policy and Management)

Contributor(s)

M. Comes – Mentor (TU Delft - Transport and Logistics)

Martijn Warnier – Mentor (TU Delft - System Engineering)

Faculty
Technology, Policy and Management
Copyright
© 2020 Meyke Nering Bögel
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Meyke Nering Bögel
Graduation Date
13-01-2020
Awarding Institution
Delft University of Technology
Programme
['Engineering and Policy Analysis']
Faculty
Technology, Policy and Management
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Abstract

In 2018, the number of forcibly displaced people all over the world was higher than ever before. More than a third of this group are refugees, often living in refugee camps.  NGOs try to deliver all necessary aid to these camps, while facing limited access and resources. Therefore, they want to optimize the results of the aid they deliver. The structure and layout of a refugee camp cannot simply be adapted, as it has evolved over time. However, this path-dependent nature of the camp expansion has not been studied from the perspective of the refugees yet. This study combines the process of camp expansion with the location decisions for healthcare facilities in expanding refugee camps. In an agent-based model, the camp expansion is simulated according to the settling preferences of refugees. These preferences are proximity to roads, to other shelters and to healthcare facilities. The locations of healthcare facilities are determined using two optimization algorithms. By using predictions about future camp expansion based on the settling preferences of refugees, the healthcare providers can adapt their locating decisions to the settling preferences of refugees. Simultaneously, the placement of new facilities designed for expected camp expansion can affect the settling choices of refugees. The success of the optimization is measured in the resulting accessibility of healthcare facilities in refugee camps. First, it is found that the facility location optimization improves when future camp expansion is taken into account, if refugees can choose a location to settle upon arrival in a refugee camp. On the contrary, if refugees cannot choose a location to settle, predictions about camp expansion should not be included. Second, in case a space restriction of 45m2 surface area per person is maintained in a refugee camp, it is recommended to locate healthcare facilities using an algorithm that minimizes the travel distance between refugees and healthcare facilities. However, if the available surface area per person is significantly lower than 45m2, it is recommended to locate healthcare facilities in a refugee camp using an algorithm that maximizes the coverage ratio of shelters in the camp. Finally, when shelters are spread evenly over the camp, the possibility to locate healthcare facilities in strategic places enhances. This improves the accessibility of healthcare facilities for all refugees.

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