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Optimizing the Access to Healthcare Services in Dense Refugee Hosting Urban Areas: A Case for Istanbul

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Guide to Mobile Data Analytics in Refugee Scenarios

Abstract

With over 3.5 million refugees, Turkey continues to host the world’s largest refugee population. This introduced several challenges in many areas including access to healthcare system. Refugees have legal rights to free healthcare services in Turkey’s public hospitals. With the aim of increasing healthcare access for refugees, we looked at where the lack of infrastructure is felt the most. Our study attempts to address these problems by assessing whether Migrant Health Centers’ locations are optimal. The aim of this study is to improve refugees’ access to healthcare services in Istanbul by improving the locations of health facilities available to them. We used call data records provided by Turk Telekom.

Authors’ Contributions: Muhammed Tarık Altuncu conducted the computational research. Nur Sevencan and Ayşe Seyyide Kaptaner were responsible for the social science research and obtaining additional data. All authors analysed the data and wrote the manuscript.

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Notes

  1. 1.

    Voronoi regions are polygonal regions constructed by unit areas that have the same number of base stations as the nearest one [22].

  2. 2.

    Details about the Distance Matrix API could be obtained from https://developers.google.com/maps/documentation/distance-matrix/start.

  3. 3.

    The interactive map is published on http://bit.ly/refugee_map.

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Acknowledgements

We thank the rest of the members of TRT World’s team for the Data for Refugees challenge: Basri Ciftci, Berk Baytar, Soud Hyder, and Yasin Sancaktutan. We also thank Mehmet Efe Akengin for providing intellectual support, and Hamza Osmanogullari for logistic support.

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Correspondence to M. Tarik Altuncu .

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Altuncu, M.T., Kaptaner, A.S., Sevencan, N. (2019). Optimizing the Access to Healthcare Services in Dense Refugee Hosting Urban Areas: A Case for Istanbul. In: Salah, A., Pentland, A., Lepri, B., Letouzé, E. (eds) Guide to Mobile Data Analytics in Refugee Scenarios. Springer, Cham. https://doi.org/10.1007/978-3-030-12554-7_20

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  • DOI: https://doi.org/10.1007/978-3-030-12554-7_20

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