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Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward

Aylett-Bullock, Joseph; Gilman, Robert Tucker; Hall, Ian; Kennedy, David; Evers, Egmond Samir; Katta, Anjali; Ahmed, Hussien; Fong, Kevin; Adib, Keyrellous; Al Ariqi, Lubna; Ardalan, Ali; Nabeth, Pierre; von Harbou, Kai; Hoffmann Pham, Katherine; Cuesta-Lazaro, Carolina; Quera-Bofarull, Arnau; Gidraf Kahindo Maina, Allen; Valentijn, Tinka; Harlass, Sandra; Krauss, Frank; Huang, Chao; Moreno Jimenez, Rebeca; Comes, Tina; Gaanderse, Mariken; Milano, Leonardo; Luengo-Oroz, Miguel

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Authors

Joseph Aylett-Bullock

Robert Tucker Gilman

Ian Hall

David Kennedy

Egmond Samir Evers

Anjali Katta

Hussien Ahmed

Kevin Fong

Keyrellous Adib

Lubna Al Ariqi

Ali Ardalan

Pierre Nabeth

Kai von Harbou

Katherine Hoffmann Pham

Carolina Cuesta-Lazaro

Arnau Quera-Bofarull

Allen Gidraf Kahindo Maina

Tinka Valentijn

Sandra Harlass

Chao Huang

Rebeca Moreno Jimenez

Tina Comes

Mariken Gaanderse

Leonardo Milano

Miguel Luengo-Oroz



Abstract

The spread of infectious diseases such as COVID-19 presents many challenges to healthcare systems and infrastructures across the world, exacerbating inequalities and leaving the world’s most vulnerable populations at risk. Epidemiological modelling is vital to guiding evidence-informed or data-driven decision making. In forced displacement contexts, and in particular refugee and internally displaced people (IDP) settlements, it meets several challenges including data availability and quality, the applicability of existing models to those contexts, the accurate modelling of cultural differences or specificities of those operational settings, the communication of results and uncertainties, as well as the alignment of strategic goals between diverse partners in complex situations. In this paper, we systematically review the limited epidemiological modelling work applied to refugee and IDP settlements so far, and discuss challenges and identify lessons learnt from the process. With the likelihood of disease outbreaks expected to increase in the future as more people are displaced due to conflict and climate change, we call for the development of more approaches and models specifically designed to include the unique features and populations of refugee and IDP settlements. To strengthen collaboration between the modelling and the humanitarian public health communities, we propose a roadmap to encourage the development of systems and frameworks to share needs, build tools and coordinate responses in an efficient and scalable manner, both for this pandemic and for future outbreaks.

Citation

Aylett-Bullock, J., Gilman, R. T., Hall, I., Kennedy, D., Evers, E. S., Katta, A., …Luengo-Oroz, M. (2022). Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward. BMJ Global Health, 7(3), Article e007822. https://doi.org/10.1136/bmjgh-2021-007822

Journal Article Type Article
Acceptance Date Jan 23, 2022
Online Publication Date Mar 9, 2022
Publication Date Mar 9, 2022
Deposit Date Jul 6, 2022
Publicly Available Date Jul 6, 2022
Journal BMJ Global Health
Publisher BMJ Publishing Group
Peer Reviewed Peer Reviewed
Volume 7
Issue 3
Article Number e007822
DOI https://doi.org/10.1136/bmjgh-2021-007822
Public URL https://durham-repository.worktribe.com/output/1198918

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Publisher Licence URL
http://creativecommons.org/licenses/by-nc/4.0/

Copyright Statement
© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.





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