Article Text

Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward
  1. Joseph Aylett-Bullock1,2,
  2. Robert Tucker Gilman3,4,
  3. Ian Hall3,5,6,
  4. David Kennedy7,
  5. Egmond Samir Evers8,
  6. Anjali Katta1,
  7. Hussien Ahmed9,
  8. Kevin Fong10,
  9. Keyrellous Adib11,
  10. Lubna Al Ariqi11,
  11. Ali Ardalan11,
  12. Pierre Nabeth11,
  13. Kai von Harbou8,
  14. Katherine Hoffmann Pham1,12,
  15. Carolina Cuesta-Lazaro2,
  16. Arnau Quera-Bofarull2,
  17. Allen Gidraf Kahindo Maina13,
  18. Tinka Valentijn14,
  19. Sandra Harlass15,
  20. Frank Krauss2,
  21. Chao Huang16,
  22. Rebeca Moreno Jimenez17,
  23. Tina Comes18,
  24. Mariken Gaanderse18,
  25. Leonardo Milano14,
  26. Miguel Luengo-Oroz1
  1. 1UN Global Pulse, United Nations, New York, New York, USA
  2. 2Institute for Data Science, Durham University, Durham, UK
  3. 3Centre for Crisis Studies and Mitigation, The University of Manchester, Manchester, UK
  4. 4Department of Earth and Environmental Sciences, The University of Manchester, Manchester, UK
  5. 5Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK
  6. 6Department of Mathematics, The University of Manchester, Manchester, UK
  7. 7UK Public Health Rapid Support Team, London School of Hygiene & Tropical Medicine/Public Health England, London, UK
  8. 8WHO Cox’s Bazar Emergency Sub-Office, United Nations, Cox's Bazar, Bangladesh
  9. 9UNHCR Cox’s Bazar Sub-Office, United Nations, Cox's Bazar, Bangladesh
  10. 10Department of Science, Technology, Engineering and Public Policy, University College London, London, UK
  11. 11WHO Eastern Mediterranean Regional Office, United Nations, Cairo, Egypt
  12. 12Stern School of Business, New York University, New York City, New York, USA
  13. 13UNHCR Public Health Unit, United Nations, Cox's Bazar, Bangladesh
  14. 14OCHA Centre for Humanitarian Data, United Nations, The Hague, The Netherlands
  15. 15UNHCR Public Health Unit, United Nations, Geneva, Switzerland
  16. 16UNHCR Global Data Service, United Nations, Copenhagen, New York, USA
  17. 17UNHCR Innovation, United Nations, Geneva, Switzerland
  18. 18Faculty of Technology, Policy, and Management, Department of Engineering Systems and Services, Delft University of Technology, Delft, The Netherlands
  1. Correspondence to Dr Joseph Aylett-Bullock; joseph{at}


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.

  • epidemiology
  • mathematical modelling

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  • Handling editor Seye Abimbola

  • Twitter @josephpbullock, @GilmanTucker

  • Contributors JA-B, ML-O conceived the project. All authors contributed to the writing of this manuscript. JA-B is the guarantor.

  • Funding United Nations Global Pulse work is supported by the Governments of Sweden and Canada, and the William and Flora Hewlett Foundation. JA-B, AQ-B and CC-L are also supported by the UKRI-STFC grant number ST/P006744/1. The UK Public Health Rapid Support Team is funded by UK Aid from the Department of Health and Social Care and is jointly run by Public Health England and the London School of Hygiene Tropical Medicine. IH is a principal investigator of the NIHR Policy Research Programme in Operational Research for Emergency Response Analysis (OPERA, PR-R17-0916-21001) and supported by JUNIPER (Joint UNiversities Pandemic and Epidemiological Research) and PROTECT COVID-19 National Core Study on Transmission and Environment. FK gratefully acknowledges funding as Royal Society Wolfson Research fellow.

  • Disclaimer The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated including the Department of Health and Social Care, NIHR, the WHO, or the United Nations.

  • Competing interests No competing interests expressed.

  • Ethics Ethics approval was not required for this study as no data was collected or analysed.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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