Article Text
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.
- epidemiology
- mathematical modelling
Data availability statement
No data was collected or analysed.
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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Data availability statement
No data was collected or analysed.
Supplementary materials
Supplementary Data
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Footnotes
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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