Epidemiological modelling in refugee and internally displaced people settlementsCitation formats

  • External authors:
  • Joseph Aylett-Bullock
  • 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
  • Frank Krauss
  • Chao Huang
  • Rebeca Moreno Jimenez
  • Tina Comes
  • Mariken Gaanderse
  • Leonardo Milano
  • Miguel Luengo-Oroz

Standard

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.

In: BMJ Global Health, Vol. 7, No. 3, e007822, 09.03.2022.

Research output: Contribution to journalArticlepeer-review

Harvard

Aylett-Bullock, J, Gilman, RT, Hall, I, Kennedy, D, Evers, ES, Katta, A, Ahmed, H, Fong, K, Adib, K, Al Ariqi, L, Ardalan, A, Nabeth, P, von Harbou, K, Hoffmann Pham, K, Cuesta-Lazaro, C, Quera-Bofarull, A, Gidraf Kahindo Maina, A, Valentijn, T, Harlass, S, Krauss, F, Huang, C, Moreno Jimenez, R, Comes, T, Gaanderse, M, Milano, L & Luengo-Oroz, M 2022, 'Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward', BMJ Global Health, vol. 7, no. 3, e007822. https://doi.org/10.1136/bmjgh-2021-007822

APA

Aylett-Bullock, J., Gilman, R. T., Hall, I., Kennedy, D., Evers, E. S., Katta, A., Ahmed, H., Fong, K., Adib, K., Al Ariqi, L., Ardalan, A., Nabeth, P., von Harbou, K., Hoffmann Pham, K., Cuesta-Lazaro, C., Quera-Bofarull, A., Gidraf Kahindo Maina, A., Valentijn, T., Harlass, S., ... Luengo-Oroz, M. (2022). Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward. BMJ Global Health, 7(3), [e007822]. https://doi.org/10.1136/bmjgh-2021-007822

Vancouver

Author

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. / Epidemiological modelling in refugee and internally displaced people settlements : challenges and ways forward. In: BMJ Global Health. 2022 ; Vol. 7, No. 3.

Bibtex

@article{94f60f8cafb943c2bc732dd9c3593ca0,
title = "Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward",
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.",
keywords = "COVID-19, Communicable Diseases/epidemiology, Humans, Pandemics, Refugees, SARS-CoV-2",
author = "Joseph Aylett-Bullock and Gilman, {Robert Tucker} and Ian Hall and David Kennedy and Evers, {Egmond Samir} and Anjali Katta and Hussien Ahmed and Kevin Fong and Keyrellous Adib and {Al Ariqi}, Lubna and Ali Ardalan and Pierre Nabeth and {von Harbou}, Kai and {Hoffmann Pham}, Katherine and Carolina Cuesta-Lazaro and Arnau Quera-Bofarull and {Gidraf Kahindo Maina}, Allen and Tinka Valentijn and Sandra Harlass and Frank Krauss and Chao Huang and {Moreno Jimenez}, Rebeca and Tina Comes and Mariken Gaanderse and Leonardo Milano and Miguel Luengo-Oroz",
note = "Funding Information: 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. Publisher Copyright: {\textcopyright} 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.",
year = "2022",
month = mar,
day = "9",
doi = "10.1136/bmjgh-2021-007822",
language = "English",
volume = "7",
journal = "BMJ Global Health",
issn = "2059-7908",
publisher = "BMJ ",
number = "3",

}

RIS

TY - JOUR

T1 - Epidemiological modelling in refugee and internally displaced people settlements

T2 - challenges and ways forward

AU - Aylett-Bullock, Joseph

AU - Gilman, Robert Tucker

AU - Hall, Ian

AU - Kennedy, David

AU - Evers, Egmond Samir

AU - Katta, Anjali

AU - Ahmed, Hussien

AU - Fong, Kevin

AU - Adib, Keyrellous

AU - Al Ariqi, Lubna

AU - Ardalan, Ali

AU - Nabeth, Pierre

AU - von Harbou, Kai

AU - Hoffmann Pham, Katherine

AU - Cuesta-Lazaro, Carolina

AU - Quera-Bofarull, Arnau

AU - Gidraf Kahindo Maina, Allen

AU - Valentijn, Tinka

AU - Harlass, Sandra

AU - Krauss, Frank

AU - Huang, Chao

AU - Moreno Jimenez, Rebeca

AU - Comes, Tina

AU - Gaanderse, Mariken

AU - Milano, Leonardo

AU - Luengo-Oroz, Miguel

N1 - Funding Information: 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. Publisher Copyright: © 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.

PY - 2022/3/9

Y1 - 2022/3/9

N2 - 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.

AB - 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.

KW - COVID-19

KW - Communicable Diseases/epidemiology

KW - Humans

KW - Pandemics

KW - Refugees

KW - SARS-CoV-2

U2 - 10.1136/bmjgh-2021-007822

DO - 10.1136/bmjgh-2021-007822

M3 - Article

C2 - 35264317

VL - 7

JO - BMJ Global Health

JF - BMJ Global Health

SN - 2059-7908

IS - 3

M1 - e007822

ER -