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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.
Afiliación
  • Aylett-Bullock J; UN Global Pulse, United Nations, New York, New York, USA joseph@unglobalpulse.org.
  • Gilman RT; Institute for Data Science, Durham University, Durham, UK.
  • Hall I; Centre for Crisis Studies and Mitigation, The University of Manchester, Manchester, UK.
  • Kennedy D; Department of Earth and Environmental Sciences, The University of Manchester, Manchester, UK.
  • Evers ES; Centre for Crisis Studies and Mitigation, The University of Manchester, Manchester, UK.
  • Katta A; Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK.
  • Ahmed H; Department of Mathematics, The University of Manchester, Manchester, UK.
  • Fong K; UK Public Health Rapid Support Team, London School of Hygiene & Tropical Medicine/Public Health England, London, UK.
  • Adib K; WHO Cox's Bazar Emergency Sub-Office, United Nations, Cox's Bazar, Bangladesh.
  • Al Ariqi L; UN Global Pulse, United Nations, New York, New York, USA.
  • Ardalan A; UNHCR Cox's Bazar Sub-Office, United Nations, Cox's Bazar, Bangladesh.
  • Nabeth P; Department of Science, Technology, Engineering and Public Policy, University College London, London, UK.
  • von Harbou K; WHO Eastern Mediterranean Regional Office, United Nations, Cairo, Egypt.
  • Hoffmann Pham K; WHO Eastern Mediterranean Regional Office, United Nations, Cairo, Egypt.
  • Cuesta-Lazaro C; WHO Eastern Mediterranean Regional Office, United Nations, Cairo, Egypt.
  • Quera-Bofarull A; WHO Eastern Mediterranean Regional Office, United Nations, Cairo, Egypt.
  • Gidraf Kahindo Maina A; WHO Cox's Bazar Emergency Sub-Office, United Nations, Cox's Bazar, Bangladesh.
  • Valentijn T; UN Global Pulse, United Nations, New York, New York, USA.
  • Harlass S; Stern School of Business, New York University, New York City, New York, USA.
  • Krauss F; Institute for Data Science, Durham University, Durham, UK.
  • Huang C; Institute for Data Science, Durham University, Durham, UK.
  • Moreno Jimenez R; UNHCR Public Health Unit, United Nations, Cox's Bazar, Bangladesh.
  • Comes T; OCHA Centre for Humanitarian Data, United Nations, The Hague, The Netherlands.
  • Gaanderse M; UNHCR Public Health Unit, United Nations, Geneva, Switzerland.
  • Milano L; Institute for Data Science, Durham University, Durham, UK.
  • Luengo-Oroz M; UNHCR Global Data Service, United Nations, Copenhagen, New York, USA.
BMJ Glob Health ; 7(3)2022 03.
Article en En | MEDLINE | ID: mdl-35264317
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Refugiados / Enfermedades Transmisibles / COVID-19 Tipo de estudio: Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Revista: BMJ Glob Health Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Refugiados / Enfermedades Transmisibles / COVID-19 Tipo de estudio: Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Revista: BMJ Glob Health Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido