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Operational response simulation tool for epidemics within refugee and IDP settlements: A scenario-based case study of the Cox's Bazar settlement.

Autor: Aylett-Bullock J; United Nations Global Pulse, New York, New York, United States of America.; Institute for Data Science, Durham University, Durham, United Kingdom., Cuesta-Lazaro C; Institute for Data Science, Durham University, Durham, United Kingdom., Quera-Bofarull A; Institute for Data Science, Durham University, Durham, United Kingdom., Katta A; United Nations Global Pulse, New York, New York, United States of America., Hoffmann Pham K; United Nations Global Pulse, New York, New York, United States of America.; New York University Stern School of Business, New York, New York, United States of America., Hoover B; MIT-IBM Watson AI Lab, Cambridge, Massachusetts, United States of America., Strobelt H; MIT-IBM Watson AI Lab, Cambridge, Massachusetts, United States of America., Moreno Jimenez R; UNHCR Innovation, Geneva, Switzerland., Sedgewick A; Institute for Data Science, Durham University, Durham, United Kingdom., Samir Evers E; WHO Emergency Sub-Office, Cox's Bazar, Bangladesh., Kennedy D; UK Public Health Rapid Support Team, Public Health England/London School of Hygiene and Tropical Medicine, London, United Kingdom., Harlass S; UNHCR Public Health Unit, Geneva, Switzerland., Gidraf Kahindo Maina A; UNHCR Public Health Unit, Cox's Bazar, Bangladesh., Hussien A; UNHCR Information Management Unit, Cox's Bazar, Bangladesh., Luengo-Oroz M; United Nations Global Pulse, New York, New York, United States of America.

Publikováno v: PLoS computational biology [PLoS Comput Biol] 2021 Oct 28; Vol. 17 (10), pp. e1009360. Date of Electronic Publication: 2021 Oct 28 (Print Publication: 2021).