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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.
Aylett-Bullock, Joseph; Cuesta-Lazaro, Carolina; Quera-Bofarull, Arnau; Katta, Anjali; Hoffmann Pham, Katherine; Hoover, Benjamin; Strobelt, Hendrik; Moreno Jimenez, Rebeca; Sedgewick, Aidan; Samir Evers, Egmond; Kennedy, David; Harlass, Sandra; Gidraf Kahindo Maina, Allen; Hussien, Ahmad; Luengo-Oroz, Miguel.
  • Aylett-Bullock J; United Nations Global Pulse, New York, New York, United States of America.
  • 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; Institute for Data Science, Durham University, Durham, United Kingdom.
  • Hoffmann Pham K; United Nations Global Pulse, New York, New York, United States of America.
  • Hoover B; United Nations Global Pulse, New York, New York, United States of America.
  • Strobelt H; New York University Stern School of Business, New York, New York, United States of America.
  • Moreno Jimenez R; MIT-IBM Watson AI Lab, Cambridge, Massachusetts, United States of America.
  • Sedgewick A; MIT-IBM Watson AI Lab, Cambridge, Massachusetts, United States of America.
  • Samir Evers E; UNHCR Innovation, Geneva, Switzerland.
  • Kennedy D; Institute for Data Science, Durham University, Durham, United Kingdom.
  • Harlass S; WHO Emergency Sub-Office, Cox's Bazar, Bangladesh.
  • Gidraf Kahindo Maina A; UK Public Health Rapid Support Team, Public Health England/London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Hussien A; UNHCR Public Health Unit, Geneva, Switzerland.
  • Luengo-Oroz M; UNHCR Public Health Unit, Cox's Bazar, Bangladesh.
PLoS Comput Biol ; 17(10): e1009360, 2021 10.
Article in English | MEDLINE | ID: covidwho-1496326
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 most affected. Given their density and available infrastructure, refugee and internally displaced person (IDP) settlements can be particularly susceptible to disease spread. In this paper we present an agent-based modeling approach to simulating the spread of disease in refugee and IDP settlements under various non-pharmaceutical intervention strategies. The model, based on the June open-source framework, is informed by data on geography, demographics, comorbidities, physical infrastructure and other parameters obtained from real-world observations and previous literature. The development and testing of this approach focuses on the Cox's Bazar refugee settlement in Bangladesh, although our model is designed to be generalizable to other informal settings. Our findings suggest the encouraging self-isolation at home of mild to severe symptomatic patients, as opposed to the isolation of all positive cases in purpose-built isolation and treatment centers, does not increase the risk of secondary infection meaning the centers can be used to provide hospital support to the most intense cases of COVID-19. Secondly we find that mask wearing in all indoor communal areas can be effective at dampening viral spread, even with low mask efficacy and compliance rates. Finally, we model the effects of reopening learning centers in the settlement under various mitigation strategies. For example, a combination of mask wearing in the classroom, halving attendance regularity to enable physical distancing, and better ventilation can almost completely mitigate the increased risk of infection which keeping the learning centers open may cause. These modeling efforts are being incorporated into decision making processes to inform future planning, and further exercises should be carried out in similar geographies to help protect those most vulnerable.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Refugees / Epidemics / SARS-CoV-2 / COVID-19 Type of study: Case report / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article Affiliation country: Journal.pcbi.1009360

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Refugees / Epidemics / SARS-CoV-2 / COVID-19 Type of study: Case report / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article Affiliation country: Journal.pcbi.1009360