Loo, P. S. and Aguiar, A. C. C. and Kopainsky, B.. (2023) Simulation-based assessment of cholera epidemic response: a case study of Al-Hudaydah, Yemen. Systems, 11. p. 3.
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Abstract
Cholera kills between 21,000 and 143,000 people globally each year. It is often fatal, killing up to 50% of the severely symptomatic patients; but death by cholera is preventable with timely treatment, so that the fatality rate can drop to less than 1%. Due to cholera's multi-pathway transmission, a multifaceted and multi-sectoral approach to combat this disease is needed. Such complexity gives rise to uncertainty about where it is best to intervene, as stakeholders have to balance prevention and treatment under highly constrained resources. Using Al-Hudaydah, Yemen as a case study, this paper demonstrates how a system dynamics model can be built using a classic infection structure with empirically grounded operational structures: health treatment, water, sanitation, and hygiene (WASH), vaccination, and a data surveillance system. The model explores the implications of the joint interventions with different start times. The model analysis revealed that the historical interventions likely prevented 55% more deaths in 2017 as compared to a counterfactual business-as-usual scenario with no interventions in the past. At the same time, some 40% of deaths could potentially have been prevented if interventions (with the same resources as historical data) had been initiated earlier in April 2017. Further research will explore each intervention impact for more detailed policy analysis and simulations into the future. © 2022 by the authors.
Faculties and Departments: | 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Household Economics and Health Systems Research > Health Systems and Policy (Tediosi) |
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UniBasel Contributors: | Loo, Pei Shan |
Item Type: | Article, refereed |
Article Subtype: | Research Article |
ISBN: | 20798954 |
Note: | Publication type according to Uni Basel Research Database: Journal article |
Language: | English |
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Identification Number: | |
edoc DOI: | |
Last Modified: | 13 Feb 2023 08:57 |
Deposited On: | 13 Feb 2023 08:57 |
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