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Analysis of intervention effectiveness using early outbreak transmission dynamics to guide future pandemic management and decision-making in Kuwait.

Authors :
Tyshenko MG
Oraby T
Longenecker J
Vainio H
Gasana J
Alali WQ
AlSeaidan M
ElSaadany S
Al-Zoughool M
Source :
Infectious Disease Modelling [Infect Dis Model] 2021; Vol. 6, pp. 693-705. Date of Electronic Publication: 2021 Apr 19.
Publication Year :
2021

Abstract

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a World Health Organization designated pandemic that can result in severe symptoms and death that disproportionately affects older patients or those with comorbidities. Kuwait reported its first imported cases of COVID-19 on February 24, 2020. Analysis of data from the first three months of community transmission of the COVID-19 outbreak in Kuwait can provide important guidance for decision-making when dealing with future SARS-CoV-2 epidemic wave management. The analysis of intervention scenarios can help to evaluate the possible impacts of various outbreak control measures going forward which aim to reduce the effective reproduction number during the initial outbreak wave. Herein we use a modified susceptible-exposed-asymptomatic-infectious-removed (SEAIR) transmission model to estimate the outbreak dynamics of SARS-CoV-2 transmission in Kuwait. We fit case data from the first 96 days in the model to estimate the effective reproduction number and used Google mobility data to refine community contact matrices. The SEAIR modelled scenarios allow for the analysis of various interventions to determine their effectiveness. The model can help inform future pandemic wave management, not only in Kuwait but for other countries as well.<br />Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (© 2021 The Authors.)

Details

Language :
English
ISSN :
2468-0427
Volume :
6
Database :
MEDLINE
Journal :
Infectious Disease Modelling
Publication Type :
Academic Journal
Accession number :
33898885
Full Text :
https://doi.org/10.1016/j.idm.2021.04.003