Journal article
Analysis of intervention effectiveness using early outbreak transmission dynamics to guide future pandemic management and decision-making in Kuwait
Infectious disease modelling, Vol.6, pp.693-705
01 Jan 2021
PMID: 33898885
Featured in Collection : UN Sustainable Development Goals @ Drexel
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.
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Details
- Title
- Analysis of intervention effectiveness using early outbreak transmission dynamics to guide future pandemic management and decision-making in Kuwait
- Creators
- Michael G. Tyshenko - University of OttawaTamer Oraby - The University of Texas Rio Grande ValleyJoseph Longenecker - Faculty of Public HealthHarri Vainio - Kuwait UniversityJanvier Gasana - Kuwait UniversityWalid Q. Alali - Kuwait UniversityMohammad AlSeaidan - Ministry of HealthSusie ElSaadany - University of OttawaMustafa Al-Zoughool - Kuwait University
- Publication Details
- Infectious disease modelling, Vol.6, pp.693-705
- Publisher
- Elsevier B.V
- Number of pages
- 13
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics
- Web of Science ID
- WOS:000649740500002
- Scopus ID
- 2-s2.0-85104676759
- Other Identifier
- 991022051417404721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Infectious Diseases
- Mathematical & Computational Biology