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

Michael G. Tyshenko, Tamer Oraby, Joseph Longenecker, Harri Vainio, Janvier Gasana, Walid Q. Alali, Mohammad AlSeaidan, Susie ElSaadany, Mustafa Al-Zoughool

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)693-705
Number of pages13
JournalInfectious Disease Modelling
Volume6
DOIs
StatePublished - Jan 2021
Externally publishedYes

Keywords

  • COVID-19
  • Effective reproduction number
  • Kuwait
  • Lockdown
  • Non-pharmaceutical interventions
  • SEAIR deterministic Model

ASJC Scopus subject areas

  • Health Policy
  • Infectious Diseases
  • Applied Mathematics

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