Literature DB >> 35035089

Analysis of non-pharmaceutical interventions impacts on COVID-19 pandemic in Iran.

Sara Saadatmand1, Khodakaram Salimifard1, Reza Mohammadi2.   

Abstract

The COVID-19 pandemic shows to have a huge impact on people's health and countries' infrastructures around the globe. Iran was one of the first countries that experienced the vast prevalence of the coronavirus outbreak. The Iranian authorities applied various non-pharmaceutical interventions to eradicate the epidemic in different periods. This study aims to investigate the effectiveness of non-pharmaceutical interventions in managing the current Coronavirus pandemic and to predict the next wave of infection in Iran. To achieve the research objective, the number of cases and deaths before and after the interventions was studied and the effective reproduction number of the infection was analyzed under various scenarios. The SEIR generic model was applied to capture the dynamic of the pandemic in Iran. To capture the effects of different interventions, the corresponding reproduction number was considered. Depending on how people are responsive to interventions, the effectiveness of each intervention has been investigated. Results show that the maximum number of the total of infected individuals will occur around the end of May and the start of June 2021. It is concluded that the outbreak could be smoothed if full lockdown and strict quarantine continue. The proposed modeling could be used as an assessment tool to evaluate the effects of different interventions in new outbreaks.
© The Author(s), under exclusive licence to Springer Nature B.V. 2021.

Entities:  

Keywords:  COVID-19; Non-pharmaceutical interventions; Nonlinear dynamics; Pandemic modeling; SEIR model

Year:  2022        PMID: 35035089      PMCID: PMC8747878          DOI: 10.1007/s11071-021-07121-8

Source DB:  PubMed          Journal:  Nonlinear Dyn        ISSN: 0924-090X            Impact factor:   5.022


  1 in total

1.  Preface to the special issue "Complex dynamics of COVID-19: modeling, prediction and control (part II)".

Authors:  Walter Lacarbonara; Jun Ma; C Nataraj
Journal:  Nonlinear Dyn       Date:  2022-06-09       Impact factor: 5.741

  1 in total

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