A SIQRS epidemic model incorporating psychological factors for COVID-19

Since the initiation of the highest-level public health emergency response in Jilin Province, China, on January 25, 2020, awareness of COVID-19 has remained high. However, in March 2022, an outbreak of COVID-19, attributed to imported cases, occurred in Changchun, China. Considering the psychological impact of COVID-19 on humans, we developed a SIQRS epidemic model. Dynamic analyses were conducted on both deterministic and corresponding stochastic models. By employing non-linear least squares to fit COVID-19 data, we analyzed the influence of psychological factors on the disease?s spread. Our aim was to explore effective prevention and control measures for COVID-19, taking into account the psychological dimension of the pandemic.

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Publication Details

Journal
Thermal Science
Published
2025-01-01
DOI
https://doi.org/10.2298/tsci2502077l
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00
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article

A SIQRS epidemic model incorporating psychological factors for COVID-19

Huilai Li, Wenda Xu, Wenxuan Li, Xu Chen
Thermal Science
COVID-19 epidemiological studies
article

A SIQRS epidemic model incorporating psychological factors for COVID-19

Huilai Li, Wenda Xu, Wenxuan Li, Xu Chen
article en

Abstract

Since the initiation of the highest-level public health emergency response in Jilin Province, China, on January 25, 2020, awareness of COVID-19 has remained high. However, in March 2022, an outbreak of COVID-19, attributed to imported cases, occurred in Changchun, China. Considering the psychological impact of COVID-19 on humans, we developed a SIQRS epidemic model. Dynamic analyses were conducted on both deterministic and corresponding stochastic models. By employing non-linear least squares to fit COVID-19 data, we analyzed the influence of psychological factors on the disease?s spread. Our aim was to explore effective prevention and control measures for COVID-19, taking into account the psychological dimension of the pandemic.

Thermal ScienceVol. 29(2 Part A)
Jilin University (CN)
Openalex Percentile: Top 91%
COVID-19 epidemiological studies
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