助推器(火箭)
随机性
2019年冠状病毒病(COVID-19)
心理干预
传输(电信)
爆发
医学
接种疫苗
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
计量经济学
环境卫生
计算机科学
统计
疾病
数学
病毒学
传染病(医学专业)
精神科
病理
物理
电信
天文
作者
Yi Tan,Pei Yuan,Iain R. Moyles,Jane M. Heffernan,James Watmough,Sanyi Tang,Huaiping Zhu
标识
DOI:10.3934/dcdss.2023044
摘要
Facing the more contagious COVID-19 variant, Omicron, nonpharmaceutical interventions (NPIs) were still in place and booster doses were proposed to mitigate the epidemic. However, the uncertainty and stochasticity in individuals' behaviours toward the NPIs and booster dose increase, and how this randomness affects the transmission remains poorly understood. We present a model framework to incorporate demographic stochasticity and two kinds of environmental stochasticity (notably variations in adherence to NPIs and booster dose acceptance) to analyze the effects of different forms of stochasticity on transmission. The model is calibrated using the data from December 31, 2021, to March 8, 2022, on daily reported cases and hospitalizations, cumulative cases, deaths and vaccinations for booster doses in Toronto, Canada. An approximate Bayesian computational (ABC) method is used for calibration. We observe that demographic stochasticity could dramatically worsen the outbreak with more incidence compared with the results of the corresponding deterministic model. We found that large variations in adherence to NPIs increase infections. The randomness in booster dose acceptance will not affect the number of reported cases significantly and it is acceptable in the mitigation of COVID-19. The stochasticity in adherence to NPIs needs more attention compared to booster dose hesitancy.
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