Department of Mathematics, Trent University, Peterborough, ON K9L 0G2, Canada.
Math Biosci Eng. 2020 Oct 28;17(6):7428-7441. doi: 10.3934/mbe.2020380.
Since the initial identification of a COVID-19 case in Wuhan, China, the novel disease quickly becomes a global pandemic emergency. In this paper, we propose a dynamic model that incorporates individuals' behavior change in social interactions at different stages of the epidemics. We fit our model to the data in Ontario, Canada and calculate the effective reproduction number $\mathcal{R}_t$ within each stage. Results show that $\mathcal{R}_t$ > 1 if the public's awareness to practice physical distancing is rela-tively low and $\mathcal{R}_t$ < 1 otherwise. Simulations show that a reduced contact rate between the susceptible and asymptomatic/unreported symptomatic individuals is effective in mitigating the disease spread. Moreover, sensitivity analysis indicates that an increasing contact rate may lead to a second wave of disease outbreak. We also investigate the effectiveness of disease intervention strategies. Simulations demonstrate that enlarging the testing capacity and motivating infected individuals to test for an early diagnosis may facilitate mitigating the disease spread in a relatively short time. Results also indicate a significantly faster decline of confirmed positive cases if individuals practice strict physical distancing even if restricted measures are lifted.
自中国武汉首次发现 COVID-19 病例以来，该新型疾病迅速成为全球紧急公共卫生事件。在本文中，我们提出了一个动态模型，该模型将个体在疾病不同阶段的社会互动中的行为变化纳入其中。我们将模型拟合到加拿大安大略省的数据，并计算了每个阶段的有效繁殖数 $\mathcal{R}_t$。结果表明，如果公众对保持身体距离的意识相对较低，则 $\mathcal{R}_t$ > 1，否则 $\mathcal{R}_t$ < 1。模拟结果表明，减少易感人群与无症状/未报告症状人群之间的接触率可有效减轻疾病传播。此外，敏感性分析表明，接触率的增加可能导致疾病的第二次爆发。我们还研究了疾病干预策略的有效性。模拟结果表明，扩大检测能力并激励感染个体进行早期诊断，可能有助于在相对较短的时间内减轻疾病的传播。结果还表明，如果个人严格保持身体距离，即使放宽限制措施，确诊阳性病例的数量也会明显更快地下降。
