温度和隔离对印度COVID-19的影响：一种数学建模方法
The Impact of Temperature and Isolation on COVID-19 in India: A Mathematical Modelling approach
AI总结：
本研究通过延迟微分方程模型，分析温度与隔离延迟对印度COVID-19传播的影响，发现温度降低和隔离延迟增加均会提高平均感染人数，预测冬季感染上升。
摘要：
通过将恒定人口划分为六个隔室，使用一组延迟微分方程捕捉印度COVID-19的动态。计算了平衡点并进行了稳定性分析。对模型参数进行了敏感性分析。进行了分岔分析并计算了临界延迟。通过将传播参数表述为温度的函数，研究了温度对人口的影响。我们得出结论，随着温度降低，人口中的平均感染人数增加。鉴于印度即将到来的冬季，新感染人数将会增加。该模型符合隔离延迟增加导致人口平均感染人数增加的特征。
英文摘要：
The dynamics of COVID-19 in India are captured using a set of delay differential equations by dividing a constant population into six compartments. The equilibrium points are calculated and stability analysis is performed. Sensitivity analysis is performed on the parameters of the model. Bifurcation analysis is performed and the critical delay is calculated. By formulating the spread parameter as a function of temperature, the impact of temperature on the population is studied. We concluded that with the decrease in temperature, the average infections in the population increases. In view of the coming winter season in India, there will be an increase in new infections. This model falls in line with the characteristics that increase in isolation delay increases average infections in the population.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
