In this paper, an optimal control model for the transmission dynamics of COVID-19 is investigated. We established important model properties like nonnegativity and boundedness of solutions, and also the region of invariance. Further, an expression for the basic reproduction number is computed and its sensitivity w.r.t model parameters is carried out to identify the most sensitive parameter. Based on sensitivity analysis, optimal control strategies were presented to reduce the disease burden and related costs. It is demonstrated that optimal control does exist and is unique. The characterization of optimal trajectories is analytically studied via Pontryagin's Minimum Principle. Moreover, various simulations were performed to support analytical results. The simulation results showed that the proposed controls significantly influence the disease burden compared to the absence of control cases. Further, it reveals that the applied control strategies are effective throughout the intervention period in reducing COVID-19 diseases in the community. Besides, the simulation results of the optimal control suggested that concurrently applying all controlling strategies outperform in mitigating the spread of COVID-19 compared to any other preventive measures.

在本文中，研究了 COVID-19 传输动力学的最优控制模型。我们建立了重要的模型属性，例如解的非负性和有界性，以及不变性区域。此外，计算基本再现数的表达式，并执行其对模型参数的敏感性，以识别最敏感的参数。基于敏感性分析，提出了最佳控制策略以减少疾病负担和相关成本。证明了最优控制确实存在并且是唯一的。通过 Pontryagin 的最小原则分析研究了最佳轨迹的特征。此外，还进行了各种模拟以支持分析结果。模拟结果表明，与没有对照病例相比，所提出的对照显着影响疾病负担。此外，它还表明，在整个干预期间，所应用的控制策略在减少社区 COVID-19 疾病方面是有效的。此外，最优控制的模拟结果表明，与任何其他预防措施相比，同时应用所有控制策略在减轻 COVID-19 传播方面的效果更好。