Xie Yaping, Zong Zisheng, Jiang Qin, Ke Xingxing, Wu Zhigang
State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Sansure Biotech Inc., Changsha 410205, China.
Micromachines (Basel). 2025 Apr 15;16(4):472. doi: 10.3390/mi16040472.
Frequent outbreaks of respiratory infectious diseases, driven by diverse pathogens, have long posed significant threats to public health, economic productivity, and societal stability. Respiratory infectious diseases are highly contagious, characterized by short incubation periods, diverse symptoms, multiple transmission routes, susceptibility to mutations, and distinct seasonality, contributing to their propensity for outbreaks. The absence of effective antiviral treatments and the heightened vulnerability of individuals with weakened immune systems make them more susceptible to infection, with severe cases potentially leading to complications or death. This situation becomes particularly concerning during peak seasons, such as influenza outbreaks. Therefore, early detection, diagnosis, and treatment are critical, alongside the prevention of cross-infection, ensuring patient safety, and controlling healthcare costs. To address these challenges, this review aims to identify a comprehensive, rapid, safe, and cost-effective diagnostic approach for respiratory infectious diseases. This approach is framed within the existing hierarchical healthcare system, focusing on establishing diagnostic capabilities at hospitals, community, and home levels to effectively tackle the above issues. In addition to PCR and isothermal amplification, the review also explores emerging molecular diagnostic strategies that may better address the evolving needs of respiratory disease diagnostics. A key focus is the transition from amplification technologies to amplification-free biosensing approaches, with particular attention given to their potential for home-based testing. This shift seeks to overcome the limitations of conventional amplification methods, particularly in decentralized and home diagnostics, offering a promising solution to enhance diagnostic speed and safety during outbreaks. In the future, with the integration of AI technologies into molecular amplification technologies, biosensors, and various application levels, the inclusively economic, rapid, and safe respiratory disease diagnosis solutions will be further optimized, and their accessibility will become more widespread.
由多种病原体驱动的呼吸道传染病频繁爆发，长期以来对公众健康、经济生产力和社会稳定构成了重大威胁。呼吸道传染病具有高度传染性，其特点是潜伏期短、症状多样、传播途径多、易发生变异且季节性明显，这些因素导致了它们易于爆发。缺乏有效的抗病毒治疗方法以及免疫系统较弱的个体易感性增加，使得他们更容易感染，严重病例可能导致并发症或死亡。在流感爆发等高峰期，这种情况尤为令人担忧。因此，早期检测、诊断和治疗至关重要，同时还要预防交叉感染、确保患者安全并控制医疗成本。为应对这些挑战，本综述旨在确定一种全面、快速、安全且具有成本效益的呼吸道传染病诊断方法。这种方法在现有的分级医疗体系框架内制定，重点是在医院、社区和家庭层面建立诊断能力，以有效解决上述问题。除了聚合酶链反应（PCR）和等温扩增技术外，本综述还探讨了新兴的分子诊断策略，这些策略可能更好地满足呼吸道疾病诊断不断变化的需求。一个关键重点是从扩增技术向无扩增生物传感方法的转变，尤其关注它们用于家庭检测的潜力。这种转变旨在克服传统扩增方法的局限性，特别是在分散式和家庭诊断中的局限性，为在疫情爆发期间提高诊断速度和安全性提供了一个有前景的解决方案。未来，随着人工智能技术融入分子扩增技术、生物传感器以及各个应用层面，经济、快速且安全的呼吸道疾病诊断综合解决方案将得到进一步优化，其可及性也将更加广泛。
