Uygun-Can Banu, Durmazpınar Parla Meva, Hatipoğlu Şirin, Acar-Bolat Bilge, Özen Çağla, Sazak-Öveçoğlu Hesna, Kadir Tanju
Department of Microbiology, Dental Faculty, Marmara University, Istanbul, Turkey.
Department of Endodontics, Dental Faculty, Marmara University, Istanbul, Turkey.
J Multidiscip Healthc. 2025 Mar 4;18:1319-1334. doi: 10.2147/JMDH.S499841. eCollection 2025.
This study focused on the risk posed by pre-symptomatic and asymptomatic carriers in dental clinics during the period (February-June 2022) when Covid-19 transmission was highest and aimed to investigate the effectiveness of infection control protocols in the prevention of SARS-CoV-2 transmission. It also evaluated the potential of wearable sensors as part of the Internet of Things (IoT) to prevent cross-infection.
Swab samples were collected from surfaces and air filters in dental clinics and analyzed using RT-PCR both before and after disinfection processes. Clinicians also used IoT-enabled wearable sensors and completed surveys (n=100) evaluating the impact of these technologies on infection control practices. The sensors monitored clinicians' movements and patient interactions to assess cross-infection risks.
All RT-PCR tests returned negative results, indicating that no SARS-CoV-2 was detected on the sampled surfaces or air filters. Surveys revealed that 70% of resident clinicians trusted the effectiveness of wearable sensors in infection control. The technology was particularly well received among younger clinicians and was found to be effective in strengthening contact tracing, control measures, and awareness.
Strict infection control measures have contributed to preventing Covid-19 infections in dental clinics, although asymptomatic cases may still be present. These findings highlight the importance of adopting advanced technologies such as wearable sensors to support current infection control measures. With further studies, the scalability and integration of IoT technologies into routine infection control practices in diverse healthcare settings can be better understood, enhancing infection control potential and significantly contributing to the safety of healthcare workers and patients.
本研究聚焦于2022年2月至6月新冠病毒传播率最高期间牙科诊所中症状前携带者和无症状携带者所带来的风险，旨在调查感染控制方案在预防新冠病毒传播方面的有效性。研究还评估了可穿戴传感器作为物联网一部分在预防交叉感染方面的潜力。
在牙科诊所的表面和空气过滤器上采集拭子样本，在消毒前后均使用逆转录聚合酶链反应（RT-PCR）进行分析。临床医生还使用了支持物联网的可穿戴传感器，并完成了调查（n = 100），评估这些技术对感染控制措施的影响。这些传感器监测临床医生的活动和与患者的互动，以评估交叉感染风险。
所有RT-PCR检测结果均为阴性，表明在采样的表面或空气过滤器上未检测到新冠病毒。调查显示，70%的住院临床医生相信可穿戴传感器在感染控制方面的有效性。该技术在年轻临床医生中尤其受到欢迎，并且被发现有助于加强接触者追踪、控制措施和意识。
严格的感染控制措施有助于预防牙科诊所中的新冠病毒感染，尽管可能仍有无症状病例存在。这些发现凸显了采用可穿戴传感器等先进技术以支持当前感染控制措施的重要性。通过进一步研究，可以更好地理解物联网技术在不同医疗环境中常规感染控制实践中的可扩展性和整合性，增强感染控制潜力，并显著提高医护人员和患者的安全性。
