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J Multidiscip Healthc
Department of Microbiology, Dental Faculty, Marmara University, Istanbul, Turkey.
Published: March 2025
Background: 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.
Material And Methods: 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.
Results: 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.
Conclusion: 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.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11889996 | PMC |
http://dx.doi.org/10.2147/JMDH.S499841 | DOI Listing |
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