Detection of Coronavirus Disease 2019 (COVID-19) Virus on the Surface of Hospital Settings by Quantitative Real-Time Polymerase Chain Reaction

Background & Objectives: Coronavirus disease 2019 (COVID-19) has had a profound impact on human health, with over 704,753,890 confirmed cases and 7,010,681 deaths reported to date. This study aimed to evaluate the contamination rate of COVID-19 on high-risk surfaces at Valiasr Hospital in Fasa, Iran, using molecular testing. Materials & Methods: A total of 142 surface swabs, immersed in viral transport medium (VTM), were collected and transported to the Virology Reference Laboratory at the Cohort Center of Fasa University of Medical Sciences for COVID-19 virus testing. The presence of the virus was assessed using the real-time polymerase chain reaction (RT- qPCR) technique (QIAquant 96 5plex), following the manufacturer’s protocol (Qiagen, MD, USA). Results: Among the 142 samples obtained from surfaces and equipment in the COVID-19 ward, two samples tested positive for COVID-19. Similarly, two samples from the coronavirus isolation ward were found to be positive using RT-qPCR. The positive samples were collected from a patient’s bed and the interior bed of an insulated room. No COVID-19 contamination was detected on hospital surface samples outside these areas. Conclusion: This study identified a low rate of COVID-19 contamination on hospital surfaces and equipment in Fasa city. The findings suggest that the hospital environment could serve as a potential source of COVID-19 transmission, particularly among healthcare providers, visitors, and patients.

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Publication Details

Journal
Journal of Advanced Biomedical Sciences
Published
2024-10-14
DOI
https://doi.org/10.18502/jabs.v14i4.16691
Primary Topic
SARS-CoV-2 detection and testing
Type
article
Field-Weighted Citation Impact
0.00

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article

Detection of Coronavirus Disease 2019 (COVID-19) Virus on the Surface of Hospital Settings by Quantitative Real-Time Polymerase Chain Reaction

Abdolazim Alinejad, Abdolmajid Ghasemian, Ali Ghanbariasad, Ramin Hayati et al.
Journal of Advanced Biomedical Sciences
SARS-CoV-2 detection and testing
article

Detection of Coronavirus Disease 2019 (COVID-19) Virus on the Surface of Hospital Settings by Quantitative Real-Time Polymerase Chain Reaction

Abdolazim Alinejad, Abdolmajid Ghasemian, Ali Ghanbariasad, Ramin Hayati, Yaser Mansoori, Zahra Montaseri, Mohammad Doustan
article en

Abstract

Background & Objectives: Coronavirus disease 2019 (COVID-19) has had a profound impact on human health, with over 704,753,890 confirmed cases and 7,010,681 deaths reported to date. This study aimed to evaluate the contamination rate of COVID-19 on high-risk surfaces at Valiasr Hospital in Fasa, Iran, using molecular testing. Materials & Methods: A total of 142 surface swabs, immersed in viral transport medium (VTM), were collected and transported to the Virology Reference Laboratory at the Cohort Center of Fasa University of Medical Sciences for COVID-19 virus testing. The presence of the virus was assessed using the real-time polymerase chain reaction (RT- qPCR) technique (QIAquant 96 5plex), following the manufacturer’s protocol (Qiagen, MD, USA). Results: Among the 142 samples obtained from surfaces and equipment in the COVID-19 ward, two samples tested positive for COVID-19. Similarly, two samples from the coronavirus isolation ward were found to be positive using RT-qPCR. The positive samples were collected from a patient’s bed and the interior bed of an insulated room. No COVID-19 contamination was detected on hospital surface samples outside these areas. Conclusion: This study identified a low rate of COVID-19 contamination on hospital surfaces and equipment in Fasa city. The findings suggest that the hospital environment could serve as a potential source of COVID-19 transmission, particularly among healthcare providers, visitors, and patients.

Journal of Advanced Biomedical Sciences
Fasa University of Medical Sciences (IR)
Fasa University of Medical Sciences
Good health and well-being
Openalex Percentile: Top 70%
SARS-CoV-2 detection and testing
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