Decoding post-mortem infection dynamics of SARS-CoV-2, IAV and RSV: New insights for public health and emerging infectious diseases management
This study presents the first comprehensive analysis of viral persistence in cadavers, revealing prolonged SARS-CoV-2 stability compared to IAV and RSV. These findings underscore the need for enhanced post-mortem biosafety protocols to mitigate occupational exposure risks in forensic and clinical settings. By elucidating viral decay dynamics across environmental conditions, this research establishes a critical foundation for infection control strategies, informing biosafety policies for emerging respiratory pathogens.
Authors
- Yi Qin (ORCID: https://orcid.org/0000-0001-6621-4165)
- Yuzhao Liu
- Xinggong Liang
- Ruina Liu (ORCID: https://orcid.org/0000-0002-6834-8922)
- Xingchun Zhao
- Gengwang Hu
- Zeyi Hao
- Sheng Hu (ORCID: https://orcid.org/0000-0002-8632-3171)
- Qinru Sun (ORCID: https://orcid.org/0000-0001-6203-8539)
- Zhenyuan Wang (ORCID: https://orcid.org/0000-0003-3561-6414)
- Jianjun Luo (ORCID: https://orcid.org/0000-0003-4942-0439)
- Wanqing Zhang
- Hongping Wei (ORCID: https://orcid.org/0000-0002-9948-8880)
- Junhua Li (ORCID: https://orcid.org/0000-0001-6466-5958)
- Jian Ye (ORCID: https://orcid.org/0000-0003-2661-760X)
- Wu Hao (ORCID: https://orcid.org/0000-0002-8955-8216)
- Mingyan Deng (ORCID: https://orcid.org/0000-0002-8452-421X)
- Chen Shen (ORCID: https://orcid.org/0000-0002-0306-7476)
- Fan Cao (ORCID: https://orcid.org/0009-0009-8890-0567)
- L. Zhang (ORCID: https://orcid.org/0000-0002-6807-7974)
- Run Chen
- Zhengyang Zhu
Institutions
- Ministry of Public Security of the People's Republic of China (CN)
- Wuhan Polytechnic University (CN)
- First Affiliated Hospital of Xi'an Jiaotong University (CN)
- Institute of Forensic Science (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- Journal of Infection
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1016/j.jinf.2025.106489
- Citations
- 2
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 2.72