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Modeling study demonstrates molecular communication frameworks for viral tracking and mutation detection, highlighting new strategies for nanoscale epidemic control.
The Internet of bio-nano things (IoBNT), envisioned as a revolutionary healthcare paradigm, shows promise for epidemic control. This article explores the potential for using molecular communication (MC) to address the challenges in constructing the IoBNT for epidemic prevention, specifically focusing on modeling viral transmission, detecting the virus/infected individuals, and identifying virus mutations. First, the MC channels in macroscale and microscale scenarios are discussed to match viral transmission in both scales separately. In addition, the detection methods for these two scales are studied, along with the localization mechanism designed for the virus/infected individuals. Moreover, an identification strategy is proposed to determine potential virus mutations, which is validated through simulation using the ORF3a protein as a benchmark. Finally, open research issues are discussed. In summary, this article aims to analyze viral transmission through MC, and combat viral spread using signal processing techniques within MC.
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Chen et al. (2025) studied this question.
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