Channel Characterization of Molecular Communications for Cytokine Storm in COVID-19 Patients

Abstract

In the most severe COVID-19 cases, often the cytokine molecules produced by the immune system to fight off coronavirus infection become hyperactive. This leads to “cytokine storm”, which is a serious adverse medical condition causing multiple organ failures. In this work, we propose a system model that captures the transmission of cytokines from the alveoli, the propagation via the vascular channel, and the reception in the blood vessel wall. We analyze the impact of different diseases on induced cytokine storm. The proposed analytical model helps observe the behavior of cytokine storm in different medical conditions. We perform particle-based simulations to analyze the proposed end-to-end channel model describing the cytokine storm in terms of gain and delay, which is inspired from the existing molecular communication channel models from literature. We observe that the channel gain mostly remains unaffected for upto three times increase in the channel length, while, with four times increase, the gain increases upto 16% at 1000 rad/s frequency. We analyze the channel response to the different stimuli of interactions between the cytokines and their varying release rates. We evaluate the cytokine signal at the receiver and observe that lesser diffusion leads to higher cytokine concentration at the receiver.