MODELING AND SIMULATION FOR THE SPREAD OF COVID-19 IN AN INDIAN CITY: A CASE STUDY

We present a case study on modeling and predicting the course of Covid-19 in the Indian city of Pune. The results presented in this paper are concerned primarily with the wave of infections triggered by the Delta variant during the period between February and June 2021. Our work demonstrates the necessity for bringing together compartmental stock-and-flow and agent-based models and the limitations of each approach when used individually. Some of the work presented here was carried out in the process of advising the local city administration and reflects the challenges associated with employing these models in a real-world environment with its uncertainties and time pressures. Our experience, described in the paper, also highlights the risks associated with forecasting the course of an epidemic with evolving variants. © 2022 IEEE.

Research on the Influence of Securities Markets on Cross-Border Capital Flows Based on the DCC-MVGARCH Model

In the study of the impact of cross-border capital flows, most scholars at home and abroad focus on the method of linear time series mainly based on the vector autoregressive model (VAR), ignoring the volatility of variables in time series. In order to make up for the deficiency, the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) model can be used to study the nonlinear time-varying correlation between variables. With the help of Eviews12 software and the DCC-MVGARCH model, this paper studies the impact of securities markets on cross-border capital flows in China from domestic and foreign perspectives in the context of two financial crises and COVID-19. The results indicate that financial crises affect the correlation between the securities markets and cross-border capital flows. China's stock market is positively correlated with short-term capital flows and negatively correlated with long-term capital flows. Its booming bond market promotes short-term capital flows but fails to affect the long-term capital flows, and China's short-term capital flows are increasingly linked to the volatility of foreign stock markets. Therefore, it is necessary to improve the mechanism for better monitoring and analyzing cross-border capital flows, promote further development of financial supervision, and guide market players to face the securities market rationally. © 2023 SPIE.

Automated, flow-based chemiluminescence microarray immunoassay for the rapid multiplex detection of IgG antibodies to SARS-CoV-2 in human serum and plasma (CoVRapid CL-MIA).

In the face of the COVID-19 pandemic, the need for rapid serological tests that allow multiplexing emerged, as antibody seropositivity can instruct about individual immunity after an infection with SARS-CoV-2 or after vaccination. As many commercial antibody tests are either time-consuming or tend to produce false negative or false positive results when only one antigen is considered, we developed an automated, flow-based chemiluminescence microarray immunoassay (CL-MIA) that allows for the detection of IgG antibodies to SARS-CoV-2 receptor-binding domain (RBD), spike protein (S1 fragment), and nucleocapsid protein (N) in human serum and plasma in less than 8 min. The CoVRapid CL-MIA was tested with a set of 65 SARS-CoV-2 serology positive or negative samples, resulting in 100% diagnostic specificity and 100% diagnostic sensitivity, thus even outcompeting commercial tests run on the same sample set. Additionally, the prospect of future quantitative assessments (i.e., quantifying the level of antibodies) was demonstrated. Due to the fully automated process, the test can easily be operated in hospitals, medical practices, or vaccination centers, offering a valuable tool for COVID-19 serosurveillance. Graphical abstract.

Modelling the Impact of Multiple Pro-inflammatory Cytokines Using Molecular Communication

Motivated by various health care applications and many other novel fields of Molecular Communication (MC), it has become an important field of research since the last decade. This paper proposes a molecular communication-based model for the spread of the SARS-CoV2 virus in the human body. The virus uses the ACE2 receptor as a gateway to enter the blood vessels, organs and then replicate itself. In response to the infection, the immune system synthesizes pro-inflammatory cytokines such as IL6, IL2, and TNFa. This active bodily response may be further compromised by the generation of anti-inflammatory cytokines such as IL4 and IL10. We also propose a mathematical model using a Markov state transition for a flow-based molecular communication system which contributes to the detection of these pro-inflammatory cytokines level and gives a further inference about the infection in the body by taking multiple cytokines into account. © 2022 IEEE.

A Molecular Communications System for the Detection of Inflammatory Levels Related to COVID-19 Disease.

A recent and extensive research activity highlighted the process behind the attack and spread of COVID-19 in the human body. What emerged is that the SARS-CoV-2 virus makes use of both the ACE2 receptor, expressed by pneumocytes in the ephitelial alveolar lining, and by the endothelium to spread the disease and to replicate itself. Since the endothelium is an extended tissue lying in the circulatory system, this may lead to a large state of diffuse endothelial inflammation with serious clinical consequences. This situation may be further compromised by the immune system, that may generate pro-inflammatory cytokines (IL-6) as a consequence of the infection. In this paper we propose and analyze a molecular communication system, designed for the detection of excessive IL-6 level, that allows monitoring its evolution in the blood vessels. The proposed analysis was performed by using the BiNS2 simulator, which is suitable for the numerical analysis of flow-based molecular communications in blood vessels, as well as Markov models of the endothelium.