COVID-19 Research Tag

Identifying the Issue

COVID -19 pandemic has caused the most severe health problems to adults over 60 years of age, with particularly fatal consequences for those over 80. In this case, age-structured mathematical modelling could be useful to determine the spread of the disease and to develop a better control strategy for different age groups. In this study, we first propose an age-structured model considering two different age groups, the first group with population age below 30 years and the second with population age above 30 years, and discuss the stability of the equilibrium points and the sensitivity of the model parameters. In the second part of the study, we propose an optimal control problem to understand the age-specific role of treatment in controlling the spread of COVID -19 infection.

Objective of the Research

• We propose to study the stability analysis of an age-structured model incorporating the saturation in medical treatment
• We propose to study the optimal control problem to study the effectiveness of treatment in reducing COVID-19 infection

Who should read this?

Academics, Mathematics, Bio-Mathematics, Mathematical Modelling, Doctors-Physicians, Research

Solution

In this research article we work on age-structured models considering two different age groups, the first group with population age below 30 years and the second with population age above 30 years. The results and findings of the modelling studies shows that infection decreases with the implementation of an optimal treatment strategy namely a combined treatment strategy considering treatment for both age groups is effective in keeping cumulative infection low in severe epidemics. Cumulative infection was found to increase with increasing saturation in medical treatment.

Key Features and Benefits

• It is found that the behaviour of the system depends on the value of basic reproduction number. Stability changes based on the value of basic reproduction number
• The results from the optimal control study suggests that with optimal treatment COVID-19 infection can be decreased

Impact

• The work presented in this paper could enhance our understanding of complex COVID-19 dynamics
• It can help physicians with decision making in the treatment of life-threatening COVID-19 pneumonia

Team

• Sri Bishal Chhetri, Research Scholar, Dept. of Mathematics & Computer Science, SSSIHL
• Dr. D K K Vamsi, Asst. Professor, Dept. of Mathematics & Computer Science, SSSIHL
• Prof. (Dr) Carani B Sanjeevi, Vice-Chancellor, SSSIHL

Paper Published in: Differential Equations and Dynamical Systems

Title of paper: Optimal Control Studies on Age Structured Modeling of COVID-19 in Presence of Saturated Medical Treatment of Holling Type III

Read Paper Here: https://doi.org/10.1007/s12591-022-00593-z

This chapter is part of the Book titled “Pandemic and Problems: Lessons for Recovery and Resilience” released by The Tamil Nadu Dr. MGR Medical University.

Identifying the Issue

In this work, we discuss the within-host, the between-host and the multi-scale mathematical models for COVID-19 viral infections. We also present the outcomes of our study.

Objective of the Research

We propose to study the natural history of COVID-19 model and also the role and efficacies of various control strategies including the antiviral drugs and immunomodulators.

Who should read this?

Academics, Mathematics, Bio-Mathematics, Mathematical Modelling, Doctors-Physicians, Research

Solution

In this work, we discuss the within-host, the between-host and the multi-scale mathematical models for COVID-19 viral infections. The results from the natural history of the within-host model suggests that the proposed model undergoes trans-critical bifurcation when the value of basic reproduction number is one. Results from optimal control theory suggests that combined drug therapy is the best strategy to be used to contain the spread of infection at within-host level. At the between-host level, combined use of vaccination and treatment is found to be effective in lowering infection at the population level. From multi-scale work it is found that the spread of infection at community level is influenced by the within-host parameters.

Key Features and Benefits

• It is observed that the viral load decreases the most when antiviral drugs and immunomodulators are used together. This could help doctors and physicians to look for combination therapy as one of the alternative to stop the multiplication of virus in the body
• Vaccination along with treatments can reduce COVID-19 infection
• The spread of infection at community level is influenced by the within-host parameters

Impact

• The work presented in this paper could enhance our understanding of complex interplay of immune response and virus particles in the body
• It can help physicians with decision making in the treatment of life-threatening COVID-19 pneumonia

Team

• Sri Bishal Chhetri, Research Scholar, Dept. of Mathematics & Computer Science, SSSIHL
• Dr. D K K Vamsi, Asst. Professor, Dept. of Mathematics & Computer Science, SSSIHL
• Prof. (Dr) Carani B Sanjeevi, Vice -Chancellor, SSSIHL

Chapter Title: Mathematical Modelling Studies with Reference to COVID-19 Pandemic

Book Title: Pandemic and Problems: Lessons for Recovery and Resilience

The book was released by the Chief Minister of Tamil Nadu, Shri M K Stalin at the Annual Convocation of The Tamil Nadu Dr MGR Medical University, Chennai, held on 20 December 2021.

Identifying the Issue

• While there are many vector-host models developed to study the spread of COVID-19 at population level, there are very few works done to understand the interplay of the immune response and the virus particles in the body. Also there is no mathematical modelling studies that talks about the time optimal control studies on COVID-19
• In this work, firstly, a mathematical model is developed incorporating inter-cellular time delay and the stability analysis of the equilibrium points admitted by the model is performed. Secondly, an optimal control problem is studied with antiviral agents and second-line drugs as control measures incorporating the adverse events caused by antiviral drugs. Lastly, a time-optimal control problem is formulated with the objective to drive the system from any given initial state to the desired infection-free equilibrium state in minimal time

Objective of the Research

• We propose to study the role and efficacies of the first line and second line drugs in reducing COVID-19 burden by framing an optimal control problem
• We propose to perform the stability analysis of the equilibrium points and find the condition for the global stability of the infection-free state
• We propose to frame and study the time-optimal control problem to drive the system from any given initial state to the desired infection-free equilibrium state in minimal time

Who should read this?

Academics, Mathematics, Bio-Mathematics, Mathematical Modelling, Doctors-Physicians, Research

Solution

In this study, we first develop SIV model at within-host level by incorporating the intercellular time delay and analyzing the stability of equilibrium points. The model dynamics admits a disease-free equilibrium and an infected equilibrium with their stability based on the value of the basic reproduction number $R_0$. We then formulate an optimal control problem with antiviral drugs and second-line drugs as control measures and study their roles in reducing the number of infected cells and viral load. The comparative study conducted in the optimal control problem suggests that if the first-line antiviral drugs show adverse effects, considering these drugs in reduced amounts along with the second-line drugs would be very effective in reducing the number of infected cells and viral load in a COVID-19 infected patient. Later, we formulate a time-optimal control problem with the goal of driving the system from any initial state to the desired infection-free equilibrium state in finite minimal time. Using Pontryagin’s Minimum Principle, it is shown that the optimal control strategy is of the bang-bang type, with the possibility of switching between two extreme values of the optimal controls. Numerically, it is shown that the desired infection-free state is achieved in a shorter time when the higher values of the optimal controls. The results of this study may be very helpful to researchers, epidemiologists, clinicians and physicians working in this field.
 

Key Features and Benefits

• When the first line antiviral drugs starts showing adverse events, considering first line antiviral drugs in reduced quantity along with the second line drug is found to be highly effective in reducing the infected cells and viral load in a COVID infected patients and this alternative also proved to be cost effective
• It is found that with higher values of first line and second line drugs the time to reach the desired infection free state decreases. This would imply that the infected cells and viral load in the body of a COVID infected individual becomes zero in short period of time with the higher values of the first line and second line drugs

Impact

• The work presented in this paper could enhance our understanding of complex interplay of immune response and virus particles in the body
• It can help physicians with decision making in the treatment of life-threatening COVID-19 pneumonia

Team

Bishal Chhetri, Vijay M. Bhagat, Swapna Muthusamy, Ananth V S, D. K. K. Vamsi, Carani B Sanjeevi

Paper Published in: RSC Advances (Royal Society of Chemistry)

Title: Time Optimal Control Studies on COVID-19 Incorporating Adverse Events of the Antiviral Drugs

Read Paper Here: Computational and Mathematical Biophysics, 2021, 9:214 – 241

Identifying the Issue

COVID-19 is the largest global pandemic currently and it has emerged as the deadliest infection of the century. It’s still critical to find novel compounds that can inhibit viral replication, in turn reducing the pace of infection.

Objective of the Research

• To design and synthesise benzoxazole-thiazolidinone hybrids (B-T hybrids) using a facile synthetic route.
• To analyse the inhibitory potential of designed B-T hybrids against the SARS-CoV-2 proteases using an in-silico approach.

Who should read this?

COVID-19 Researchers, Medicinal Chemists and Pharmaceutical Industry.

Solution

Hybrid molecules represent a relatively recent area in drug research with promising results.

The two scaffolds (benzoxazole and thiazolidinone) exhibit a wide spectrum of pharmacological activities and showed antiviral efficacy (both in vitro and in vivo) against a variety of viruses.

The hybrids derived from these two scaffolds share a similarity (structurally) with some of the active compounds screened in vitro against SARS-CoV-2.

This motivated us to screen the benzoxazole–thiazolidinone hybrids as SARS-CoV-2 protease inhibitors. In order to achieve this, a combination of docking, dynamics, and free energy studies were employed in this study.

Key Features and Benefits

• Established the key interactions between the B-T hybrids and SARS-CoV-2 proteases.
• A simple four-step synthetic procedure was developed to synthesise the B-T hybrids.
• Identifying a novel compound (MBT9) that could act as an allosteric inhibitor of PLp, thus inhibits viral replication, in turn reducing the pace of infection.

Impact

• This study is related to the COVID-19 research and contributes to the understanding of SARS-CoV-2.
• The in-vivo and in-vitro studies could be carried out to further evaluate the therapeutic potential of the proposed ligands.
• The potential of the B-T hybrids as covalent binders to 3CLp can also be explored, as the conjugate amide group present in the thiazolidinone scaffold of the molecule can serve as a Michael acceptor.

Team

Vijay Sai Krishna Cheerala, Research Scholar, Department of Chemistry, Brindavan Campus, SSSIHL

Prasanth Ghanta, Research Scholar, Department of Biosciences, Prasanthi Nilayam Campus, SSSIHL

Prof. C N Sundaresan, Professor (Hon.), Department of Chemistry, Brindavan Campus, SSSIHL

Paper Published in: RSC Advances (Royal Society of Chemistry)

Title: Design, synthesis and in silico screening of benzoxazole–thiazolidinone hybrids as potential inhibitors of SARS-CoV-2 proteases

Read Paper Here: https://pubs.rsc.org/en/content/articlelanding/2021/ra/d1ra07504g

Identifying the Issue

• Number of reports has suggested symptoms of dyspnea, an indication of impaired lung function with reduced diffusion capacity post SARS-CoV-2 infection
• Need for a more reliable and accurate oxygen monitoring device that can complement pulse oximetry in the remote management of COVID-19 recovered individuals

Objective of the Research

• Monitoring of O2 uptake in SARS-CoV-2 recovered participants to assess their lung function in comparison with healthy individuals
• Designing of a low-cost, eco-friendly, high sensitive, plasmonics based sensor

Who should read this?

COVID-19 researchers, COVID-19 recovered patients, Pulmonologists, COVID Care health experts, Chemical sensor & nanotechnology scientists.

Solution

The trilateral international collaboration between the Sri Sathya Sai Institute of Higher Learning (SSSIHL), India, Macquarie University, Australia (MACQ) and University of Maryland Baltimore County (UMBC), United States of America began in the year 2017. Over the years, the collaboration has grown stronger with multiple collaborative projects and publications between these institutions.

In one such successful research collaboration, a new research study is now published in ACS Sensors. The technology developed is:

• A wood-microfluidics chip & plasmon-coupling based biodegradable and eco-friendly O2 sensor with ultrafast response time (~0.2 sec) and high sensitivity
• This is suggestive that SARS-CoV-2 recovered participants had comparatively lower oxygen uptake than healthy participants
• While this clinical data is preliminary in nature, this unique study presents novel insights into an under researched problem that is of paramount significance given the larger health implications of this ongoing pandemic and the nascent understanding of the post-acute sequelae of SARS-CoV-2

Key Features and Benefits

• Next-gen breath sensors that will help achieve low-cost lung health diagnostic devices
• This technology will help in understanding the impact of COVID-19 on lung health through non-invasive mode of evaluation
• Use of novel, biodegradable wood chips for microfluidics will help save environment from plastic-based one-time use microfluidic chips

Impact

• First time 27-fold phosphorescence emission enhancement using surface plasmon-coupled emission platform
• Use of novel and reusable Au(III) complexes having fluorescence and phosphorescence emission for designing ratiometric O2 sensor
• Highly potential technology for post-COVID lung health monitoring

Team

• STAR Laboratory, Department of Chemistry, Sri Sathya Sai Institute of Higher Learning: Bebeto Rai, Dr. Venkatesh Srinivasan Dr. Kalathur Mohan Ganesh, Dr. Naga Sai Visweswar Kambhampati, Prof. Carani B Sanjeevi and Dr. Sai Sathish Ramamurthy
• MQ Photonics Research Centre, MQ Sustainable Research Centre, Macquarie University: Dr. Robert Malmberg and Dr. Koushik Venkatesan.
• Center for Advanced Sensor Technology, University of Maryland, Baltimore County: Dr. Abhay Andar, Dr. Sai Sathish Ramamurthy and Prof. Govind Rao

Paper Published in: ACS Sensors

Title: Surface Plasmon-Coupled Dual Emission Platform for Ultrafast Oxygen Monitoring after SARS-CoV-2 Infection

Read Paper Here: https://pubs.acs.org/doi/10.1021/acssensors.1c01665

Identifying the Issue

a) While there are many vector-host models developed to study the spread of COVID-19 at population level, there are very few works done to understand the interplay of the immune response and the virus particles in the body. None of the current models developed has studied the role and efficacies of HCQ and BCG Vaccination in reducing COVID-19 burden. Furthermore, these models have not considered explicitly the role of inflammatory mediators such as Cytokines and Chemokine’s released by the body in defending the body against the virus.

b) In this work, a within-host mathematical model is developed and optimal control problem is framed to study the role and efficacies of HCQ and BCG Vaccination in reducing the burden of COVID-19

Objective of the Research

• We propose to study the role and efficacies of HCQ and BCG Vaccination in reducing COVID-19 burden by framing an optimal control problem
• Comparative Effectiveness study is also done to support the results obtained in optimal control problem
• Both the above can help to understand the dynamics and control SARS-Cov-2 virus in a better way

Who should read this?

Anyone in the field of Academics and research, working in areas of Mathematics, Bio-Mathematics, Mathematical Modelling, and also Doctors, especially Physicians

Solution

In this work, we consider two scenarios involving the administration of HCQ and BCG vaccine. The findings of these studies include the following: the average infected cell count and viral load decreased the most when both the HCQ and BCG interventions were applied together in both scenarios. On the other hand, the average susceptible cell count decreased the best when HCQ alone was administered in both these scenarios. The basic reproduction number and viral count decreased the best when HCQ and BCG booster interventions were applied together, reinstating the fact obtained earlier in the optimal control setting.

Key Features and Benefits

• It is observed that the viral load decreased the most when both the HCQ and BCG interventions were applied together. This could help doctors and physicians to look for combination therapy as one of the alternatives to stop the multiplication of virus in the body
• The basic reproduction number and viral count decreased the best when HCQ and BCG booster interventions were applied together

Impact

• The work presented in this paper could enhance our understanding of complex interplay of immune response and virus particles in the body
• It can help physicians with decision making in the treatment of life-threatening COVID-19 pneumonia

Team

• Bishal Chhetri, Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, India
• D K K Vamsi, Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, India
• Bhanu Prakash, Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, India
• Carani B Sanjeevi, Vice-Chancellor, Sri Sathya Sai Institute of Higher Learning, India

Paper Published In: Advances in Dynamical Systems and Application, Volume 16, no. 1, 369-403

Title: “Combined Drug Interventions and its Efficacy in the Reduction of COVID-19 Burden: A Within-Host Modelling Study with reference to HCQ and BCG Vaccination”

Read Paper Here: https://www.ripublication.com/adsa21/v16n1p26.pdf