arXiv subjects

Rupchand Sutradhar

Publications and source records attributed to Rupchand Sutradhar.

8 recordsLinked to original sources

arXiv2026

Modeling of Pneumococcal and Respiratory Syncytial Virus Pneumonia: An Epidemiological Review, with Statistical Inference

Infectious diseases continue to pose significant public health challenges worldwide, requiring effective prevention and control strategies to mitigate their negative impact. Infectious diseases can be broadly classified into two groups: vaccine-preventable diseases (e.g., measles, polio, influenza, hepatitis B, pneumonia) and vaccine-non-preventable diseases (e.g., HIV/AIDS). Vaccine-preventable disease models are one of the essential tools for understanding infectious disease dynamics, evaluating intervention strategies, and guiding public health policies. In this review article, we explore the recent advancements in modeling two particular vaccine-preventable infectious diseases. Here, we consider both deterministic and stochastic models to comprehensively capture the complexity of disease transmission, vaccine efficacy, and population-level immunity. We highlight the application of these models to the infectious diseases, namely, bacterial and viral pneumonia caused by the bacteria Streptococcus pneumoniae (S. pneumoniae) and the respiratory syncytial virus (RSV). Pneumonia carry a substantial global burden, where modeling has played a crucial role in assessing vaccine impacts and optimizing immunization strategies to minimize the disease burden. By synthesizing recent methodologies and findings, this review provides valuable insights for future research and policy decisions aimed at improving vaccine-preventable disease control for pneumonia caused by S. pneumoniae and RSV.

q-bio.PE↗

arXiv2025

Exploration of Hepatitis B Virus Infection Dynamics through Physics-Informed Deep Learning Approach

Accurate forecasting of viral disease outbreaks is crucial for guiding public health responses and preventing widespread loss of life. In recent years, Physics-Informed Neural Networks (PINNs) have emerged as a promising framework that can capture the intricate dynamics of viral infection and reliably predict its future progression. However, despite notable advances, the application of PINNs in disease modeling remains limited. Standard PINNs are effective in simulating disease dynamics through forward modeling but often face challenges in estimating key biological parameters from sparse or noisy experimental data when applied in an inverse framework. To overcome these limitations, a recent extension known as Disease Informed Neural Networks (DINNs) has emerged, offering a more robust approach to parameter estimation tasks. In this work, we apply this DINNs technique on a recently proposed hepatitis B virus (HBV) infection dynamics model to predict infection transmission within the liver. This model consists of four compartments: uninfected and infected hepatocytes, rcDNA-containing capsids, and free viruses. Leveraging the power of DINNs, we study the impacts of (i) variations in parameter range, (ii) experimental noise in data, (iii) sample sizes, (iv) network architecture and (v) learning rate. We employ this methodology in experimental data collected from nine HBV-infected chimpanzees and observe that it reliably estimates the model parameters. DINNs can capture infection dynamics and predict their future progression even when data of some compartments of the system are missing. Additionally, it identifies the influential model parameters that determine whether the HBV infection is cleared or persists within the host.

q-bio.QM↗

arXiv2025

Exploration of Hepatitis B Virus Infection Dynamics through an Intracellular Model

Analysis of the cell population generally provides average information about viral infection in a host whereas the intracellular model captures the individual cellular responses. The primary goal of this study is to comprehensively analyze the intracellular dynamics of hepatitis B virus (HBV) infection and to identify the most influential factors. In this study, an intracellular HBV infection dynamics model is proposed by considering several intracellular steps that are observed in the virus life cycle. Upon comparison with the experimental data, it is seen that the model solutions exhibit a good agreement. The well-known fourth-order Runge-Kutta method is applied to numerically solve the proposed model. The effects of HBx proteins, dslDNA containing intermediates, intracellular delay and initial concentration of cccDNAs are explicitly studied. In order to identify the most positively and also the most negatively sensitive parameter of the proposed model, the global sensitivity analysis is performed using the widely-used method, Latin hypercube sampling-partial rank correlation coefficients. As a result, it is observed that HBx proteins have notable impacts on the dynamics of the infection, whereas intracellular delay and dslDNA-containing intermediates may not significantly affect the infection. This study also suggests that sub-viral particles could potentially contribute to the progression of the infection. Furthermore, recycling of capsids (an intracellular process perhaps unique to the HBV life cycle, where a portion of the newly produced capsids return to the nucleus and amplify the cccDNAs) is found to play an important role in enhancing the infection.

math.DS↗

arXiv2024

Multi-point Infection Dynamics of Hepatitis B in the Presence of Sub-Viral Particles

Hepatitis B virus (HBV) is considered as etiological agent of the lethal liver disease hepatitis B. Globally, hepatitis B is recognized as one of the prevailing infectious diseases with a significant impact on human health. In spite of being non-infectious in nature, sub-viral particles (SVPs) , composed with mainly viral surface proteins, play critical roles in the persistence and progression of the infection. Although the understanding on the functions of these non-infectious SVPs remains limited and incomplete. In this study, a mathematical model is proposed for the first time by incorporating the roles of SVPs and including the effects of capsids recycling. The impacts of spatial mobility of capsids, viruses, SVPs and antibodies are also taken into account in this model. Overall, this model carry unique characteristics in the context of this viral infection. This study investigates the changes in the dynamics of infection considering both single-point as well as multi-point infection initial condition. As a result, it is observed that SVPs can significantly enhance intracellular viral replication and gene expression by reducing the neutralization of virus particles by antibodies. The recycling of capsids substantially increase the concentration of SVPs. The experiments which are carried out on single-point as well as multi-point infection initial conditions show that if the liver is infected at more than one point, infection propagates rapidly. The outcomes of the proposed model strongly recommend that it is imperative to consider the diffusion term while HBV infection dynamics are illustrated.

q-bio.QM↗

arXiv2024

Combination Therapy for Chronic Hepatitis B Using Capsid Recycling Inhibitor

In this paper, we investigate the dynamics of hepatitis B virus infection taking into account the implementation of combination therapy through mathematical modeling. This model is established considering the interplay between uninfected cells, infected cells, capsids, and viruses. Three drugs are considered for specific roles (i) pegylated interferon (PEG IFN) for immune modulation, (ii) lamivudine (LMV) as a reverse-transcriptase inhibitor, and (iii) entecavir (ETV) to block capsid recycling. Using these drugs, three combination therapies are introduced, specifically CT PEG IFN plus LMV, CT PEG IFN plus ETV, and CT PEG IFN plus LMV plus ETV. As a result, when LMV is used in combination therapy with PEG IFN and ETV, the impacts of ETV become insignificant. In conclusion, if the appropriate drug effectively inhibits reverse transcription, there is no need for an additional inhibitor to block capsid recycling.

q-bio.CB↗

arXiv2024

On existence of traveling wave of an HBV infection dynamics model: A novel approach

In this work, a hepatitis B virus infection dynamics model is proposed including the spatial dependence of viruses. The existence of traveling waves for the proposed model is established through the application of the celebrated Gersgorin theorem. The procedure followed to establish the existence of a traveling wave solution is innovative and probably the first attempt of this particular approach. The elasticity of basic reproduction number with respect to some model parameters are also shown. Furthermore, the effects of spatial diffusivity of the viruses on infection are studied, and it is noticed that due to the diffusion, viruses spread rapidly throughout the liver.

math.DS↗

arXiv2024

Understanding Hepatitis B Virus Infection through Hepatocyte Proliferation and Capsid Recycling

Proliferation of uninfected as well as infected hepatocytes and recycling of DNA-containing capsids are two major mechanisms playing significant roles in the clearance of hepatitis B virus (HBV) infection. In this study, the temporal dynamics of this infection are investigated through two in silico bio-mathematical models considering both proliferation of hepatocytes and the recycling of capsids. Both models are formulated on the basis of a key finding in the existing literature: mitosis of infected yields in two uninfected progenies. In the first model, we examine regular proliferation (occurs continuously), while the second model deals with the irregular proliferation (happens when the total number of liver cells decreases to less than 70% of its initial volume). The models are calibrated with the experimental data obtained from an adult chimpanzee. Results of this study suggest that when both hepatocytes proliferate with equal rate, proliferation aids the individual in a rapid recovery from the acute infection whereas in the case of chronic infection, the severity of the infection increases if the proliferation occurs frequently. On the other hand, if the infected cells proliferate at a slower rate than uninfected cells, the proliferation of uninfected hepatocytes contributes to increase the infection, but the proliferation of infected hepatocytes acts to reduce the infection from the long-term perspective. Furthermore, it is also observed that the differences between the outcomes of regular and irregular proliferations are substantial and noteworthy.

q-bio.PE↗

arXiv2023

Re-cycling of DNA-containing Capsids Enhances Hepatitis B Virus Infection

Hepatitis B virus infection is a deadly liver disease. A part of newly produced HBV DNA-containing capsids are reused as a core particle in HBV replication. It is investigated that the recycling of HBV capsids greatly affects the intracellular dynamics of HBV infection. The main purpose of the present work is to study the recycling effects of HBV DNA-containing capsids in the HBV infection. Incorporating recycling effects of capsids, a four-compartment mathematical model is proposed for the first time in order to understand the dynamics of HBV infection in a better way. The well-posedness of the model is obtained by showing non-negativity, boundedness, and uniqueness of the solution. The explicit formula for the basic reproduction number is determined by applying the next-generation approach method. The proposed model is solved with help of fourth-order explicit Runge-Kutta method. Through a rigorous comparison with experimental data obtained from four chimpanzees, the proposed model demonstrates a strong correspondence with the dynamics of HBV infection. Global sensitivity analysis is also conducted to identify the most positively as well as negatively sensitive parameters for each compartment in the model. In the context of biology, depending on the value of basic reproduction number, the present model possesses two global asymptotically stable steady states: disease-free and endemic. The present study shows that the consideration of recycling of capsids reverses the existing mechanism of infection dynamics. This study also reveals that the accumulation of capsids within the infected hepatocytes is a key factor for exacerbating the disease. Moreover, another major finding of our study is that due to recycling of capsids, the number of released virus increases in spite of low virus production rate. The recycling of capsids acts as a positive feedback loop in the viral infection.

math.DS↗