Search

Antibiotic resistance is becoming one of the threats to global health. This crisis has been attributed to the over-the-counter and overuse of antibiotics leading bacteria to gain the ability to resist and survive even in the presence of antimicrobial agents. Escherichia coli (E. coli) is one of the major gram-negative bacteria that are the representative indicators of antibiotic resistance. One of the mechanisms of gaining antibiotic resistance is the ability of E. coli to gain the production of extended-spectrum beta-lactamases (ESBL). In this study, Near East University Hospital data from 2016 to 2019 were used to study the dynamics of ESBL-producing (ESBL+{\text{ESBL}}^{+}) and non-ESBL-producing (ESBL−{\text{ESBL}}^{-}) E. coli infections by using a mathematical model. In our study, the aim was to evaluate the distribution of infections caused by resistant E. coli strains in later years and to increase the success of treatment in patients infected with E. coli by reducing the problem of antibiotic resistance. By using the mathematical model and data of the patients, basic reproduction number (R 0) values were calculated to study epidemiologic dynamics of the disease. The R0E−{R}_{0}^{{E}^{-}} and R0E+{R}_{0}^{{E}^{+}}values for ESBL−{\text{ESBL}}^{-} and ESBL+ {\text{ ESBL}}^{+}\text{ } E. coli infections were calculated, respectively. According to the model and the data used within the study, it was calculated that R0E−{R}_{0}^{{E}^{-}}to be 1,266,403 and R0E+{R}_{0}^{{E}^{+}}to be 2,096,747. Since the values for R0E−{R}_{0}^{{E}^{-}} and R0E+{R}_{0}^{{E}^{+}} were equal or greater than 1, this suggests that currently the ESBL−\hspace{.25em}{\text{ESBL}}^{-} and ESBL+ {\text{ ESBL}}^{+}\text{ } E. coli infections are in epidemic character for Cyprus. Furthermore, when simulation analyses were carried out for the model, it was predicted that in 2042 the ESBL−{\text{ESBL}}^{-} and ESBL+{\text{ ESBL}}^{+} E. coli infection trends will equalize. After 2042, the ESBL− {\text{ESBL}}^{-}\text{ } E. coli infections will indicate a descending pattern whereas ESBL+ {\text{ ESBL}}^{+}\text{ } E. coli infection will increase constantly.

This study aims to investigate the potential impact of inhibitors targeting the papain-like protease (PLpro) of SARS-CoV-2 on viral replication and the host immune response. A mathematical model was developed to simulate the interaction among susceptible cells, infected cells, PLpro, and immune cells, incorporating data on PLpro inhibition. Through numerical simulations using MATLAB, the model parameters were estimated based on available statistical data. The results indicate that strategically positioned inhibitors could impede the virus’s access to host cellular machinery, thereby enhancing the immune response and gradually reducing susceptible and infected cells over time. The dynamics of the viral enzyme PLpro showed reduced activity with the introduction of the inhibitor, leading to a decline in viral replication. Moreover, the immune cell population exhibited functional recovery as the inhibitor suppressed PLpro activity. These findings suggest that inhibitors targeting PLpro may serve as therapeutic interventions against SARS-CoV-2 by inhibiting viral replication and bolstering the immune response. [ABSTRACT FROM AUTHOR]

The global population has been and will continue to be severely impacted by the COVID-19 epidemic. The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer, heart disease, and diabetes. Here, using ordinary differential equations (ODEs), two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease. After that, we highlight the stability assessments that can be applied to these models. Sensitivity analysis is used to examine how changes in certain factors impact different aspects of disease. The sensitivity analysis showed that many people are still nervous about seeing a doctor due to COVID-19, which could result in a dramatic increase in the diagnosis of various ailments in the years to come. The correlation between diabetes and cardiovascular illness is also illustrated graphically. The effects of smoking and obesity are also found to be significant in disease compartments.Model fitting is also provided for interpreting the relationship between real data and the results of thiswork.Diabetic people, in particular, need tomonitor their health conditions closely and practice heart health maintenance. People with heart diseases should undergo regular checks so that they can protect themselves from diabetes and take some precautions including suitable diets. The main purpose of this study is to emphasize the importance of regular checks, to warn people about the effects of COVID-19 (including avoiding healthcare centers and doctors because of the spread of infectious diseases) and to indicate the importance of family history of cancer, heart diseases and diabetes. The provision of the recommendations requires an increase in public consciousness. [ABSTRACT FROM AUTHOR]

The present study discussed a model to describe the SARS-CoV-2 viral kinetics in the presence of saturated antiviral responses. A discrete-time delay was introduced due to the time required for uninfected epithelial cells to activate a suitable antiviral response by generating immune cytokines and chemokines. We examined the system's stability at each equilibrium point. A threshold value was obtained for which the system switched from stability to instability via a Hopf bifurcation. The length of the time delay has been computed, for which the system has preserved its stability. Numerical results show that the system was stable for the faster antiviral responses of epithelial cells to the virus concentration, i.e., quick antiviral responses stabilized patients' bodies by neutralizing the virus. However, if the antiviral response of epithelial cells to the virus increased, the system became unstable, and the virus occupied the whole body, which caused patients' deaths. [ABSTRACT FROM AUTHOR]

This study aims to examine the early detection and treatment of conjunctivitis (eye infection) through vaccination and recovery measures, both with and without medication. We develop an immune system-boosting mathematical model and convert it to a fractionally ordered model using the ABC operator. Key properties, such as the uniqueness and boundedness of the model, are investigated using Banach space. To assess the stability of the newly developed S E V I R u R i system and confirm the occurrence of flip bifurcation, we conduct both qualitative and quantitative analyses. We calculate the basic reproductive number, R 0 , using an advanced approach and analyze its impact across different sub-compartments. Sensitivity analysis is performed on each parameter to understand the rate of change sensitivity. The Atangana–Toufik method is employed to solve the system for various fractional values, providing a reliable bounded solution. Simulations are conducted to observe the real behavior and effects of the conjunctivitis virus, showing that individuals with a strong immune system can recover with or without medication. Finally, we determine the actual state of virus control post-early detection, accounting for treated and untreated individuals due to the robust immune system and precautionary measures. [ABSTRACT FROM AUTHOR]