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Abstract Salmonella Typhi, a bacteria, is responsible for typhoid fever, a potentially dangerous infection. Typhoid fever affects a large number of people each year, estimated to be between 11 and 20 million, resulting in a high mortality rate of 128,000 to 161,000 deaths. This research investigates a robust numerical analytic strategy for typhoid fever that takes infection protection into consideration and incorporates fuzzy parameters. The use of fuzzy parameters acknowledges the variation in parameter values among individuals in the population, which leads to uncertainties. Because of their diverse histories, different age groups within this community may exhibit distinct customs, habits, and levels of resistance. Fuzzy theory appears as the most appropriate instrument for dealing with these uncertainty. With this in mind, a model of typhoid fever featuring fuzzy parameters is thoroughly examined. Two numerical techniques are developed within a fuzzy framework to address this model. We employ the non-standard finite difference (NSFD) scheme, which ensures the preservation of essential properties like dynamic consistency and positivity. Additionally, we conduct numerical simulations to illustrate the practical applicability of the developed technique. In contrast to many classical methods commonly found in the literature, the proposed approach exhibits unconditional convergence, solidifying its status as a dependable tool for investigating the dynamics of typhoid disease.

Abstract Hepatitis C infection and HIV/AIDS contaminations are normal in certain areas of the world, and because of their geographic overlap, co-infection can’t be precluded as the two illnesses have a similar transmission course. This current work presents a co-infection model of HIV/AIDS and Hepatitis C virus with fuzzy parameters. The application of fuzzy theory aids in tackling the issues associated with measuring uncertainty in the mathematical depiction of diseases. The fuzzy reproduction number and fuzzy equilibrium points have been determined in this context, focusing on a model applicable to a specific group defined by a triangular membership function. Furthermore, for the model, a fuzzy non-standard finite difference (NSFD) technique has been developed, and its convergence is examined within a fuzzy framework. The suggested model is numerically validated, confirming the dependability of the devised NSFD technique, which successfully retains all of the key properties of a continuous dynamical system.

Abstract The terms susceptibility, exposure, infectiousness, and recovered all have some inherent ambiguity because different population members have different susceptibility levels, exposure levels, infectiousness levels, and recovery patterns. This uncertainty becomes more pronounced when examining population subgroups characterized by distinct behaviors, cultural norms, and varying degrees of resilience across different age brackets, thereby introducing the possibility of fluctuations. There is a need for more accurate models that take into account the various levels of susceptibility, exposure, infectiousness, and recovery of the individuals. A fuzzy SEIR model of the dynamics of the measles disease is discussed in this article. The rates of disease transmission and recovery are treated as fuzzy sets. Three distinct numerical approaches, the forward Euler, fourth-order Runge-Kutta, and nonstandard finite difference (NSFD) are employed for the resolution of this fuzzy SEIR model. Next, the outcomes of the three methods are examined. The results of the simulation demonstrate that the NSFD method adeptly portrays convergent solutions across various time step sizes. Conversely, the conventional Euler and RK-4 methods only exhibit positivity and convergence solutions when handling smaller step sizes. Even when considering larger step sizes, the NSFD method maintains its consistency, showcasing its efficacy. This demonstrates the NSFD technique’s superior reliability when compared to the other two methods, while maintaining all essential aspects of a continuous dynamical system. Additionally, the results from numerical and simulation studies offer solid proof that the suggested NSFD technique is a reliable and effective tool for controlling these kinds of dynamical systems.The convergence and consistency analysis of the NSFD method are also studied.

Rubella is an infectious disease that can spread globally. It spreads in the subtropics as well as the tropics. Although it is commonly thought to be a non-fatal condition, there are several circumstances in which it can be fatal. Pregnant women infected with the Rubella virus face a high risk of fetal development. The main goal of this study is to look into a model for the spread of Rubella while considering a vaccination campaign as a control measure. The positivity and boundedness of the re-infection rubella transmission and vaccination model are investigated. The local and global stability of the equilibrium points is examined. The sensitivity of parameters is also investigated. Three different techniques forward Euler, RK-4, and non-standard finite difference (NSFD) method are developed for the numerical solution, and their simulation results are examined. Among these three, the NSFD method is superior due to its convergence and positive behavior for all step size values. For some values of the step size, the other two techniques failed to produce positivity and convergent solutions. Analytically, the proposed model's convergence, positivity, boundedness, and consistency are investigated. Finally, the impact of the Rubella vaccine on infected populations has been examined, revealing that vaccination is one of the most effective ways to prevent rubella transmission.

IntroductionMalnutrition continues to pose a major challenge to human well-being around the world. In Ethiopia, 39% of children

Wireless sensor networks (WSNs) have gained much interest due to their enormous potential in civil and military applications. The power and radio communication capabilities of the sensor nodes are limited. Because sensor nodes have limited resources, they have weak defense capabilities and are attractive targets for software attacks. Worm-based cyberattacks are among the most significant threats to computers and WSNs’ security and integrity. In this article, a five-compartmental WSN epidemic model is considered. We conducted an investigation into equilibrium analysis and the reproductive number, followed by the development of a nonstandard finite difference numerical scheme for our model. The outcomes of our numerical simulations are then presented. This method yields reliable predictions, which can be valuable for regulators when making decisions related to designing and implementing control strategies. Furthermore, some interesting properties of the developed scheme are investigated, such as positivity, convergence, and consistency. The developed scheme preserves the essential characteristics of disease epidemic models like positivity, convergence, and consistency.

This work investigates the computational study of a six-compartmental mathematical model of tuberculosis disease dynamics with the impact of vaccination. Traditional mathematical models presume that all variables are precise and can be measured or calculated precisely. However, in many real-world scenarios, variables may need to be more accurate or easier to quantify, resulting in model uncertainty. Considering this, fuzziness is introduced into the model by taking the contact, recovery, and death rates due to disease as fuzzy membership functions. Two numerical computational schemes, forward Euler and nonstandard finite difference (NSFD), are designed to solve the model. The positivity and convergence for the developed method are investigated, which are significant characteristics of these dynamical models, and it is revealed that these features are preserved in the extended scheme. Numerical computations are performed to support the analytical results. The numerical and computational results indicate that the proposed NSFD method adequately represents the dynamics of the disease despite the uncertainty and heterogeneity. Moreover, the obtained method generates plausible predictions that regulators can use to design and develop control strategies to support decision-making.

BackgroundMicronutrient deficiencies including vitamin A, vitamin D, and zinc are highly prevalent in children below 5 years of age in low and –middle-income countries. We aimed to evaluate the effectiveness of ready-to-use Lipid-based Nutrient Supplement—Medium Quantity (LNS-MQ) local name “Wawa-mum” on plasma micronutrient status, hemoglobin concentration and anthropometric measurements.MethodsA community-based non-randomized trial was conducted in the Kurram district of Khyber Pakhtunkhwa from January 2018 to June 2019. A total of 110 children aged 6 to 23 months old were recruited and allocated to the intervention and control arm of the study. A total of 57 children in the intervention arm received a daily ration of 50 g of Wawa-mum, for one year. To assess the impact of the intervention on primary outcome measures, i.e., serum vitamin A, D concentration, plasma zinc, and hemoglobin concentration. Blood samples were collected at baseline and after one year following the intervention. The vitamins concentration in serum were assessed using Enzyme-Linked Immunosorbent Assay (ELISA) and plasma zinc by atomic absorption spectrometry. The hemoglobin concentration was measured by an automated hematology analyzer. A 24-h dietary recall interview was used to assess the nutrient intake adequacy. Multivariate Linear regression models were used to analyze the outcomes while controlling for potential confounders.ResultsIn the intervention arm, children had on average 6.2 μg/dL (95% CI 3.0–9.3, value of p

This current work presents an SEIQR model with fuzzy parameters. The use of fuzzy theory helps us to solve the problems of quantifying uncertainty in the mathematical modeling of diseases. The fuzzy reproduction number and fuzzy equilibrium points have been derived focusing on a model in a specific group of people having a triangular membership function. Moreover, a fuzzy non-standard finite difference (FNSFD) method for the model is developed. The stability of the proposed method is discussed in a fuzzy sense. A numerical verification for the proposed model is presented. The developed FNSFD scheme is a reliable method and preserves all the essential features of a continuous dynamical system.

In this research, a multiband patch antenna design based on the superposition of multiple modes at the same resonant frequency is presented. The concept of the contribution of lower order modes (LOMs) with the higher order dominant modes (HODMs) is investigated using characteristic mode analysis (CMA). In order to provide similar broadside radiations in three bands, the radiating capability of the LOMs is enhanced in the resonant frequencies of HODMs. These HODMs when excited alone provide null in the broadside radiations of the antenna. Using a single feed, enhancement in the broadside radiations of the antenna is achieved with the superposition of multiple modes at the same resonant frequency. Based on the proposed concept two antennas have been designed and fabricated. The antenna provides stable and enhanced radiations. simulated and measured results are in good agreement. These antennas find application in many applications including communication systems, base station antennas, 5G communications, satellite communication etc., (© 2023. Springer Nature Limited.)