A Mathematical Model for Alcoholism Epidemic

Mathematical models are widely used to study the dynamics of infectious diseases as well as the social networks. This study considers a mathematical model for alcoholism transmission for a closed population. The model is derived from the SIR model for infectious diseases. The study utilizes the Runge-Kutta method as the numerical method to solve a system of differential equations describing the transmission of alcoholism.https://ecommons.udayton.edu/stander_posters/1758/thumbnail.jp

Analysis of SIR Mathematical Model for Malaria Disease: A Study in Assam, India

The global outbreak of covid-19 pandemic is still affecting people around the globe very badly. Before the covid-19 pandemic outbreak, several research works were done for the detection and prevention of various infectious diseases using different mathematical modeling. Implementing mathematical modeling to resolve problems in Biology and physiology is generally called Mathematical Biology, an extremely interdisciplinary area. The applications of mathematical modeling in the analysis of infectious diseases help to concentrate on the necessary processes associated with forming the infectious disease epidemiology and specifications estimation. The compartmental mathematical model can be either SI, SIS, SIR, SIRS, or SEIR where S, I, R, and E denote susceptible, infected, recovered, and exposed respectively. Malaria is an infectious disease that has a large economic and health impact on society. This study aims to predict the estimation of suspected, infected and recovered people using the SIR mathematical model of the Barama area of Baksa District in Assam, India. Here we analyzed the Basic Reproductive Ratio of the SIR model for malaria disease and examined if malaria is epidemic or endemic in that area

Simulasi numerik model matematika untuk menganalisis relasi antara korupsi dan dinamika penyebaran penyakit menular

A mathematical model has been widely used to understand complex phenomena in biology, social, and politics. A number of mathematical model has been formulated to understand infectious diseases or corruption phenomena. However, to the best of our knowledge, none of the work has has been conducted to investigate the relation of corruption and transmission dynamics of infectious diseases. In this work, a structured model in the form of system of differential equations has been formulated to investigate the relation between corruption and transmission dynamics of infectious diseases. In this work, a novel mathematical model has been formulated to investigate the relation between corruption and the transmission dynamics of infectious diseases. The results showed that in the presence of corruption the number of infections is higher compared to that in the absence of corruption. Although the implementation of public health intervention can reduce the number of infections, the presence of corruption can increase the disease incidence. This implies that corruption potentially hinder the effort for disease elimination. Numerical simulations showed that in the absence of corruption, the level of efficacy of public health intervention can reduce the number of infections. It showed that 80% efficacy level can eliminate the disease cases, which cannot be achieved in the presence of corruption. The results suggest that the corruption should be minimized in order to achieve disease elimination. When data becomes available, the model would be validated against the data

Local Stability of Equilibrium Points of a SIR Mathematical Model of Infectious Diseases

In this paper, we studied a SIR mathematical model of infectious diseases. We formulate a theorem on existence and uniqueness of solutions and establish the proof of the theorem We showed that the model has two equilibrium points: disease-free and endemic equilibrium. Local stability of the equilibrium points was obtained using reliable Jacobian matrices and basic reproduction number (R0). The analysis reveals that the disease- free equilibrium is locally asymptotically stable if R0 lt1, the infection is temporalwill disappear with time. On the other hand, if nbspR0 gt1, the number of infections rises, an epidemic results and the nbspendemic equilibrium is locally stable.nbspnbs

Mathematical modeling and numerical calculation of an epidemic with medical vaccination in account

This article describes and analyzes mathematical models of the spread of infectious diseases, on the basis of the considered model, a mathematical model of the spread of epidemics is built, it is studied to what extent receiving medical vaccination affects the spread of infectious diseases in this process, and the mathematical models considered in this paper are compared with others. epidemic models

Modeling Infectious Diseases : Two Strain Diseases in Metapopulations

Infectious diseases often mutate and are carried between regions. We consider a mathematical model which begins to account for these factors. We assume two disjoint populations that only occasionally comingle, and two strains of a disease present in these populations. Of interest are the equations describing the dynamics of this system, the conditions under which epidemics will occur, and the long term behavior of the system under various initial conditions. We find that in many ways this system is similar to a simpler one-population model. However, we find evidence that there may be conditions under which both disease strains can coexist, other than the expected case where both strains are of equal strength

On A Model For The Cross Protection Of Two Infectious Diseases

This paper studies the effects of the spread of two similarly transmitted infectious diseases with cross protection in an unvaccinated population using a basic SEIR model with vital dynamics (births and deaths). A basic Mathematical model is built-up to study the joint transmission dynamics of diseases in the population. The equilibriums of these models as well as their stabilities are studied. Specifically, the stability results for disease-free and endemic steady states are proven. Finally, numerical simulations of the models are carried out with Matlab / Mathematica to study the behavior of the solutions in different regions of the parameter space. Keywords: cross protection, infectious diseases, disease-free and endemic equilibria, numerical simulations, joint modelin