A SIR Mathematical Model of Dengue Transmission and Its Simulation

Asmaidi, Asmaidi; Sianturi, Paian; Nugrahani, E. H.

doi:10.9790/5728-10525665

Cited by 4 publications

(3 citation statements)

References 2 publications

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“…The slider shows the number of initialization humans, mosquitoes, infection rate, and the rate of population growth. As seen in Figure 4, the graph shows that humans are susceptible will decrease when the number of people infected increase and the result of the trend proposed model was similar to that of the SIR model (a classic and popular approach) [17]. The infection of human illustrates the total percentage of infected humans.…”

Section: Implementation Of the Agent Based Modelmentioning

confidence: 60%

Agent Based Modeling on Dynamic Spreading Dengue Fever Epidemic

2017

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Agent based model (ABM) is a computational model for simulation, behavioral representation and interaction of autonomous agents. The main problem definition related to how to make a dynamic model of dengue fever with consideration of their behavioral and interaction agent. This paper aims to develop IntroductionAn epidemic is the occurrence cases of disease that spreading widely and quickly by infection and affecting many individuals in an area or population at the same time [1]. The spread of infectious disease in a population is a serious health problem and can be an economic threat. The epidemic model aims to controlling spread infections disease and the model commonly used for policy strategies in preventive medicine such as vaccinations, fogging and counseling. Most of the models for epidemic simulation are based on Ordinary Differential Equation (ODE) or statistical model [2][3][4][5]. Unfortunately, ODE and statistical model ignore the effects of individual behavior, interaction and assume a homogeneous environment [2].In order to catch a real picture of how the interaction between actors and their environment, researchers proposed agent based models for involving behavior, interaction and environment factor. Some studies have been conducted such as developing agent based model an Aedes aegypti population dynamics [6]. The model used LAIS simulator and given information about agent larva, pupa and adults, but without information and data of climatology specified. An agent based model for the spread of dengue fever was previously investigated by [7], the result showed that the growing rate of mosquito higher during a summer season than during the winter season. Multi agent modeling and simulation of an Aedes aegypti mosquito population [8] was developed to study whether or not an artificial trap can be effectively used as an active based population control measure. The model for enhancing dengue fever modeling through a multi-scale analysis framework [9] using MASON simulator was developed using climate parameters, socio-economics and demography.Agent based model (ABM) is a computational model for simulation, representation behavior and interaction autonomous agent [10]. ABM is one of dynamic approach besides Cellular Automata. ABM has the ability to construct individual system units at the different levels of representation to describe nonlinear relationships between those units. ABM consists of

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Section: Implementation Of the Agent Based Modelmentioning

confidence: 60%

Agent Based Modeling on Dynamic Spreading Dengue Fever Epidemic

2017

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“…The specific objectives of this study were to measure or to identify the spreading pattern of product marketing through videos and to compare the growth and the decline of the number of viewers in regard video marketing based on Susceptible-Infected-Recovered (SIR) model. Originally, SIR models have been used to investigate the spread of contagious diseases such as dengue (Asmaidi et al 2014;Side and Salmi, 2013) and tuberculosis (Side et al, 2017;Kalu and Inyama, 2012). Since the nature of the spread of disease and the spread of online video posting are alike, SIR model is applicable.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of Online Video Marketing on Facebook Using Susceptible-Infected-Recovered (SIR) Model

Sharif

Bidin

Akil

et al. 2022

JCRINN

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The advancements in technology and high-speed networks give advantages for entrepreneurs to promote their products and services in various forms of posting through social media platforms such as Facebook, Twitter, Instagram and many more. The effectiveness of the video posting in terms of the virality of the video, the time the video reaches the maximum number of viewers and the flow of video spread are very important inputs for the marketers. Therefore, this preliminary study was designed to differentiate the effectiveness of two selected video posting on Facebook promoting two different popular products among women: shawls and slimming product. Susceptible-Infected-Recovered (SIR) models with demography and without demography was used in analysing the data since the nature of the dissemination of the video is similar to the spread of virus. The variables used in the analysis were the number of Facebook users who exposed to the video (Susceptible), received and shared the video (Infected) and stop sharing the video (Recovered). The finding shows the video promoting the shawl is more viral (R0Â > 1) as compared to the video promoting the slimming product (R0 < 1) based on both SIR Model. Although the earliest number of users who received the shawl video was lower but the number of users who received and shared that videos increased tremendously until it reached the maximum number of 19.6 million viewers in 2 days and after that the number was slowly decreased. For slimming product, it started with higher number of viewers, but reached the maximum number of viewers of 10.3 million in 8 days and later the number was gradually decreased. Further study should be done because there are a lot of possibilities or factors that contribute to these findings.

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“…Several studies on mathematical modelling have been developed by [3], in which the mathematical models of the spread of DHF were developed by involving mosquito populations and mosquito eggs. In 2017, [4] developed a mathematical model of the type of SEIR by using insulin as a form of treatment.…”

Section: Introductionmentioning

confidence: 99%

SEIITR Model for Diabetes Mellitus Distribution in Case of Insulin and Care Factors

Fajri¹,

Sanusi

Asmaidi³

2020

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This research is done to learn diabetes mellitus type SEIITR with insulin and care factors. Mathematical model type SEIITR is a mathematical model of diabetes in which the human population is divided into five groups: susceptible humans (Susceptible) S, exposed (Exposed) E, infected I without treatment, infected (Infected) IT with treatment dan recovered (Recovery) R. The SEIITR model has two fixed points, namely, a fixed point without disease and an endemic fixed point. By using basic reproduction numbers (R0), it is found that the fixed point without disease is stable if R0 < 1 and when R0 > 1. Then the fixed point without disease is unstable. The simulation shows the effect of giving insulin to changes in the value of the basic reproduction number. If the effectiveness of β decreases, the basic reproduction number decreases too. Thus, a decrease in the value of this parameter will be able to help reduce the rate of diabetes mellitus in the population.

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A SIR Mathematical Model of Dengue Transmission and Its Simulation

Cited by 4 publications

References 2 publications

Agent Based Modeling on Dynamic Spreading Dengue Fever Epidemic

Agent Based Modeling on Dynamic Spreading Dengue Fever Epidemic

Effectiveness of Online Video Marketing on Facebook Using Susceptible-Infected-Recovered (SIR) Model

SEIITR Model for Diabetes Mellitus Distribution in Case of Insulin and Care Factors

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