Optimal control mathemathical SIR model of malaria spread in South Kalimantan

Affandi, Pardi; Faisal, .

doi:10.1088/1742-6596/1116/2/022001

Cited by 6 publications

(9 citation statements)

References 9 publications

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“…According to Satorras [37], we are currently witnessing a golden age in epidemic modeling: models are improving significantly thanks to the continuous addition of data, while the powerful computational resources available now make it possible to extend simulations to new limits. Throughout the years, SIR models have been used to analyse viral infections such as measles [5,6], rubella [7], malaria [8], zika [9], COVID-19 [10,11], dengue [12][13][14][15][16][17][18] and others.…”

Section: Methodsmentioning

confidence: 99%

“…For instance, in the celebrated Susceptible-Infectious-Recovered (SIR) model, individuals are divided into susceptible (healthy people who may acquire the virus), infectious (people who have acquired and can transmit the virus) and recovered (people who cannot propagate the pathogen and have acquired immunity to the virus) [2][3][4]. Yet simple and minimal, the SIR model has been pervasively used to analyse a plethora of viral infections such as measles [5,6], rubella [7], malaria [8], zika [9], COVID-19 [10,11], dengue [12][13][14][15][16][17][18], among others. In the case of vector-borne disease, more refined compartmental models have been introduced in which both human and vector populations are divided into several compartments.…”

Section: Introductionmentioning

confidence: 99%

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Effect of human mobility in Dengue spreading: Study cases for Caldas (CO)

Ospina

Soriano

Tost

et al. 2023

Preprint

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According to the World Health Organization (WHO), dengue is the most common acute arthropod-borne viral infection in the world. The spread of dengue and other infectious diseases is closely related to human activity and mobility. In this paper we analyze the effect on the total number of dengue cases within a population after introducing mobility restrictions as a public health policy. To perform the analysis, we use a complex metapopulation in which we implement a compartmental propagation model coupled with the mobility of individuals between the patches. This model is used to investigate the spread of dengue in the municipalities of Caldas (CO). Two scenarios corresponding to different types of mobility restrictions are applied. In the first scenario, the effect of restricting mobility is analyzed in three different ways: a) limiting the access to the endemic node but allowing the movement of its inhabitants, b) restricting the diaspora of the inhabitants of the endemic node but allowing the access of outsiders, and c) a total isolation of the inhabitants of the endemic node. In this scenario, the best simulation results are obtained when endemic nodes are isolated during a dengue outbreak, obtaining a reduction of up to 22.51% of dengue cases. Finally, the second scenario simulates a total isolation of the network, i.e., mobility between nodes is completely limited. We have found that this control measure reduces the number of total dengue cases in the network by up to 42.67%.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effect of human mobility in Dengue spreading: Study cases for Caldas (CO)

Ospina

Soriano

Tost

et al. 2023

Preprint

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“…In recent years, scholars have studied the evolution of infectious disease transmission by constructing models such as SIR, SEIR, and SEIR. Jinhong Zhang et al (2014) studied the dynamics of the SEIR infectious disease model with saturated incidence and saturated treatment functions, giving the basic regeneration numbers that determine disease extinction and disease survival 11 .P Affandi et al (2018) explored the formation of a modified malaria distribution model through a SIR modeling study. The malaria distribution model was used to analyze the infection rate in South Kalimantan for optimal control of malaria transmission in South Kalimantan 12 .…”

Section: Literature Reviewmentioning

confidence: 99%

“…Jinhong Zhang et al (2014) studied the dynamics of the SEIR infectious disease model with saturated incidence and saturated treatment functions, giving the basic regeneration numbers that determine disease extinction and disease survival 11 .P Affandi et al (2018) explored the formation of a modified malaria distribution model through a SIR modeling study. The malaria distribution model was used to analyze the infection rate in South Kalimantan for optimal control of malaria transmission in South Kalimantan 12 . Ferjouchia H et al (2020) used the SEIRD model to provide a theoretical framework for the prediction of the ongoing epidemic of COVID-19 in Morocco, and the structure and parameters of the proposed model provided insights and ideas for the development of virus dynamics 13 .…”

Section: Literature Reviewmentioning

confidence: 99%

Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19: A data-driven transmission model

Wang

Huang

Dong

et al. 2023

Preprint

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COVID-19 has dramatically changed people’s mobility behavior patterns and affected the operations of different functional sites. In the context of the successive reopening of countries around the world since 2022, it is crucial to understand whether the reopening of different types of locations poses a risk of widespread epidemic transmission. In this paper, by establishing an epidemiological model based on mobile network data, combining the mobile network data provided by Safegraph website, and taking into account the crowd flow characteristics and the changes of susceptible and latent populations, we simulated the trends of the number of crowd visits and the number of epidemic infections at different functional points of interest after the implementation of reopening strategies. Accordingly, the impact of crowd flow changes under different reopening strategies on the risk of epidemic transmission was judged. The model was also validated with daily new cases in ten metropolitan areas in the United States from March to May 2020, and the results showed that the model fitted the evolutionary trend of realistic data more accurately. Further, the points of interest were classified into risk levels, and the corresponding reopening minimum standard prevention and control measures were proposed to be implemented according to different risk levels. The results showed that restaurants and gyms became high-risk points of interest after the implementation of the reopening strategy, especially the general dine-in restaurants were at higher risk. Religious activity centers were the points of interest with the highest average infection rates after the implementation of the reopening strategy. Points of interest such as convenience stores, large shopping malls and pharmacies were at a lower risk for outbreak impact after the reopening strategy was implemented. Based on this, reopening prevention and control strategies for different functional points of interest are proposed to provide decision support for the development of precise prevention and control measures for different sites.

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“…Instruments that underlie the influence of disease spread can be detected through mathematical modeling, applying control strategies, and their applications. Many references that apply control theory to disease problems include [1], [2], [3], [4], [5], [6] also by Kermack, WO and Mc Kendrick, A. G [7], Bellomo, N. and Preziosi, L. [8]. However, control theory is also widely applied to industrial and inventory problems [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Optimum Control in the model of blood fever disease with vaccines and treatment

et al. 2021

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Dengue Hemorrhagic Fever (DHF) is a disease caused by an arbovirus that enters the human body through the Aedes aegypti or Aedes albopictus mosquito. Dengue Hemorrhagic Fever (DHF) is characterized by symptoms of dengue fever; headache; reddish skin that looks like measles; and muscle and joint pain. In some patients, dengue fever can turn into one of two life-threatening forms that lead to decreased immunity. Various ways have been done to prevent the cause of DHF, but the results have not been optimal. The problem of the spread of the dengue virus can also be modeled mathematically and through the stability of the equilibrium point, the dynamics or behavior of the model can be determined. DHF spread can be suppressed by giving control in the form of treatment. This type of treatment is given to infected individuals. This treatment can be controlled optimally by applying the Pontryagin maximum principle. Pontryagin's maximum principle is the optimal control solution in accordance with the objective of maximizing the performance index. The purpose of this study is to discuss a mathematical model for the transmission of the dengue virus in the human body. As an effort to inhibit dengue virus replication, treatment control is used in the model, starting from the formation of a model from determining assumptions, parameters so that the SIV-T model is obtained, determining stability analysis, and then involving optimal

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Optimal control mathemathical SIR model of malaria spread in South Kalimantan

Cited by 6 publications

References 9 publications

Effect of human mobility in Dengue spreading: Study cases for Caldas (CO)

Effect of human mobility in Dengue spreading: Study cases for Caldas (CO)

Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19: A data-driven transmission model

Optimum Control in the model of blood fever disease with vaccines and treatment

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