A Mathematical Model for the Population Dynamics of Malaria with a Temperature Dependent Control

Nwankwo, Ann; Okuonghae, D.

doi:10.1007/s12591-019-00466-y

Cited by 16 publications

(15 citation statements)

References 33 publications

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“…Mathematical modeling is a valuable tool to control disease spread effectively. Several useful mathematical models have been formulated in the last few decades to study infectious diseases and develop helpful strategies for the efficient elimination of infection [19][20][21][22][23][24][25]. The compartmental models and real cases are more effective in providing valuable information about a particular disease outbreak.…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Model of COVID-19 Pandemic: A Case Study of Bangkok, Thailand

Riyapan

Shuaib

Intarasit

2021

Computational and Mathematical Methods in Medicine

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In this study, we propose a new mathematical model and analyze it to understand the transmission dynamics of the COVID-19 pandemic in Bangkok, Thailand. It is divided into seven compartmental classes, namely, susceptible S , exposed E , symptomatically infected I s , asymptomatically infected I a , quarantined Q , recovered R , and death D , respectively. The next-generation matrix approach was used to compute the basic reproduction number denoted as R cvd 19 of the proposed model. The results show that the disease-free equilibrium is globally asymptotically stable if R cvd 19 < 1 . On the other hand, the global asymptotic stability of the endemic equilibrium occurs if R cvd 19 > 1 . The mathematical analysis of the model is supported using numerical simulations. Moreover, the model’s analysis and numerical results prove that the consistent use of face masks would go on a long way in reducing the COVID-19 pandemic.

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Section: Introductionmentioning

confidence: 99%

A Mathematical Model of COVID-19 Pandemic: A Case Study of Bangkok, Thailand

Riyapan

Shuaib

Intarasit

2021

Computational and Mathematical Methods in Medicine

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“…Mathematical models are used to simulate the transmission of coronavirus and are helpful to understand the dynamical behavior of an infection, providing tools to estimate the duration and peaks of infection outbreaks and to design efficient control strategies [11,12,13]. Epidemiological mathematical models to be used here are present in health literature [14,15] related to several diseases, being helpful to define public actions to reduce COVID [16,17,18,19,20,21,22].…”

Section: Introductionmentioning

confidence: 99%

Three-level algorithm to control COVID-19 spreading

Dieguez

Batistela

Piqueira

2021

Preprint

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As the main ways of the coronavirus (COVID-19) spreading are airand physical contact, actions to mitigate and suppress its spreading must bedeveloped in order to change population behavior, providing efficient controlstrategies. Here, these actions are described as a simple heuristic frameworkto establish public policies. The possible effects of these actions are modeledas a stratified control algorithm applied to an extension of the Susceptible-Infected-Removed (SIR) compartmental model. The model dynamics is an-alyzed and validated with simulations considering parameters obtained fromepidemiological data from Brazil and Uruguay. Model simulations allow theproposition of a three-level control strategy that, as the numerical experimentsshow, presents promising results for the development of strategies to reducethe spread of COVID-19.

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“…Mathematical models are used to simulate the transmission of coronavirus and are helpful to understand the dynamical behavior of an infection, providing tools to estimate the duration and peaks of infection outbreaks and to design efficient control strategies [11][12][13]. Epidemiological mathematical models to be used here are present in health literature [14,15] related to several diseases, being helpful to define public actions to reduce COVID [16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Three-level algorithm to control COVID-19 spreading

Dieguez

Batistela

Piqueira

2021

Preprint

View full text Add to dashboard Cite

As the main ways of the coronavirus (COVID-19) spreading are air and physical contact, actions to mitigate and suppress its spreading must be developed in order to change population behavior, providing efficient control strategies. Here, these actions are described as a simple heuristic frame work to establish public policies. The possible effects of these actions are modeled as a stratified control algorithm applied to an extension of the Susceptible-Infected-Removed (SIR) compartmental model. The model dynamics is analyzed and validated with simulations considering parameters obtained from epidemiological data from Brazil and Uruguay. Model simulations allow the proposition of a three-level control strategy that, as the numerical experiment sshow, presents promising results for the development of strategies to reduce the spread of COVID-19.

show abstract

A Mathematical Model for the Population Dynamics of Malaria with a Temperature Dependent Control

Cited by 16 publications

References 33 publications

A Mathematical Model of COVID-19 Pandemic: A Case Study of Bangkok, Thailand

A Mathematical Model of COVID-19 Pandemic: A Case Study of Bangkok, Thailand

Three-level algorithm to control COVID-19 spreading

Three-level algorithm to control COVID-19 spreading

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