Modeling pyrethroids repellency and its role on the bifurcation analysis for a bed net malaria model

Tsanou, Berge; Kamgang, Jean Claude; Lubuma, Jean M.‐S.; Danga, Duplex Elvis Houpa

doi:10.1016/j.chaos.2020.109809

Cited by 8 publications

(2 citation statements)

References 43 publications

(73 reference statements)

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“…Mostly, they found that malaria will disappear from the population if

, and exist if

. In several cases, mainly when backward bifurcation phenomena occur in their model [ 18 , 49 , 50 , 51 ], it is still possible to find malaria even though

is already less than one.…”

Section: Dynamical Analysis Of the Modelmentioning

confidence: 99%

An Optimal Control Model to Understand the Potential Impact of the New Vaccine and Transmission-Blocking Drugs for Malaria: A Case Study in Papua and West Papua, Indonesia

et al. 2022

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Malaria is one of the major causes of a high death rate due to infectious diseases every year. Despite attempts to eradicate the disease, results have not been very successful. New vaccines and other treatments are being constantly developed to seek optimal ways to prevent malaria outbreaks. In this article, we formulate and analyze an optimal control model of malaria incorporating the new pre-erythrocytic vaccine and transmission-blocking treatment. Sufficient conditions to guarantee local stability of the malaria-free equilibrium were derived based on the controlled reproduction number condition. Using the non-linear least square fitting method, we fitted the incidence data from the province of Papua and West Papua in Indonesia to estimate the model parameter values. The optimal control characterization and optimality conditions were derived by applying the Pontryagin Maximum Principle, and numerical simulations were also presented. Simulation results show that both the pre-erythrocytic vaccine and transmission-blocking treatment significantly reduce the spread of malaria. Accordingly, a high doses of pre-erythrocytic vaccine is needed if the number of infected individuals is relatively small, while transmission blocking is required if the number of infected individuals is relatively large. These results suggest that a large-scale implementation of both strategies is vital as the world continues with the effort to eradicate malaria, especially in endemic regions across the globe.

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“…Mostly, they found that malaria will disappear from the population if

, and exist if

. In several cases, mainly when backward bifurcation phenomena occur in their model [ 18 , 49 , 50 , 51 ], it is still possible to find malaria even though

is already less than one.…”

Section: Dynamical Analysis Of the Modelmentioning

confidence: 99%

An Optimal Control Model to Understand the Potential Impact of the New Vaccine and Transmission-Blocking Drugs for Malaria: A Case Study in Papua and West Papua, Indonesia

et al. 2022

View full text Add to dashboard Cite

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“…Nowadays, these approaches have been proposed to understand the spread of new coronavirus [5] , [6] . Also, different mathematical approaches are proposed to mitigate the effects of several diseases such as ebola [7] , influenza [8] , and malaria [9] . In the last years, a computer science field called artificial intelligence (AI) able to recognize patterns of historical data and support the decision making has received attention to solving problems from the commerce [10] , and industry [11] .…”

Section: Introductionmentioning

confidence: 99%

Multi-step ahead meningitis case forecasting based on decomposition and multi-objective optimization methods

Ribeiro

Mariani

Coelho

2020

Journal of Biomedical Informatics

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Epidemiological time series forecasting plays an important role in health public systems, due to its ability to allow managers to develop strategic planning to avoid possible epidemics. In this paper, a hybrid learning framework is developed to forecast multi-step-ahead (one, two, and three-month-ahead) meningitis cases in four states of Brazil. First, the proposed approach applies an ensemble empirical mode decomposition (EEMD) to decompose the data into intrinsic mode functions and residual components. Then, each component is used as the input of five different forecasting models, and, from there, forecasted results are obtained. Finally, all combinations of models and components are developed, and for each case, the forecasted results are weighted integrated (WI) to formulate a heterogeneous ensemble forecaster for the monthly meningitis cases. In the final stage, a multi-objective optimization (MOO) using the Non-Dominated Sorting Genetic Algorithm – version II is employed to find a set of candidates’ weights, and then the Technique for Order of Preference by similarity to Ideal Solution (TOPSIS) is applied to choose the adequate set of weights. Next, the most adequate model is the one with the best generalization capacity out-of-sample in terms of performance criteria including mean absolute error (MAE), relative root mean squared error (RRMSE), and symmetric mean absolute percentage error (sMAPE). By using MOO, the intention is to enhance the performance of the forecasting models by improving simultaneously their accuracy and stability measures. To access the model’s performance, comparisons based on metrics are conducted with: (i) EEMD, heterogeneous ensemble integrated by direct strategy, or simple sum; (ii) EEMD, homogeneous ensemble of components WI; (iii) models without signal decomposition. At this stage, MAE, RRMSE, and sMAPE criteria as well as Diebold–Mariano statistical test are adopted. In all twelve scenarios, the proposed framework was able to perform more accurate and stable forecasts, which showed, on 89.17% of the cases, that the errors of the proposed approach are statistically lower than other approaches. These results showed that combining EEMD, heterogeneous ensemble and WI with weights obtained by optimization can develop precise and stable forecasts. The modeling developed in this paper is promising and can be used by managers to support decision making.

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Can insecticide resistance increase malaria transmission? A genetics-epidemiology mathematical modeling approach

Mohammed-Awel

Gumel

2023

J. Math. Biol.

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Modeling pyrethroids repellency and its role on the bifurcation analysis for a bed net malaria model

Cited by 8 publications

References 43 publications

An Optimal Control Model to Understand the Potential Impact of the New Vaccine and Transmission-Blocking Drugs for Malaria: A Case Study in Papua and West Papua, Indonesia

An Optimal Control Model to Understand the Potential Impact of the New Vaccine and Transmission-Blocking Drugs for Malaria: A Case Study in Papua and West Papua, Indonesia

Multi-step ahead meningitis case forecasting based on decomposition and multi-objective optimization methods

Can insecticide resistance increase malaria transmission? A genetics-epidemiology mathematical modeling approach

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