Modeling the Impact of Educational Campaign on the Transmission Dynamics of Ebola

Dautel, Kimberly A; Agyingi, Ephraim

doi:10.1142/s0218339021500248

Cited by 3 publications

(4 citation statements)

References 24 publications

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“…In particular, we intend firstly to develop an EVD model which considers the impact of misconceptions 63 and educational campaigns to control EVD outbreaks. 60 In fact in the model presented in this paper, the modern medicine appears as the only means of treatment. Considering the African context, this is not always the case, because many people link EVD to witchcraft or the punishment of God for the corruption of the humanity.…”

Section: Discussion and Perspectivesmentioning

confidence: 96%

“…Through this control measure, the population is well inform about EVD symptoms and develop cautiousness so that the reduction of contacts between susceptible and infectious individuals can occurs. 60,61 Through educational campaigns, the effective transmission rate of EVD for individuals in compartment J, I, H and D can be written as β(1 − e), βν 1 (1 − e), βε(1 − e) and βν 2 (1 − e), where e measure the efficiency of this control strategy. In Figure 11, we assume for instance that: (i) e = 0 (black curve), (ii) e = 0.2 (cyan curve), (iii) e = 0.4 (magenta curve).…”

Section: Strategy 2: Educational Campaignsmentioning

confidence: 99%

“…This figure highlights that, the number of infected decreases as the impact of educational campaigns in the population increases and add credit to the usefulness of educational campaigns presented in. 60,61 In particular, the curve of the cumulative number of cases shows that after 50 weeks, the number of infected is respectively 3500 cases (for e = 0), 3125 cases (for e = 0.2)…”

Section: Strategy 2: Educational Campaignsmentioning

confidence: 99%

See 2 more Smart Citations

Ebola Virus Disease Dynamics With Some Preventive Measures: A Case Study of the 2018–2020 Kivu Outbreak

et al. 2022

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To fight against Ebola virus disease, several measures have been adopted. Among them, isolation, safe burial and vaccination occupy a prominent place. In this paper, we present a model which takes into account these three control strategies as well as the indirect transmission through a polluted environment. The asymptotic behavior of our model is achieved. Namely, we determine a threshold value [Formula: see text] of the control reproduction number [Formula: see text], below which the disease is eliminated in the long run. Whenever the value of [Formula: see text] ranges from [Formula: see text] and 1, we prove the existence of a backward bifurcation phenomenon, which corresponds to the case, where a locally asymptotically stable positive equilibrium co-exists with the disease-free equilibrium, which is also locally asymptotically stable. The existence of this bifurcation complicates the control of Ebola, since the requirement of [Formula: see text] below one, although necessary, is no longer sufficient for the elimination of Ebola, more efforts need to be deployed. When the value of [Formula: see text] is greater than one, we prove the existence of a unique endemic equilibrium, locally asymptotically stable. That is the disease may persist and become endemic. Numerically, we fit our model to the reported data for the 2018–2020 Kivu Ebola outbreak which occurred in Democratic Republic of Congo. Through the sensitivity analysis of the control reproduction number, we prove that the transmission rates of infected alive who are outside hospital are the most influential parameters. Numerically, we explore the usefulness of isolation, safe burial combined with vaccination and investigate the importance to combine the latter control strategies to the educational campaigns or/and case finding.

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Section: Discussion and Perspectivesmentioning

confidence: 96%

Section: Strategy 2: Educational Campaignsmentioning

confidence: 99%

Section: Strategy 2: Educational Campaignsmentioning

confidence: 99%

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Ebola Virus Disease Dynamics With Some Preventive Measures: A Case Study of the 2018–2020 Kivu Outbreak

et al. 2022

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“…The reproduction number is the number of secondary infections that occur when an infectious person is put into a completely susceptible population. Using the next generation matrix method (see for example Duatel et al [22]) and the DFEs, E 1 0 and E 2 0 , respectively, we obtain the reproduction numbers…”

Section: Existence Of Equilibriamentioning

confidence: 99%

Modeling the Impact of Misinformation on the Transmission Dynamics of COVID-19

Su,

Agyingi

2024

AppliedMath

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The threat posed by the COVID-19 pandemic has been accompanied by an epidemic of misinformation, causing confusion and mistrust among the public. Misinformation about COVID-19 whether intentional or unintentional takes many forms, including conspiracy theories, false treatments, and inaccurate information about the origins and spread of the virus. Though the pandemic has brought to light the significant impact of misinformation on public health, mathematical modeling emerged as a valuable tool for understanding the spread of COVID-19 and the impact of public health interventions. However, there has been limited research on the mathematical modeling of the spread of misinformation related to COVID-19. In this paper, we present a mathematical model of the spread of misinformation related to COVID-19. The model highlights the challenges posed by misinformation, in that rather than focusing only on the reproduction number that drives new infections, there is an additional threshold parameter that drives the spread of misinformation. The equilibria of the model are analyzed for both local and global stability, and numerical simulations are presented. We also discuss the model’s potential to develop effective strategies for combating misinformation related to COVID-19.

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A mathematical model on the impact of awareness and traditional medicine in the control of Ebola: case study of the 2014–2016 outbreaks in Sierra Leone and Liberia

Ouemba Tassé,

Tsanou,

Kum

et al. 2024

IMA Journal of Applied Mathematics

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In the control of infectious diseases worldwide, awareness of the population occupies a prominent place. In Africa, there has been a long standing rivalry between traditional medicine and modern medicine. Any disease control strategy must take into account disease-oriented education, as this has a direct influence on the choice of treatment type to follow. In this work, we present a mathematical model that takes into consideration not only public health awareness but also the significant contribution of traditional medicine to the Ebola treatment effort. This study uses data from the 2014 – 2016 Ebola outbreaks in Sierra Leone and Liberia. Theoretically, we show that our model exhibits a trans-critical bifurcation at $\mathcal{R}_{c}=1$ and a backward bifurcation phenomenon whenever $\mathcal{R}_{c}^{c}<\mathcal{R}_{c}< 1$. While the disease persists when $\mathcal{R}_{c}>1$. In addition, a threshold number $\mathcal{T}_{0}$, is obtained which ensures the global asymptotic stability of the disease-free equilibrium when its value is less than one. Numerically, it is shown that the number of hospitalized infected cases increases more rapidly than the number of infected cases treated by traditional healers in both countries, suggesting that people have a high tendency to visit hospitals than visiting traditional healers. Our analysis reveals that during an Ebola outbreak, awareness messages should target the susceptible population for behavior change in order to mitigate the spread of the disease. Calibrating the model, it fits well the weekly cumulative cases in Sierra Leone and Liberia, and their corresponding estimated control reproduction numbers are $0.5725$ and $0.8340$, respectively.

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Modeling the Impact of Educational Campaign on the Transmission Dynamics of Ebola

Cited by 3 publications

References 24 publications

Ebola Virus Disease Dynamics With Some Preventive Measures: A Case Study of the 2018–2020 Kivu Outbreak

Ebola Virus Disease Dynamics With Some Preventive Measures: A Case Study of the 2018–2020 Kivu Outbreak

Modeling the Impact of Misinformation on the Transmission Dynamics of COVID-19

A mathematical model on the impact of awareness and traditional medicine in the control of Ebola: case study of the 2014–2016 outbreaks in Sierra Leone and Liberia

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