Analysis of a Model of Leishmaniasis with Multiple Time Lags in All Populations

Agyingi, Ephraim; Wiandt, Tamas

doi:10.3390/mca24020063

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…Further studies of this type, using spatio-temporal models that allow assessment of the impact of vaccines targeting different aspects of disease natural history, deployed with different schedules and with differing efficacy are urgently needed. In addition, expanding the modeling of other forms of leishmaniasis including zoonotic cutaneous leishmaniasis [ 93 , 94 ] should be seen as a priority, so that the potential global impact of newly developed vaccines might be more fully assessed.…”

Section: Roadblocks Along the Path To Vaccine Developmentmentioning

confidence: 99%

Overcoming roadblocks in the development of vaccines for leishmaniasis

Kaye

Mohan

Mantel³

et al. 2021

Expert Review of Vaccines

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Introduction The leishmaniases represent a group of parasitic diseases caused by infection with one of several species of Leishmania parasites. Disease presentation varies because of differences in parasite and host genetics and may be influenced by additional factors such as host nutritional status or co-infection. Studies in experimental models of Leishmania infection, vaccination of companion animals and human epidemiological data suggest that many forms of leishmaniasis could be prevented by vaccination, but no vaccines are currently available for human use. Areas covered We describe some of the existing roadblocks to the development and implementation of an effective leishmaniasis vaccine, based on a review of recent literature found on PubMed, BioRxiv and MedRxiv. In addition to discussing scientific unknowns that hinder vaccine candidate identification and selection, we explore gaps in knowledge regarding the commercial and public health value propositions underpinning vaccine development and provide a route map for future research and advocacy. Expert opinion Despite significant progress, leishmaniasis vaccine development remains hindered by significant gaps in understanding that span the vaccine development pipeline. Increased coordination and adoption of a more holistic view to vaccine development will be required to ensure more rapid progress in the years ahead.

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Section: Roadblocks Along the Path To Vaccine Developmentmentioning

confidence: 99%

Overcoming roadblocks in the development of vaccines for leishmaniasis

Kaye

Mohan

Mantel³

et al. 2021

Expert Review of Vaccines

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“…Mucocutaneous leishmaniasis (MCL) is the most disabling form of the disease, and it affects mostly the mucous membranes of the nose and mouth. Visceral leishmaniasis (VL) is the most fatal disease, causing enlargement of the spleen and liver [2]. It may cause epidemic outbreaks with a high mortality rate.…”

Section: Introductionmentioning

confidence: 99%

Modeling visceral leishmaniasis and tuberculosis co-infection dynamics

Egbelowo

Munyakazi

Dlamini

et al. 2023

Front. Appl. Math. Stat.

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The co-infection of visceral leishmaniasis (VL) and tuberculosis (TB) patients pose a major public health challenge. In this study, we develop a mathematical model to study the transmission dynamics of VL and TB co-infection by first analyzing the VL and TB sub-models separately. The dynamics of these sub-models and the full co-infection model are determined based on the reproduction number. When the associated reproduction number (R1) for the TB-only model and (R2) for the VL-only are less than unity, the model exhibits backward bifurcation. If max{R1,R2}=R1, then the TB-VL co-infection model exhibits backward bifurcation for values of R1. Furthermore, if max{R1,R2}=R2, and by choosing the transmission probability, βL as the bifurcation parameter, then the phenomenon of backward bifurcation occurs for values of R2. Consequently, the full model, whose associated reproduction number is R0, also exhibits backward bifurcation when R0=1. The equilibrium points and their stability for the models are determined and analyzed based on the magnitude of the respective reproduction numbers. Finally, some numerical simulations are presented to show the reliability of our theoretical results.

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“…Several scholars have developed different models for HIV, VL, and their co-infection with other diseases to study their transmission dynamics. For example, many mathematical models have been developed to understand the transmission nature of HIV [9,[15][16][17][18] and VL [19][20][21][22][23][24][25] explicitly. In addition, some co-infection models for HIV and malaria [26], HIV-TB [8] and VL and malaria [5] were proposed and analyzed.…”

Section: Introductionmentioning

confidence: 99%

“…Reservoirs acquire infection with leishmaniasis following contact with infected sand flies, and they are infected to their life time. Treating humans while removing reservoirs from the system reduces the fraction of infected sand flies, which gives a good control strategy against the disease [3,21].…”

Section: Introductionmentioning

confidence: 99%

Enhancing reservoir control in the co-dynamics of HIV-VL: from mathematical modeling perspective

Melese

Alemneh

2021

Adv Differ Equ

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HIV patients are vulnerable to developing active visceral leishmaniasis (VL). To understand this complication, we studied a mathematical model for HIV and visceral leishmaniasis coinfection. In this approach, we reckoned two distinct equilibria: the disease-free and the endemic equilibria. The local and global stability of the disease-free equilibrium were thoroughly investigated. To further support the qualitative findings, we performed simulations to quantify the changes of the dynamical behavior of the full model for variation of relevant parameters. Increasing the rate of VL recovery ($\phi _{1}$ ϕ 1 ), the recovery rate for VL–HIV Co-infection ($\phi _{2}$ ϕ 2 ), removing reservoirs ($c_{1}$ c 1 ), minimizing the contact rate ($\beta _{h}$ β h ) are important in controlling the transmission of individual and co-infection disease of VL and HIV. In conclusion, possible measures should be implemented to reduce the number of infected individuals. Therefore, we recommend that policy makers and stakeholders incorporate these measures during planing and implementation phases to control the transmission of VL–HIV co-infection.

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Analysis of a Model of Leishmaniasis with Multiple Time Lags in All Populations

Cited by 3 publications

References 15 publications

Overcoming roadblocks in the development of vaccines for leishmaniasis

Overcoming roadblocks in the development of vaccines for leishmaniasis

Modeling visceral leishmaniasis and tuberculosis co-infection dynamics

Enhancing reservoir control in the co-dynamics of HIV-VL: from mathematical modeling perspective

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