A mathematical model for Lassa fever transmission dynamics in a seasonal environment with a view to the 2017–20 epidemic in Nigeria

Ibrahim, Mahmoud A.; Dénes, Attila

doi:10.1016/j.nonrwa.2021.103310

Cited by 35 publications

(37 citation statements)

References 24 publications

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“…Based on the suggestions by Bakare et al and the WHO guidelines, this work presents an optimal control theory model for the transmission dynamics of Lassa fever in the presence of control measures such as avoiding hunting of rodents, early treatment and isolation, proper handling of food, rodent control, the wearing of protective clothing when caring for the sick and avoiding contacts with rodents. This is different from other works on Lassa fever as it incorporates a virus concentration compartment, a periodic rodent population, [4,3] and proper handling of food as an additional control measure to the controls investigated by Peter et al [11], Onah et al [12] and Ibrahim et al [3].…”

Section: Introductionmentioning

confidence: 77%

“…Several mathematical models have been developed to understand the dynamics of Lassa fever within a population. Ibrahim et al [3] and Bakare et al [4] presented a periodic model for Lassa fever transmission dynamics. Their results suggest interventions should be employed for the elimination of the Lassa virus within the community.…”

Section: Introductionmentioning

confidence: 99%

“…Their results suggest interventions should be employed for the elimination of the Lassa virus within the community. However, their models did not include optimal control analysis of intervention measures [3]. Bakare et al [4] further pointed out that a combination of intervention measures such as treatment of Lassa fever with Ribavirin, educating the community on how to practice environmental hygiene, isolation of infected Lassa fever patients and the probable culling any rodents found, could marginally reduce the prevalence of Lassa fever and its mortality rate [4].…”

Section: Introductionmentioning

confidence: 99%

“…Although, Peter et al [11], Onah et al [12] and Ibrahim et al [3] presented an optimal control model of Lassa fever but the virus concentration compartment and periodic rodent population are not considered in their works which is the novelty of this paper. Virus concentration in the environment is considered in this paper due to the faecal droppings and urine discharge by the rodents.…”

Section: Introductionmentioning

confidence: 99%

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An optimal control model for the transmission dynamics of Lassa fever

Madubueze

Chazuka

2022

Preprint

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In this paper, a mathematical model for Lassa fever transmission dynamics with rodent logistic growth is developed and analysed. The stability analysis of the autonomous system of the model is presented. The sensitivity analysis of the parameters is performed using the Partial Rank Correlation Coefficient (PRCC) technique. The non-autonomous model is further analysed for stability of disease-free periodic equilibrium(DFPE) in terms of reproduction number ratio, $R_{0t}.$ It shown that DFPE is locally asymptotically stable when $R_{0t}<1$ and unstable if $R_{0t}>1$. Additionally, the optimal control model is formulated with five control measures namely; personal protective equipment and avoiding hunting of rodents, proper handling of food, treatment and isolation, cleaning and disinfecting the environment, and rodent control. Simulations of the optimal control model show that the combined implementation of the five control measures reduce Lassa fever spread in the population. However, when there is limited resources to implement the five control measures, three or four combined control measures can be implemented provided that proper handle of food is among the combined control measures.

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Section: Introductionmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An optimal control model for the transmission dynamics of Lassa fever

Madubueze

Chazuka

2022

Preprint

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“…Davies et al [30] used a mathematical model capturing seasonal transmission between rodents and humans, assessing the potential outcomes of an introduction of a vaccination program in affected areas. In [31] , a model was established with humans differentiated according to the severity of the disease and with time-periodic parameters for rodent birth rate and carrying capacity of the environment with respect to rodents. The basic reproduction number was introduced as the spectral radius of a linear integral operator and it was shown to serve as a threshold parameter concerning the global dynamics: the disease-free periodic solution is globally asymptotically stable in the case of

1

, while the disease persists if

1

.…”

Section: Introductionmentioning

confidence: 99%

A seasonal model to assess intervention strategies for preventing periodic recurrence of Lassa fever

Barua

Dénes

Ibrahim

2021

Heliyon

Self Cite

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Lassa haemorrhagic fever is listed in WHO's Blueprint priority list of diseases and pathogens prioritized for research and development, affecting several hundreds of thousands of people each year. Lassa fever is spread via infected Natal multimammate mice and also through human-to-human contacts and it is a particular threat to pregnant women. Despite its importance, relatively few mathematical models have been established for modelling Lassa fever transmission up to now. We establish and study a new compartmental model for Lassa fever transmission including asymptomatic carriers, quarantine and periodic coefficients to model annual weather changes. We determine parameter values providing the best fit to data from Nigerian states Edo and Ondo from 2018–20. We perform uncertainty analysis and PRCC analysis to assess the importance of different parameters and numerical simulations to estimate the possible effects of control measures in eradicating the disease. The results suggest that the most important parameter which might be subject of control measures is death rate of mice, while mouse-to-human and human-to-human transmission rates also significantly influence the number of infected. However, decreasing the latter two parameters seems insufficient to eradicate the disease, while a parallel application of decreasing transmission rates and increasing mouse death rate might be able to stop the epidemic.

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