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A Stochastic Model for Malaria Transmission Dynamics
Joint Authors
Mbogo, Rachel Waema
Luboobi, Livingstone S.
Odhiambo, John
Source
Journal of Applied Mathematics
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-11
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Malaria is one of the three most dangerous infectious diseases worldwide (along with HIV/AIDS and tuberculosis).
In this paper we compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in malaria transmission dynamics.
Relationships between the basic reproduction number for malaria transmission dynamics between humans and mosquitoes and the extinction thresholds of corresponding continuous-time Markov chain models are derived under certain assumptions.
The stochastic model is formulated using the continuous-time discrete state Galton-Watson branching process (CTDSGWbp).
The reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or die out.
Thresholds for disease extinction from stochastic models contribute crucial knowledge on disease control and elimination and mitigation of infectious diseases.
Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models.
In particular, we find that malaria outbreak is more likely if the disease is introduced by infected mosquitoes as opposed to infected humans.
These insights demonstrate the importance of a policy or intervention focusing on controlling the infected mosquito population if the control of malaria is to be realized.
American Psychological Association (APA)
Mbogo, Rachel Waema& Luboobi, Livingstone S.& Odhiambo, John. 2018. A Stochastic Model for Malaria Transmission Dynamics. Journal of Applied Mathematics،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1175967
Modern Language Association (MLA)
Mbogo, Rachel Waema…[et al.]. A Stochastic Model for Malaria Transmission Dynamics. Journal of Applied Mathematics No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1175967
American Medical Association (AMA)
Mbogo, Rachel Waema& Luboobi, Livingstone S.& Odhiambo, John. A Stochastic Model for Malaria Transmission Dynamics. Journal of Applied Mathematics. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1175967
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175967