Mathematical Modelling of Cholera Incorporating The Dynamics of The Induced Achlorhydria Condition And Treatment
Abstract
Cholera is an infectious disease caused by the bacterium Vibrio cholerae rampant in countries with inadequate access to clean water and proper sanitation. In this work a mathematical model for cholera incorporating the dynamics of the induced achlorhydria condition and treatment is analysed. Michaelis-menten equation in microbiology is used to show variation in pH level of the hydrochloric acid in the digestive system. Vibrio cholerae are acid labile and thrive well in alkaline medium.
Once the gastric pH is raised by factors like antacid drugs or surgery the stomach medium become suitable for Vibrio cholerae to thrive and multiply very fast than healthy people. This lead to cholera transmission as the infected individuals with induced achlorhydria condition shed more folds of Vibrio cholerae to the environment. If individuals with achlorhydria condition are treated, the effect of cholera outbreak is reduced. The existence and stability of the equilibrium points is established. Analysis of the model show that the disease free equilibrium is both locally and globally asymptotically stable when the basic reproduction number is less than unity, while the endemic equilibrium is locally asymptotically stable when the reproduction number is greater
than unity. Numerical simulations is done using MATLAB software to show the effect of the induced achlorhydria condition on the spread of cholera and individuals with this condition suffer severe infection during cholera outbreak.
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[2] D. J. Daley and J. Gani, Epidemic modelling: an introduction. No. 15, Cambridge University Press, 2001.
[3] R. I. Joh, H. Wang, H. Weiss, and J. S. Weitz, “Dynamics of indirectly transmitted infectious diseases with immunological threshold,” Bulletin of mathematical biology, vol. 71, no. 4, pp. 845–862, 2009.
[4] G. Pande, B. Kwesiga, G. Bwire, P. Kalyebi, A. Riolexus, J. K. Matovu, F. Makumbi, S. Mugerwa, J. Musinguzi, R. K. Wanyenze, et al., “Cholera outbreak caused by drinking contaminated water from a lakeshore water-collection site, kasese district, south-western uganda, june-july 2015,” PloS one, vol. 13, no. 6, p. e0198431, 2018.
[5] D. L. Taylor, T. M. Kahawita, S. Cairncross, and J. H. Ensink, “The impact of water, sanitation and hygiene interventions to control cholera: a systematic review,” PLoS one, vol. 10, no. 8, p. e0135676, 2015.
[6] G. H. Sack Jr, N. F. Pierce, K. N. Hennessey, R. C. Mitra, R. B. Sack, and D. G. Mazumder, “Gastric acidity in cholera and noncholera diarrhoea,” Bulletin of the World Health Organization, vol. 47, no. 1, p. 31, 1972.
[7] A. Ayoade, M. Ibrahim, O. Peter, and F. Oguntolu, “A mathematical model on cholera dynamics with prevention and control,” 2018.
[8] G. Kolaye, S. Bowong, R. Houe, M. A. Aziz-Alaoui, and M. Cadivel, “Mathematical assessment of the role of
environmental factors on the dynamical transmission of cholera,” Communications in Nonlinear Science and Numerical Simulation, vol. 67, pp. 203–222, 2019.
[9] J. Lin, R. Xu, and X. Tian, “Transmission dynamics of cholera with hyperinfectious and hypoinfectious vibrios:
mathematical modelling and control strategies,” Mathematical Biosciences and Engineering, vol. 16, no. 5, pp. 4339–4358, 2019.
[10] E. A. Bakare and S. Hoskova-Mayerova, “Optimal control analysis of cholera dynamics in the presence of asymptotic transmission,” Axioms, vol. 10, no. 2, p. 60, 2021.
[11] J. A. Pienaar, Escherichia coli Survival Strategies in Simulated Gastric Fluid and the Possible Impact on Calculated Human Infectious Doses. University of Johannesburg (South Africa), 2019.
[12] D. De Biase and P. A. Lund, “The escherichia coli acid stress response and its significance for pathogenesis,” Advances in applied microbiology, vol. 92, pp. 49–88, 2015.
[13] H. L. DuPont, “Gastric acid and enteric infections: souring on the use of ppis,” 2018.
[14] C. Castillo-Chavez, S. Blower, P. Van den Driessche, D. Kirschner, and A.-A. Yakubu, Mathematical approaches for emerging and reemerging infectious diseases: models, methods, and theory, vol. 126. Springer Science & Business Media, 2002.
[15] Z. Hu, Z. Teng, and L. Zhang, “Stability and bifurcation analysis of a discrete predator–prey model with nonmonotonic functional response,” Nonlinear Analysis: Real World Applications, vol. 12, no. 4, pp. 2356–2377, 2011.
[16] O. C. Akinyi, J. Mugisha, A. Manyonge, C. Ouma, and K. Maseno, “Modelling the impact of misdiagnosis and treatment on the dynamics of malaria concurrent and co-infection with pneumonia,” Applied Mathematical Sciences, vol. 7, no. 126, pp. 6275–6296, 2013.
[17] Z. Mukandavire, P. Das, C. Chiyaka, and F. Nyabadza, “Global analysis of an hiv/aids epidemic model,” World Journal of Modelling and Simulation, vol. 6, no. 3, pp. 231–240, 2010.
[18] S. D. Hove-Musekwa, F. Nyabadza, C. Chiyaka, P. Das, A. Tripathi, and Z. Mukandavire, “Modelling and analysis of the effects of malnutrition in the spread of cholera,” Mathematical and computer modelling, vol. 53, no. 9-10, pp. 1583–1595, 2011.
[19] K. N. B. of Statistics, “2019 kenya population and housing census volume ii: distribution of population by administrative units,” 2019.
[20] K. Alderman, L. R. Turner, and S. Tong, “Floods and human health: a systematic review,” Environment international, vol. 47, pp. 37–47, 2012.
[21] K. Kin, T. Yasuhara, M. Kameda, and I. Date, “Animal models for parkinsonˆas disease research: trends in the 2000s,” International journal of molecular sciences, vol. 20, no. 21, p. 5402, 2019.
[22] J. Clemens, “The granuliteˆagranite connexion,” in Granulites and crustal evolution, pp. 25–36, Springer, 1990.
[23] S. Kadaleka, “Assessing the effects of nutrition and treatment in cholera dynamics: The case of malawi,” Unpublished M. Sc. Dissertation. University of Der es Salaam, Tanzania, 2011.
[24] S. Sur and V. K. Sinha, “Event-related potential: An overview,” Industrial psychiatry journal, vol. 18, no. 1, p. 70, 2009.
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