Modeling the Effect of Stress and Stigma on the Transmission and Control of Tuberculosis Infection
Keywords:
Tuberculosis, Stress, Stigma, Effective reproduction number, simulations.Abstract
In this paper a continuous time deterministic model with health education campaign and treatment strategy is formulated to assess the effect of stress and stigma on the transmission and control of Tuberculosis (TB). The effective reproduction number is obtained and used to investigate the impact of health education campaign and treatment strategies. The effective reproduction numbers for health education campaign and treatment considered separately were found not to be effective as compared to a combination of both strategies. Numerical simulation results show that TB can be reduced or eliminated from the community when as treatment is applied. The disease prevalence and incidence are high when stigma is high and decline gradually when the combination of both treatment and health campaign are administered. We recommend that health education campaign to reduce stress among individuals and stigma for infectious individuals should be accompanied by treatment of active TB individuals for improved reduction of TB disease.
References
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[2] West EL, GadkowskLB, Ostbye T, Piedrahita C, Stout JE. “Tuberculosis knowledge, Altitudes, and beliefs among North Carolinians at increased risk of infection.” N.C MedJ 69(1): 14-20, 2008.
[3] Demissie M, Getalum H, Lindtjoru B. “Community tuberculosis care through TB Clubs in rural North Ethiopia.” Soc Sci Med 56(10): 2009-2018, 2003.
[4] Kelly P. “Isolation and stigma experience of patients with active tuberculosis.” J community Health Nurs 16(4):23-41, 1999.
[5] Link BG, Phela JC. “Conceptualize stigma.” Annual review of Sociology 27: 363-385, 2001.
[6] P. van den Driessche, and J. Watmough. “Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission.” Math. Biosci. 180 (2002), 29–48.
[7] World Health Organization (WHO). “Global Tuberculosis Report (2012)” 2010/2011 Tuberculosis Global Facts.
[8] Z. Feng, C. Castillo-Chavez, and A. F. Capurro. “A model for tuberculosis with exogenous reinfection.” Theor. Popul. Biol. 57:235–247, 2000.
[9] D. Okuonghae, and A. Korobeinikov. “Dynamics of Tuberculosis: The Effect of Direct Observation Therapy Strategy (DOTS) in Nigeria.” Mathematical Modeling of Natural Phenomena, 2 ,101-113, 2007.
[10] T. Cohen, C. Colijn, B. Finklea, and M. Megan. “Exogenous Re-infection and the Dynamics of Tuberculosis Epidemics.” Local Effects in a Network Model of Transmission, J. R. Soc. Interface 4, 523-531, 2007.
[12] F.B. Agusto. “Optimal chemoprophylaxis and treatment control strategies of a tuberculosis transmission model.” World Journal of Modelling and Simulation 5(3) 163-173, 2009.
[13] Stephen, E., Dmitry, K., and Silas, M. “Modeling the Impact of Immunization on the epidemiology of Varicella-Zoster Virus.” Mathematical theory and Modeling.Vol.4, No. 8, pp.46-56, 2014.
[14] N. Nyerere, L. S. Luboobi and Y. Nkansah-Gyekye. “Modeling the Effect of Screening and Treatment on the Transmission of Tuberculosis Infections.” Mathematical Theory and Modeling. Vol.4, No. 7, pp.51-62, 2014.
[15] N. Nyerere, L. S. Luboobi and Y. Nkansah-Gyekye. “Bifurcation and Stability analysis of the dynamics of Tuberculosis model incorporating, vaccination, Screening and treatment.” Communications in Mathematical biology and Neuroscience, Vol. 2014, Article ID 3, 2014.
[16] G.M. Mlay, L.S. Luboobi, D. Kuznetsov, F. Shahada. “Dynamics of one-strain pulmonary tuberculosis model with vaccination and treatment.” Communications in Mathematical Biology and Neuroscience, Article ID 6, 2014.
[17] S.C. Mpeshe, L.S. Luboobi, Y. Nkansah-Gyekye. “Optimal Control Strategies for theDynamics of Rift Valley Fever.” Communications in Optimization Theory, Article ID 5, 2014.
[18] Tesfaye Tadesse Ega, Livingstone S. Luboobi, Dmitry Kuznetsov. “Modeling the Dynamics of Rabies Transmission with Vaccination and Stability Analysis.” Applied and Computational Mathematics. Vol. 4, No. 6, pp. 409-419. doi: 10.11648/j.acm.20150406.13, 2015.
[19] LaSalle, J. P. “The stability of dynamical systems” CBMS-NSF presented regional conference series in applied mathematics 25. SIAM, Philadelphia, 2013.
[20] Massawe, L. N., Massawe, E. S., Makinde, O. D. “Temporal Model for Dengue Disease with Treatment, Advances in Infectious Diseases.” 5 (1):21-36, 2015.
[21] Mlay, G. M., Luboobi, L. S., Kuznetsov, D., Shahada, F. “The Role of Re-Infection in Modeling the Dynamics of One-Strain Tuberculosis Involving Vaccination and Treatment.” Asian Journal of Mathematics and Applications, 2014.
[22] H. Nemawejje, N. Shaban, S. Hove-Musekwa. “Modeling the effect of stress on the dynamics and treatment of Tuberculosis.” MSc. Thesis, UDSM, Dar Es Salaam, 2011.
[23] A. Korobeinikov. “Lyapunov functions and global properties for SEIR and SEIS epidemic models.” Mathematical Medicine and Biology, 21: 75–83, 2004.
[24] C. C. McCluskey. “Lyapunov functions for tuberculosis models with fast and slow progression.” Mathematical Biosciences and Engineering, 3(4) : 603–614, 2006.
[25] Z. Mukandavire, W. Garira, and J. M. Tchuenche. “Modelling effects of public health educational campaigns on HIV/AIDS transmission dynamics.” Appl. Math. Model. 33. 2084–2095, 2015.
[26] J. P. LaSalle. “The stability of dynamical systems.” in CBMS-NSF in Regional Conference Series in Applied Mathematics. No. 25. SIAM, Philadelphia, 1976.
[27] P. Van der Driessche and J. Watmough. “Reproduction numbers and sub threshold endemic equilibria for compartmental models of disease transmission.” Math. Biosciences, 180 29 – 48, 2002.
[28] Feng, Z., Castillo-Chavez, C. and Capurro, A. F. “A model for tuberculosis with exogenous re-infection.” Theoretical population biology, 57, 235-247, 2000.
[29] Dieckmann. O. and Heesterbeek, J.A. “Mathematical Epidemiology of Infectious Disease Model building.” Analysis and Interpretation. Wiley New York.
[30] Kajunguri, J.Hargove, R.Ouifki, F.Nyabadzan. “Modeling the impact of TB Superinfection on the dynamics of HIV-TB coinfection” MSc. Thesis, Stellenbosch University, SA, 2009.
[31] I.A. Adetunde, The Mathematical Models of the Dynamical Behaviour of Tuberculosis Disease in the Upper East Region of the Northern Part of Ghana. A Case Study of Bawku: Current Research in Tuberculosis, 1(2008), 1-6.
[32] Stephen Edward, Nkuba Nyerere. A Mathematical Model for the Dynamics of Cholera with Control Measures. Applied and Computational Mathematics, Vol. 4, No. 2, 2015, pp. 53-63. doi: 10.11648/j.acm.20150402.14.
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Published
2016-08-20
How to Cite
Lengiteng i, L., Kajunguri, D., & Nkansah-Gyekye, Y. (2016). Modeling the Effect of Stress and Stigma on the Transmission and Control of Tuberculosis Infection. American Scientific Research Journal for Engineering, Technology, and Sciences, 24(1), 26–50. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/1923
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