Stochastic Approach for Witnessing the Incubation Period of a Patient

Vinoth Raman; Kannadasan Karuppaiah; Subash Chandrabose Gandhi

doi:doi:10.11648/j.bsi.20210603.13

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Stochastic Approach for Witnessing the Incubation Period of a Patient

Vinoth Raman, Kannadasan Karuppaiah, Subash Chandrabose Gandhi

Published in Biomedical Statistics and Informatics (Volume 6, Issue 3)

Received: 10 June 2021 Accepted: 24 June 2021 Published: 23 August 2021

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Abstract

The spread of HIV remains a huge investigation in this present environment. A Mathematical or Statistical model must be developed for estimating parameters related to the epidemic, the death rate of affected cells or the infectious viral production rate. Inability to carry out people evaluates their HIV status has led to widespread lack of correct and comprehensive data on HIV infection, while an individual first involved. Stochastic model measures the predicted point of threshold through discrete and continuous distribution attained by many researchers in last two decades. This paper develops a stochastic model for the time of HIV epidemic in a homosexual population. Expected time of incubation period derived through shock model approach. The fitting of information sets generated through simulation methods that the Alpha statistical distribution ought to be assumed because the epidemic distribution planned the time of stochastic model to search out HIV epidemics. To check the validity of analytical arguments and to explore the dynamics of disease above the epidemic threshold, this study concludes, the possible significance of the result is that transmit HIV in incubation stage is quicker as the intensity of the immune system is lower.

Published in	Biomedical Statistics and Informatics (Volume 6, Issue 3)
DOI	10.11648/j.bsi.20210603.13
Page(s)	54-58
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Distribution, HIV/AIDS, Infection, Incubation Period and Stochastic Model

References

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[2]	Perelson, A. S, Kirschner, D. E and de Boer, R. (1993). Dynamics of HIV infection of CD4+ T cells. Math. Biosci. Vol: 114, pp. 81–125.
[3]	Schenzle, D. (1994). A model for AIDS pathogenesis. Stat. Med. Vol: 13, pp. 2067–2079.
[4]	Medley, G. F., Billard, L., Cox, D. R. and Anderson, R. M. (1988). The distribution of the incubation period for the acquired immunodeficiency syndrome (AIDS). Proceeding of the Royal Society of London, Series B, Biological Sciences, Vol. 233, No. 1272, pp. 367-377.
[5]	Chevret. S., Costagliola, D., Lefrere, and J. J and Valler on, A. J. (1992). A new approach to estimating AIDS incubation times: results in homosexual infected men. Journal of Epidemiology Community Health, Vol. 46 (6), pp. 582-586.
[6]	Lee, S. (1999). Estimation of the maturity of HIV and the incubation period of AIDS patients. http://www.tilastokeskus.fi/isi99/proceedings/arkisto/varasto/lee_0375.pdf.
[7]	Pereson, A. S., Neumann, A. U., Markowitz, M., Leonard, J. M and Ho, D. D. (1996). HIV-1 dynamics in vivo viron clearence rate, infected cell life span, and viral generation time. Science New Science New Series, Vol. 271, pp. 1582-1586.
[8]	Tan and Xiang, Z. (1999). Stochastic Modelling of the dynamics of HIV Pathogenesis under treatment by anti-viral drugs in HIV-infected individuals. Mathematical bioscience, Vol. 156, pp. 69-94.
[9]	Pillai, R. N. (1990). On Mittag-Leffler function and related distributions, Annals of the Institute of statistical Mathematics, Vol: 42, pp. 157-161.
[10]	Anil. V. (2001). A generalized distribution and its application. Journal of the Kerala statistical Association, Vol 12: pp. 11-20.
[11]	Mathai, A. M., Saxena, R. K., Haubold, H. J. (2006). A certain class of Laplace transforms with applications to reaction and reaction-diffusion equations. Atrophy’s. Space Sci. Vol: 305, pp. 283–288.
[12]	Subramanian, C, R. Rajivgandhi and R. Vinoth. (2012), Estimation of the Generalized Logistic Distribution based on the Expected time in Shock Model, Global Journal of Mathematical Sciences: Theory and Practical, Vol. 4, No. 12, pp. 57-62.
[13]	Pradeep Sukla, D. Raja, D. Jegadeesh Ramasamy and R. Vinoth. (2013), Preventing Threshold in Human Immune Virus of Infected Persons through Statistical Model, International Journal of Pharmaceutical Science and Health Care, Vol. 1 (2), pp. 43-46.
[14]	Thirumurugan, A and R. Vinoth. (2016), “Time to Survival of HIV Environment of the Infected Patients”, Journal of Reliability and Statistical Studies, Vol. 9 (2), pp. 91-98.
[15]	Shangguan, D., Liu, Z., Wang, L., Tan R. (2021). A stochastic epidemic model with infectivity in incubation period and homestead–isolation on the susceptible. Journal of Applied Mathematics and Computing. https://doi.org/10.1007/s12190-021-01504-1.

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APA Style

Vinoth Raman, Kannadasan Karuppaiah, Subash Chandrabose Gandhi. (2021). Stochastic Approach for Witnessing the Incubation Period of a Patient. Biomedical Statistics and Informatics, 6(3), 54-58. https://doi.org/10.11648/j.bsi.20210603.13

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ACS Style

Vinoth Raman; Kannadasan Karuppaiah; Subash Chandrabose Gandhi. Stochastic Approach for Witnessing the Incubation Period of a Patient. Biomed. Stat. Inform. 2021, 6(3), 54-58. doi: 10.11648/j.bsi.20210603.13

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AMA Style

Vinoth Raman, Kannadasan Karuppaiah, Subash Chandrabose Gandhi. Stochastic Approach for Witnessing the Incubation Period of a Patient. Biomed Stat Inform. 2021;6(3):54-58. doi: 10.11648/j.bsi.20210603.13

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@article{10.11648/j.bsi.20210603.13,
  author = {Vinoth Raman and Kannadasan Karuppaiah and Subash Chandrabose Gandhi},
  title = {Stochastic Approach for Witnessing the Incubation Period of a Patient},
  journal = {Biomedical Statistics and Informatics},
  volume = {6},
  number = {3},
  pages = {54-58},
  doi = {10.11648/j.bsi.20210603.13},
  url = {https://doi.org/10.11648/j.bsi.20210603.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bsi.20210603.13},
  abstract = {The spread of HIV remains a huge investigation in this present environment. A Mathematical or Statistical model must be developed for estimating parameters related to the epidemic, the death rate of affected cells or the infectious viral production rate. Inability to carry out people evaluates their HIV status has led to widespread lack of correct and comprehensive data on HIV infection, while an individual first involved. Stochastic model measures the predicted point of threshold through discrete and continuous distribution attained by many researchers in last two decades. This paper develops a stochastic model for the time of HIV epidemic in a homosexual population. Expected time of incubation period derived through shock model approach. The fitting of information sets generated through simulation methods that the Alpha statistical distribution ought to be assumed because the epidemic distribution planned the time of stochastic model to search out HIV epidemics. To check the validity of analytical arguments and to explore the dynamics of disease above the epidemic threshold, this study concludes, the possible significance of the result is that transmit HIV in incubation stage is quicker as the intensity of the immune system is lower.},
 year = {2021}
}

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TY  - JOUR
T1  - Stochastic Approach for Witnessing the Incubation Period of a Patient
AU  - Vinoth Raman
AU  - Kannadasan Karuppaiah
AU  - Subash Chandrabose Gandhi
Y1  - 2021/08/23
PY  - 2021
N1  - https://doi.org/10.11648/j.bsi.20210603.13
DO  - 10.11648/j.bsi.20210603.13
T2  - Biomedical Statistics and Informatics
JF  - Biomedical Statistics and Informatics
JO  - Biomedical Statistics and Informatics
SP  - 54
EP  - 58
PB  - Science Publishing Group
SN  - 2578-8728
UR  - https://doi.org/10.11648/j.bsi.20210603.13
AB  - The spread of HIV remains a huge investigation in this present environment. A Mathematical or Statistical model must be developed for estimating parameters related to the epidemic, the death rate of affected cells or the infectious viral production rate. Inability to carry out people evaluates their HIV status has led to widespread lack of correct and comprehensive data on HIV infection, while an individual first involved. Stochastic model measures the predicted point of threshold through discrete and continuous distribution attained by many researchers in last two decades. This paper develops a stochastic model for the time of HIV epidemic in a homosexual population. Expected time of incubation period derived through shock model approach. The fitting of information sets generated through simulation methods that the Alpha statistical distribution ought to be assumed because the epidemic distribution planned the time of stochastic model to search out HIV epidemics. To check the validity of analytical arguments and to explore the dynamics of disease above the epidemic threshold, this study concludes, the possible significance of the result is that transmit HIV in incubation stage is quicker as the intensity of the immune system is lower.
VL  - 6
IS  - 3
ER  -

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Author Information

Vinoth Raman

Quality Measurement and Evaluation Department, Deanship of Quality and Academic Accreditation, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
Kannadasan Karuppaiah

Department of Community Medicine, Melmaruvathur Adhiparasakthi Institute of Medical Sciences and Research, Melmaruvathur, India
Subash Chandrabose Gandhi

Department of Community Medicine, Aarupadai Veedu Medical College & Hospital, Puducherry, India

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APA Style

Vinoth Raman, Kannadasan Karuppaiah, Subash Chandrabose Gandhi. (2021). Stochastic Approach for Witnessing the Incubation Period of a Patient. Biomedical Statistics and Informatics, 6(3), 54-58. https://doi.org/10.11648/j.bsi.20210603.13

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ACS Style

Vinoth Raman; Kannadasan Karuppaiah; Subash Chandrabose Gandhi. Stochastic Approach for Witnessing the Incubation Period of a Patient. Biomed. Stat. Inform. 2021, 6(3), 54-58. doi: 10.11648/j.bsi.20210603.13

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AMA Style

Vinoth Raman, Kannadasan Karuppaiah, Subash Chandrabose Gandhi. Stochastic Approach for Witnessing the Incubation Period of a Patient. Biomed Stat Inform. 2021;6(3):54-58. doi: 10.11648/j.bsi.20210603.13

Copy | Download

@article{10.11648/j.bsi.20210603.13,
  author = {Vinoth Raman and Kannadasan Karuppaiah and Subash Chandrabose Gandhi},
  title = {Stochastic Approach for Witnessing the Incubation Period of a Patient},
  journal = {Biomedical Statistics and Informatics},
  volume = {6},
  number = {3},
  pages = {54-58},
  doi = {10.11648/j.bsi.20210603.13},
  url = {https://doi.org/10.11648/j.bsi.20210603.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.bsi.20210603.13},
  abstract = {The spread of HIV remains a huge investigation in this present environment. A Mathematical or Statistical model must be developed for estimating parameters related to the epidemic, the death rate of affected cells or the infectious viral production rate. Inability to carry out people evaluates their HIV status has led to widespread lack of correct and comprehensive data on HIV infection, while an individual first involved. Stochastic model measures the predicted point of threshold through discrete and continuous distribution attained by many researchers in last two decades. This paper develops a stochastic model for the time of HIV epidemic in a homosexual population. Expected time of incubation period derived through shock model approach. The fitting of information sets generated through simulation methods that the Alpha statistical distribution ought to be assumed because the epidemic distribution planned the time of stochastic model to search out HIV epidemics. To check the validity of analytical arguments and to explore the dynamics of disease above the epidemic threshold, this study concludes, the possible significance of the result is that transmit HIV in incubation stage is quicker as the intensity of the immune system is lower.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Stochastic Approach for Witnessing the Incubation Period of a Patient
AU  - Vinoth Raman
AU  - Kannadasan Karuppaiah
AU  - Subash Chandrabose Gandhi
Y1  - 2021/08/23
PY  - 2021
N1  - https://doi.org/10.11648/j.bsi.20210603.13
DO  - 10.11648/j.bsi.20210603.13
T2  - Biomedical Statistics and Informatics
JF  - Biomedical Statistics and Informatics
JO  - Biomedical Statistics and Informatics
SP  - 54
EP  - 58
PB  - Science Publishing Group
SN  - 2578-8728
UR  - https://doi.org/10.11648/j.bsi.20210603.13
AB  - The spread of HIV remains a huge investigation in this present environment. A Mathematical or Statistical model must be developed for estimating parameters related to the epidemic, the death rate of affected cells or the infectious viral production rate. Inability to carry out people evaluates their HIV status has led to widespread lack of correct and comprehensive data on HIV infection, while an individual first involved. Stochastic model measures the predicted point of threshold through discrete and continuous distribution attained by many researchers in last two decades. This paper develops a stochastic model for the time of HIV epidemic in a homosexual population. Expected time of incubation period derived through shock model approach. The fitting of information sets generated through simulation methods that the Alpha statistical distribution ought to be assumed because the epidemic distribution planned the time of stochastic model to search out HIV epidemics. To check the validity of analytical arguments and to explore the dynamics of disease above the epidemic threshold, this study concludes, the possible significance of the result is that transmit HIV in incubation stage is quicker as the intensity of the immune system is lower.
VL  - 6
IS  - 3
ER  -

Copy | Download