# Comparison of Sojourn Time Distributions in Modeling HIV/AIDS Disease Progression

Tilahun Ferede Asena; Ayele Taye Goshu

Biometrical Letters (2017)

- Volume: 54, Issue: 2, page 155-174
- ISSN: 1896-3811

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topTilahun Ferede Asena, and Ayele Taye Goshu. "Comparison of Sojourn Time Distributions in Modeling HIV/AIDS Disease Progression." Biometrical Letters 54.2 (2017): 155-174. <http://eudml.org/doc/288318>.

@article{TilahunFeredeAsena2017,

abstract = {An application of semi-Markov models to AIDS disease progression was utilized to find best sojourn time distributions. We obtained data on 370 HIV/AIDS patients who were under follow-up from September 2008 to August 2015, from Yirgalim General Hospital, Ethiopia. The study reveals that within the “good” states, the transition probability of moving from a given state to the next worst state has a parabolic pattern that increases with time until it reaches a maximum and then declines over time. Compared with the case of exponential distribution, the conditional probability of remaining in a good state before moving to the next good state grows faster at the beginning, peaks, and then declines faster for a long period. The probability of remaining in the same good disease state declines over time, though maintaining higher values for healthier states. Moreover, the Weibull distribution under the semi-Markov model leads to dynamic probabilities with a higher rate of decline and smaller deviations. In this study, we found that the Weibull distribution is flexible in modeling and preferable for use as a waiting time distribution for monitoring HIV/AIDS disease progression.},

author = {Tilahun Ferede Asena, Ayele Taye Goshu},

journal = {Biometrical Letters},

keywords = {HIV/AIDS; semi-Markov model; sojourn time distributions; transition probability},

language = {eng},

number = {2},

pages = {155-174},

title = {Comparison of Sojourn Time Distributions in Modeling HIV/AIDS Disease Progression},

url = {http://eudml.org/doc/288318},

volume = {54},

year = {2017},

}

TY - JOUR

AU - Tilahun Ferede Asena

AU - Ayele Taye Goshu

TI - Comparison of Sojourn Time Distributions in Modeling HIV/AIDS Disease Progression

JO - Biometrical Letters

PY - 2017

VL - 54

IS - 2

SP - 155

EP - 174

AB - An application of semi-Markov models to AIDS disease progression was utilized to find best sojourn time distributions. We obtained data on 370 HIV/AIDS patients who were under follow-up from September 2008 to August 2015, from Yirgalim General Hospital, Ethiopia. The study reveals that within the “good” states, the transition probability of moving from a given state to the next worst state has a parabolic pattern that increases with time until it reaches a maximum and then declines over time. Compared with the case of exponential distribution, the conditional probability of remaining in a good state before moving to the next good state grows faster at the beginning, peaks, and then declines faster for a long period. The probability of remaining in the same good disease state declines over time, though maintaining higher values for healthier states. Moreover, the Weibull distribution under the semi-Markov model leads to dynamic probabilities with a higher rate of decline and smaller deviations. In this study, we found that the Weibull distribution is flexible in modeling and preferable for use as a waiting time distribution for monitoring HIV/AIDS disease progression.

LA - eng

KW - HIV/AIDS; semi-Markov model; sojourn time distributions; transition probability

UR - http://eudml.org/doc/288318

ER -

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