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

Tilahun 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 -