Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia

Lema Abate; Megersa Tadesse

doi:doi:10.11648/j.ijdst.20200601.16

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Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia

Lema Abate, Megersa Tadesse

Published in International Journal on Data Science and Technology (Volume 6, Issue 1)

Received: 9 December 2019 Accepted: 25 December 2019 Published: 16 January 2020

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Abstract

Pneumonia is among the major killer diseases in under-five children in the world. In developing countries 3 million children die each year due to pneumonia. Ethiopia is one of the 15 pneumonia high burden countries. The aim of this study was to examine the risk factors of the survival time of under-five pneumonia patients using Bayesian approach analysis. Total of 281 under-five pneumonia patients included in this study. The parametric survival models such as Weibull, Lognormal and Log-logistic baseline distributions were used to fit the datasets by introducing prior distributions. The DIC value was used to compare the baseline distributions, and based on the DIC value the Weibull baseline distribution was selected as good model to fit under-five pneumonia dataset well. The results obtained from the Weibull survival model showed that patients from urban residence and patients who were admitted during patient nurse ratio (PNR) was small; were prolong timing death of under-five pneumonia patients, while patients who admitted during Spring and summer season, patients who suffer comorbidity and severe acute malnutrition (SAM) were shorten timing of death of under-five pneumonia patients. Factors such as sex, residence, Season of Diagnosis, Comorbidity, Severe Acute Malnutrition (SAM), Patient refer status and Patient to Nurse Ratio (PNR) were associated with the survival time of under-five pneumonia in this study. The concerned body should give attention for the factors identified in these study to prevent the mortality of under-five children due to pneumonia.

Published in	International Journal on Data Science and Technology (Volume 6, Issue 1)
DOI	10.11648/j.ijdst.20200601.16
Page(s)	44-52
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), 2020. Published by Science Publishing Group

Keywords

Pneumonia, Under-Five, Parametric Models, Risk Factors, Bayesian Approach, WinBUGs

References

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APA Style

Lema Abate, Megersa Tadesse. (2020). Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia. International Journal on Data Science and Technology, 6(1), 44-52. https://doi.org/10.11648/j.ijdst.20200601.16

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ACS Style

Lema Abate; Megersa Tadesse. Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia. Int. J. Data Sci. Technol. 2020, 6(1), 44-52. doi: 10.11648/j.ijdst.20200601.16

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AMA Style

Lema Abate, Megersa Tadesse. Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia. Int J Data Sci Technol. 2020;6(1):44-52. doi: 10.11648/j.ijdst.20200601.16

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@article{10.11648/j.ijdst.20200601.16,
  author = {Lema Abate and Megersa Tadesse},
  title = {Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia},
  journal = {International Journal on Data Science and Technology},
  volume = {6},
  number = {1},
  pages = {44-52},
  doi = {10.11648/j.ijdst.20200601.16},
  url = {https://doi.org/10.11648/j.ijdst.20200601.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20200601.16},
  abstract = {Pneumonia is among the major killer diseases in under-five children in the world. In developing countries 3 million children die each year due to pneumonia. Ethiopia is one of the 15 pneumonia high burden countries. The aim of this study was to examine the risk factors of the survival time of under-five pneumonia patients using Bayesian approach analysis. Total of 281 under-five pneumonia patients included in this study. The parametric survival models such as Weibull, Lognormal and Log-logistic baseline distributions were used to fit the datasets by introducing prior distributions. The DIC value was used to compare the baseline distributions, and based on the DIC value the Weibull baseline distribution was selected as good model to fit under-five pneumonia dataset well. The results obtained from the Weibull survival model showed that patients from urban residence and patients who were admitted during patient nurse ratio (PNR) was small; were prolong timing death of under-five pneumonia patients, while patients who admitted during Spring and summer season, patients who suffer comorbidity and severe acute malnutrition (SAM) were shorten timing of death of under-five pneumonia patients. Factors such as sex, residence, Season of Diagnosis, Comorbidity, Severe Acute Malnutrition (SAM), Patient refer status and Patient to Nurse Ratio (PNR) were associated with the survival time of under-five pneumonia in this study. The concerned body should give attention for the factors identified in these study to prevent the mortality of under-five children due to pneumonia.},
 year = {2020}
}

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TY  - JOUR
T1  - Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia
AU  - Lema Abate
AU  - Megersa Tadesse
Y1  - 2020/01/16
PY  - 2020
N1  - https://doi.org/10.11648/j.ijdst.20200601.16
DO  - 10.11648/j.ijdst.20200601.16
T2  - International Journal on Data Science and Technology
JF  - International Journal on Data Science and Technology
JO  - International Journal on Data Science and Technology
SP  - 44
EP  - 52
PB  - Science Publishing Group
SN  - 2472-2235
UR  - https://doi.org/10.11648/j.ijdst.20200601.16
AB  - Pneumonia is among the major killer diseases in under-five children in the world. In developing countries 3 million children die each year due to pneumonia. Ethiopia is one of the 15 pneumonia high burden countries. The aim of this study was to examine the risk factors of the survival time of under-five pneumonia patients using Bayesian approach analysis. Total of 281 under-five pneumonia patients included in this study. The parametric survival models such as Weibull, Lognormal and Log-logistic baseline distributions were used to fit the datasets by introducing prior distributions. The DIC value was used to compare the baseline distributions, and based on the DIC value the Weibull baseline distribution was selected as good model to fit under-five pneumonia dataset well. The results obtained from the Weibull survival model showed that patients from urban residence and patients who were admitted during patient nurse ratio (PNR) was small; were prolong timing death of under-five pneumonia patients, while patients who admitted during Spring and summer season, patients who suffer comorbidity and severe acute malnutrition (SAM) were shorten timing of death of under-five pneumonia patients. Factors such as sex, residence, Season of Diagnosis, Comorbidity, Severe Acute Malnutrition (SAM), Patient refer status and Patient to Nurse Ratio (PNR) were associated with the survival time of under-five pneumonia in this study. The concerned body should give attention for the factors identified in these study to prevent the mortality of under-five children due to pneumonia.
VL  - 6
IS  - 1
ER  -

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Author Information

Lema Abate

Department of Statistics, College of Natural and Computational Science, Mizan-Tepi University, Tepi, Ethiopia
Megersa Tadesse

Department of Statistics, College of Natural Science, Jimma University, Jimma, Ethiopia

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APA Style

Lema Abate, Megersa Tadesse. (2020). Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia. International Journal on Data Science and Technology, 6(1), 44-52. https://doi.org/10.11648/j.ijdst.20200601.16

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ACS Style

Lema Abate; Megersa Tadesse. Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia. Int. J. Data Sci. Technol. 2020, 6(1), 44-52. doi: 10.11648/j.ijdst.20200601.16

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AMA Style

Lema Abate, Megersa Tadesse. Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia. Int J Data Sci Technol. 2020;6(1):44-52. doi: 10.11648/j.ijdst.20200601.16

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@article{10.11648/j.ijdst.20200601.16,
  author = {Lema Abate and Megersa Tadesse},
  title = {Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia},
  journal = {International Journal on Data Science and Technology},
  volume = {6},
  number = {1},
  pages = {44-52},
  doi = {10.11648/j.ijdst.20200601.16},
  url = {https://doi.org/10.11648/j.ijdst.20200601.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20200601.16},
  abstract = {Pneumonia is among the major killer diseases in under-five children in the world. In developing countries 3 million children die each year due to pneumonia. Ethiopia is one of the 15 pneumonia high burden countries. The aim of this study was to examine the risk factors of the survival time of under-five pneumonia patients using Bayesian approach analysis. Total of 281 under-five pneumonia patients included in this study. The parametric survival models such as Weibull, Lognormal and Log-logistic baseline distributions were used to fit the datasets by introducing prior distributions. The DIC value was used to compare the baseline distributions, and based on the DIC value the Weibull baseline distribution was selected as good model to fit under-five pneumonia dataset well. The results obtained from the Weibull survival model showed that patients from urban residence and patients who were admitted during patient nurse ratio (PNR) was small; were prolong timing death of under-five pneumonia patients, while patients who admitted during Spring and summer season, patients who suffer comorbidity and severe acute malnutrition (SAM) were shorten timing of death of under-five pneumonia patients. Factors such as sex, residence, Season of Diagnosis, Comorbidity, Severe Acute Malnutrition (SAM), Patient refer status and Patient to Nurse Ratio (PNR) were associated with the survival time of under-five pneumonia in this study. The concerned body should give attention for the factors identified in these study to prevent the mortality of under-five children due to pneumonia.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Application of Bayesian Approach Survival Analysis of Under-five Pneumonia Patients in Tercha General Hospital, South West Ethiopia
AU  - Lema Abate
AU  - Megersa Tadesse
Y1  - 2020/01/16
PY  - 2020
N1  - https://doi.org/10.11648/j.ijdst.20200601.16
DO  - 10.11648/j.ijdst.20200601.16
T2  - International Journal on Data Science and Technology
JF  - International Journal on Data Science and Technology
JO  - International Journal on Data Science and Technology
SP  - 44
EP  - 52
PB  - Science Publishing Group
SN  - 2472-2235
UR  - https://doi.org/10.11648/j.ijdst.20200601.16
AB  - Pneumonia is among the major killer diseases in under-five children in the world. In developing countries 3 million children die each year due to pneumonia. Ethiopia is one of the 15 pneumonia high burden countries. The aim of this study was to examine the risk factors of the survival time of under-five pneumonia patients using Bayesian approach analysis. Total of 281 under-five pneumonia patients included in this study. The parametric survival models such as Weibull, Lognormal and Log-logistic baseline distributions were used to fit the datasets by introducing prior distributions. The DIC value was used to compare the baseline distributions, and based on the DIC value the Weibull baseline distribution was selected as good model to fit under-five pneumonia dataset well. The results obtained from the Weibull survival model showed that patients from urban residence and patients who were admitted during patient nurse ratio (PNR) was small; were prolong timing death of under-five pneumonia patients, while patients who admitted during Spring and summer season, patients who suffer comorbidity and severe acute malnutrition (SAM) were shorten timing of death of under-five pneumonia patients. Factors such as sex, residence, Season of Diagnosis, Comorbidity, Severe Acute Malnutrition (SAM), Patient refer status and Patient to Nurse Ratio (PNR) were associated with the survival time of under-five pneumonia in this study. The concerned body should give attention for the factors identified in these study to prevent the mortality of under-five children due to pneumonia.
VL  - 6
IS  - 1
ER  -

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