Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital

Roseline Achieng Oburu; Joseph Eyang’an Esekon; Martin Mutwiri Kithinji

doi:doi:10.11648/j.ajtas.20231205.11

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Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital

Roseline Achieng Oburu, Joseph Eyang’an Esekon, Martin Mutwiri Kithinji

Published in American Journal of Theoretical and Applied Statistics (Volume 12, Issue 5)

Received: 4 August 2023 Accepted: 28 August 2023 Published: 12 September 2023

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Abstract

COVID-19 is an infectious disease caused by the novel coronavirus: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The disease quickly spread, resulting in an epidemic in China and a number of cases in other countries around the world. This led to inconsistent health conditions and caused unceasing loss of human lives. Globally, the current COVID-19 pandemic posed a significant and imminent threat to healthcare systems, including Kenya, in terms of patient triage and allocation of limited resources. In this study we analyze time to recovery of the COVID-19 patients at AIC Kijabe hospital. A retrospective cohort study was used to review the existing medical records of 66 patients who tested positive for COVID-19 at AIC Kijabe Hospital. Kaplan-Meier curves were used in determining the probability of recovery. For statistical comparison of the survival curves, Log-rank test statistic was used while Cox proportional hazards model was used to investigate the relation between time to recovery and the predictor variables. Results showed that female patients recovered faster than male patients while there was no significant difference between the survival curves for gender and marital status among the COVID-19 patients. In the Cox proportional hazards model, only age was significant with a p - value (0.0463) and therefore affected the time to recovery of the COVID-19 patients while the rest of the variables, gender and marital status were not significant. In conclusion, age was the only variable that had an effect on the time to recovery of COVID-19 patients.

Published in	American Journal of Theoretical and Applied Statistics (Volume 12, Issue 5)
DOI	10.11648/j.ajtas.20231205.11
Page(s)	103-109
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), 2023. Published by Science Publishing Group

Keywords

COVID-19, Kaplan-Meier, Log-rank Test, Cox Proportional Hazards Model, Survival Analysis

References

[1]	Bewick, V., Cheek, L., & Ball, J. (2004). Statistics review 12: survival analysis. Critical care, 8, 1-6.
[2]	Chen, R., Liang, W., Jiang, M., Guan, W., Zhan, C., Wang, T., ... & for COVID, M. T. E. G. (2020). Risk factors of fatal outcome in hospitalized subjects with coronavirus disease 2019 from a nationwide analysis in China. Chest, 158 (1), 97-105.
[3]	Cox, D. R. (1972). Regression models and life tables. Journal of the Royal Statistical Society: Series B (Methodological), 34 (2), 187-202.
[4]	Gyeltshen, K., Tsheten, T., Dorji, S., Pelzang, T., & Wangdi, K. (2021). Survival analysis of symptomatic COVID-19 in phuentsholing municipality, Bhutan. International Journal of Environmental Research and Public Health, 18 (20), 10929.
[5]	Kang, D., Choi, H., Kim, J. H., & Choi, J. (2020). Spatial epidemic dynamics of the COVID-19 outbreak in China. International journal of infectious diseases, 94, 96-102.
[6]	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American statistical association, 53 (282), 457-481.
[7]	Kaso, A. W., Agero, G., Hurissa, Z., Kaso, T., Ewune, H. A., Hareru, H. E., & Hailu, A. (2022). Survival analysis of COVID-19 patients in Ethiopia: a hospital-based study. Plos one, 17 (5), e0268280.
[8]	Mbae, N. (2020). COVID-19 in Kenya. Electronic Journal of General Medicine, 17 (6).
[9]	Salinas-Escudero, G., Carrillo-Vega, M. F., Granados-García, V., Martínez-Valverde, S., Toledano-Toledano, F., & Garduño-Espinosa, J. (2020). A survival analysis of COVID-19 in the Mexican population. BMC public health, 20 (1), 1-8.
[10]	Sam-Agudu, N. A., Quakyi, N. K., Masekela, R., Zumla, A., & Nachega, J. B. (2022). Children and adolescents in African countries should also be vaccinated for COVID- 19. BMJ global health, 7 (2), e008315.
[11]	Schoenfeld, D. (1982). Partial residuals for the proportional hazards regression model. Biometrika, 69 (1), 239-241.
[12]	Shah, S. G. S., & Farrow, A. (2020). A commentary on World Health Organization declares global emergency: A review of the 2019 novel Coronavirus (COVID-19)? International journal of surgery (London, England), 76, 128.
[13]	Sousa, G. J. B., Garces, T. S., Cestari, V. R. F., Florêncio, R. S., Moreira, T. M. M., & Pereira, M. L. D. (2020). Mortality and survival of COVID-19. Epidemiology & Infection, 148.
[14]	World Health Organization. (2023, August 2). “WHO official COVID-19 information.”
[15]	Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., ... & Tan, W. (2020). A novel coronavirus from patients with pneumonia in China, 2019. New England journal of medicine, 382 (8), 727-733.

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APA Style

Roseline Achieng Oburu, Joseph Eyang’an Esekon, Martin Mutwiri Kithinji. (2023). Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital. American Journal of Theoretical and Applied Statistics, 12(5), 103-109. https://doi.org/10.11648/j.ajtas.20231205.11

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ACS Style

Roseline Achieng Oburu; Joseph Eyang’an Esekon; Martin Mutwiri Kithinji. Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital. Am. J. Theor. Appl. Stat. 2023, 12(5), 103-109. doi: 10.11648/j.ajtas.20231205.11

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AMA Style

Roseline Achieng Oburu, Joseph Eyang’an Esekon, Martin Mutwiri Kithinji. Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital. Am J Theor Appl Stat. 2023;12(5):103-109. doi: 10.11648/j.ajtas.20231205.11

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@article{10.11648/j.ajtas.20231205.11,
  author = {Roseline Achieng Oburu and Joseph Eyang’an Esekon and Martin Mutwiri Kithinji},
  title = {Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {12},
  number = {5},
  pages = {103-109},
  doi = {10.11648/j.ajtas.20231205.11},
  url = {https://doi.org/10.11648/j.ajtas.20231205.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20231205.11},
  abstract = {COVID-19 is an infectious disease caused by the novel coronavirus: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The disease quickly spread, resulting in an epidemic in China and a number of cases in other countries around the world. This led to inconsistent health conditions and caused unceasing loss of human lives. Globally, the current COVID-19 pandemic posed a significant and imminent threat to healthcare systems, including Kenya, in terms of patient triage and allocation of limited resources. In this study we analyze time to recovery of the COVID-19 patients at AIC Kijabe hospital. A retrospective cohort study was used to review the existing medical records of 66 patients who tested positive for COVID-19 at AIC Kijabe Hospital. Kaplan-Meier curves were used in determining the probability of recovery. For statistical comparison of the survival curves, Log-rank test statistic was used while Cox proportional hazards model was used to investigate the relation between time to recovery and the predictor variables. Results showed that female patients recovered faster than male patients while there was no significant difference between the survival curves for gender and marital status among the COVID-19 patients. In the Cox proportional hazards model, only age was significant with a p - value (0.0463) and therefore affected the time to recovery of the COVID-19 patients while the rest of the variables, gender and marital status were not significant. In conclusion, age was the only variable that had an effect on the time to recovery of COVID-19 patients.},
 year = {2023}
}

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TY  - JOUR
T1  - Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital
AU  - Roseline Achieng Oburu
AU  - Joseph Eyang’an Esekon
AU  - Martin Mutwiri Kithinji
Y1  - 2023/09/12
PY  - 2023
N1  - https://doi.org/10.11648/j.ajtas.20231205.11
DO  - 10.11648/j.ajtas.20231205.11
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 103
EP  - 109
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20231205.11
AB  - COVID-19 is an infectious disease caused by the novel coronavirus: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The disease quickly spread, resulting in an epidemic in China and a number of cases in other countries around the world. This led to inconsistent health conditions and caused unceasing loss of human lives. Globally, the current COVID-19 pandemic posed a significant and imminent threat to healthcare systems, including Kenya, in terms of patient triage and allocation of limited resources. In this study we analyze time to recovery of the COVID-19 patients at AIC Kijabe hospital. A retrospective cohort study was used to review the existing medical records of 66 patients who tested positive for COVID-19 at AIC Kijabe Hospital. Kaplan-Meier curves were used in determining the probability of recovery. For statistical comparison of the survival curves, Log-rank test statistic was used while Cox proportional hazards model was used to investigate the relation between time to recovery and the predictor variables. Results showed that female patients recovered faster than male patients while there was no significant difference between the survival curves for gender and marital status among the COVID-19 patients. In the Cox proportional hazards model, only age was significant with a p - value (0.0463) and therefore affected the time to recovery of the COVID-19 patients while the rest of the variables, gender and marital status were not significant. In conclusion, age was the only variable that had an effect on the time to recovery of COVID-19 patients.
VL  - 12
IS  - 5
ER  -

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Author Information

Roseline Achieng Oburu

Department of Pure and Applied Sciences, School of Pure and Applied Sciences, Kirinyaga University, Kerugoya, Kenya
Joseph Eyang’an Esekon

Department of Pure and Applied Sciences, School of Pure and Applied Sciences, Kirinyaga University, Kerugoya, Kenya
Martin Mutwiri Kithinji

Department of Pure and Applied Sciences, School of Pure and Applied Sciences, Kirinyaga University, Kerugoya, Kenya

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APA Style

Roseline Achieng Oburu, Joseph Eyang’an Esekon, Martin Mutwiri Kithinji. (2023). Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital. American Journal of Theoretical and Applied Statistics, 12(5), 103-109. https://doi.org/10.11648/j.ajtas.20231205.11

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ACS Style

Roseline Achieng Oburu; Joseph Eyang’an Esekon; Martin Mutwiri Kithinji. Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital. Am. J. Theor. Appl. Stat. 2023, 12(5), 103-109. doi: 10.11648/j.ajtas.20231205.11

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AMA Style

Roseline Achieng Oburu, Joseph Eyang’an Esekon, Martin Mutwiri Kithinji. Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital. Am J Theor Appl Stat. 2023;12(5):103-109. doi: 10.11648/j.ajtas.20231205.11

Copy | Download

@article{10.11648/j.ajtas.20231205.11,
  author = {Roseline Achieng Oburu and Joseph Eyang’an Esekon and Martin Mutwiri Kithinji},
  title = {Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {12},
  number = {5},
  pages = {103-109},
  doi = {10.11648/j.ajtas.20231205.11},
  url = {https://doi.org/10.11648/j.ajtas.20231205.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20231205.11},
  abstract = {COVID-19 is an infectious disease caused by the novel coronavirus: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The disease quickly spread, resulting in an epidemic in China and a number of cases in other countries around the world. This led to inconsistent health conditions and caused unceasing loss of human lives. Globally, the current COVID-19 pandemic posed a significant and imminent threat to healthcare systems, including Kenya, in terms of patient triage and allocation of limited resources. In this study we analyze time to recovery of the COVID-19 patients at AIC Kijabe hospital. A retrospective cohort study was used to review the existing medical records of 66 patients who tested positive for COVID-19 at AIC Kijabe Hospital. Kaplan-Meier curves were used in determining the probability of recovery. For statistical comparison of the survival curves, Log-rank test statistic was used while Cox proportional hazards model was used to investigate the relation between time to recovery and the predictor variables. Results showed that female patients recovered faster than male patients while there was no significant difference between the survival curves for gender and marital status among the COVID-19 patients. In the Cox proportional hazards model, only age was significant with a p - value (0.0463) and therefore affected the time to recovery of the COVID-19 patients while the rest of the variables, gender and marital status were not significant. In conclusion, age was the only variable that had an effect on the time to recovery of COVID-19 patients.},
 year = {2023}
}

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TY  - JOUR
T1  - Survival Analysis of COVID-19 Patients: A Case Study of AIC Kijabe Hospital
AU  - Roseline Achieng Oburu
AU  - Joseph Eyang’an Esekon
AU  - Martin Mutwiri Kithinji
Y1  - 2023/09/12
PY  - 2023
N1  - https://doi.org/10.11648/j.ajtas.20231205.11
DO  - 10.11648/j.ajtas.20231205.11
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 103
EP  - 109
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20231205.11
AB  - COVID-19 is an infectious disease caused by the novel coronavirus: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The disease quickly spread, resulting in an epidemic in China and a number of cases in other countries around the world. This led to inconsistent health conditions and caused unceasing loss of human lives. Globally, the current COVID-19 pandemic posed a significant and imminent threat to healthcare systems, including Kenya, in terms of patient triage and allocation of limited resources. In this study we analyze time to recovery of the COVID-19 patients at AIC Kijabe hospital. A retrospective cohort study was used to review the existing medical records of 66 patients who tested positive for COVID-19 at AIC Kijabe Hospital. Kaplan-Meier curves were used in determining the probability of recovery. For statistical comparison of the survival curves, Log-rank test statistic was used while Cox proportional hazards model was used to investigate the relation between time to recovery and the predictor variables. Results showed that female patients recovered faster than male patients while there was no significant difference between the survival curves for gender and marital status among the COVID-19 patients. In the Cox proportional hazards model, only age was significant with a p - value (0.0463) and therefore affected the time to recovery of the COVID-19 patients while the rest of the variables, gender and marital status were not significant. In conclusion, age was the only variable that had an effect on the time to recovery of COVID-19 patients.
VL  - 12
IS  - 5
ER  -

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