Estimation of Hazard Cumulative Function Using the Nelson-Aalen Method on Covid-19 Patient Data in Jember Regency

The Covid-19 pandemic presents a major challenge in the health sector, especially related to understanding patient recovery patterns. This study aims to estimate the cumulative hazard function using the Nelson-Aalen method on the length of treatment data of Covid-19 patients who have recovered in Jember Regency. The Nelson-Aalen method is a non-parametric approach that does not require certain distribution assumptions and is suitable for survival data, especially those subjected to right censorship. In this study, all patient data was complete without sensors. The analysis was performed with R software, resulting in a cumulative hazard curve that showed an increased risk of recovery as the treatment time increased. The results of this study provide an empirical picture of patient recovery patterns and serve as a basis for evaluating health service efficiency and hospital capacity planning during the pandemic. In addition, the application of the Nelson-Aalen method reinforces the contribution of non-parametric statistical methods in epidemiological studies

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Publication Details

Journal
Indonesian Council of Premier Statistical Science.
Published
2025-06-22
DOI
https://doi.org/10.24014/icopss.v4i1.37519
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Estimation of Hazard Cumulative Function Using the Nelson-Aalen Method on Covid-19 Patient Data in Jember Regency

Hilvania Ramadhani, Rini Pauziah
Indonesian Council of Premier Statistical Science.
Data Mining and Machine Learning Applications
article

Estimation of Hazard Cumulative Function Using the Nelson-Aalen Method on Covid-19 Patient Data in Jember Regency

Hilvania Ramadhani, Rini Pauziah
article en

Abstract

The Covid-19 pandemic presents a major challenge in the health sector, especially related to understanding patient recovery patterns. This study aims to estimate the cumulative hazard function using the Nelson-Aalen method on the length of treatment data of Covid-19 patients who have recovered in Jember Regency. The Nelson-Aalen method is a non-parametric approach that does not require certain distribution assumptions and is suitable for survival data, especially those subjected to right censorship. In this study, all patient data was complete without sensors. The analysis was performed with R software, resulting in a cumulative hazard curve that showed an increased risk of recovery as the treatment time increased. The results of this study provide an empirical picture of patient recovery patterns and serve as a basis for evaluating health service efficiency and hospital capacity planning during the pandemic. In addition, the application of the Nelson-Aalen method reinforces the contribution of non-parametric statistical methods in epidemiological studies

Indonesian Council of Premier Statistical Science.Vol. 4(1)
Universitas Islam Negeri Sultan Syarif Kasim Riau (ID)
Openalex Percentile: Top 62%
Data Mining and Machine Learning Applications
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Estimation of Hazard Cumulative Function Using the Nelson-Aalen Method on Covid-19 Patient Data in Jember Regency — Hilvania Ramadhani, Rini Pauziah · Indonesian Council of Premier Statistical Science. (2025) | TGRS Research Map | TGRS