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COVID-19 Mortality Risk Factors Using Survival Analysis: A Case Study of Jakarta, Indonesia
Ieee Transactions on Computational Social Systems ; : 10, 2022.
Article in English | Web of Science | ID: covidwho-1816469
ABSTRACT
At the end of 2021 Q2, coronavirus disease 2019 (COVID-19) in Indonesia experienced a continuous increase in positivity and mortality rates. There are limited studies regarding the factors of COVID-19 mortality in Indonesia with a more balanced dataset. The previous studies only implemented logistic regression, sensitive to the imbalanced dataset. Meanwhile, other countries implemented survival analysis to overcome the problem. Most survival analyses using Cox proportional hazard (CPH) model require the variables to be time-independent. To this end, this study aims to identify the risk factors for COVID-19 mortality in Indonesia using a survival analysis approach using Jakarta as a case study. We use the Piecewise Exponential Model (PEM) to overcome the time-dependent problem in CPH. The findings show that the COVID-19 mortality does not differ the gender. In contrast, it differs the elderly with 3.5 times higher to be deceased. Dyspnea, malaise, and pneumonia are the primary symptoms associated with COVID-19 mortality. From the comorbidities, diabetes and chronic disease are related to COVID-19, while hypertension and heart attack are still considerable in clustered contexts. The advanced treatment using intubation and extra corporeal membrane oxygenation (ECMO) produces a relatively large hazard risk of COVID-19 mortality. Based on the findings, we suggest that collaboration among the government, society, and hospitals is vital in overcoming the COVID-19 pandemic and minimizing the COVID-19 death.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Case report / Prognostic study Language: English Journal: Ieee Transactions on Computational Social Systems Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Case report / Prognostic study Language: English Journal: Ieee Transactions on Computational Social Systems Year: 2022 Document Type: Article