Developing a Probit Regression Model for Estimating the Chance of Mortality for Coronavirus Disease-2019 Patients.
The COVID-19 virus with a rapid human-to-human transmission makes patients experience a variety of symptoms and causes a significant risk to patients who are suffering from weak
immune systems. In this case, the elderly people or those who are suffering from underlying diseases may experience more severely symptoms than the others followed by receiving particular healthcare at the intensive care unit (ICU). This situation leads health authorities to manage medical operations, according to a rough estimation of admitted patients’ mortality rate.
There is a specific statistical method, called probit regression, to estimate the rate of mortality based on data collected for the patients, those have received medical treatment and invention resulted into death or recovered. Therefore, developing a probit regression model would
support health authorities to provide a rough estimation of the mortality chance prior to admission process.
Comparing situations is another research field, where for example the study of the healthcare system forecast and its impact on health costs through linear regression in Colombia showed that long-term treatments are costly for insurers and patients. In terms of application, the results support health authorities to provide an estimation on the rate of mortality before admiration process in hospital. Researchers interested in working in this field are recommended to focus more on the other factors contributing to the immunity of the human system resulted to death or recovery.
Public Health Open J. 2021; 6(2): 62-67. doi: 10.17140/PHOJ-6-160