Estimating the number of ICU patients of COVID-19 by using a simple mathematical model

초록

Predicting the number of ICU patients holds significant importance, serving as a critical aspect in efficiently allocating resources, ensuring high-quality care for critically ill individuals, and implementing effective public health strategies to mitigate the impact of diseases. This research focuses on estimating ICU patient numbers through the development of a simple mathematical model. Utilizing data on confirmed COVID-19 cases and deaths, this model becomes a valuable tool for predicting and managing ICU resource requirements during the ongoing pandemic. By incorporating historical data on infected individuals and fatalities from previous weeks, we establish a straightforward equation. We found the substantial impact of the delay in infected individuals, particularly those occurring more than five weeks earlier, on the accuracy of ICU predictions. Proactively preparing for potential surges in severe cases becomes feasible by forecasting the demand for intensive care beds, ultimately improving patient outcomes and preventing excessive strain on medical facilities.

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