Abstract
Background
COVID-19 is the most informative pandemic in history. These unprecedented recorded data give rise to some novel concepts, discussions, and models. Macroscopic modeling of the period of hospitalization is one of these new issues.
Methods
Modeling of the lag between diagnosis and death is done by using two classes of macroscopic analytical methods: the correlation-based methods based on Pearson, Spearman, and Kendall correlation coefficients, and the logarithmic methods of two types. Also, we apply eight weighted average methods to smooth the time series before calculating the distance. We consider five lags with the least distance. All the computations are conducted on Matlab R2015b.
Results
The length of hospitalization for the fatal cases in the USA, Italy, and Germany are 2–10, 1–6, and 5–19 days, respectively. Overall, this length in the USA is two days more than in Italy and five days less than in Germany.
Conclusion
We take the distance between the diagnosis and death as the length of hospitalization. There is a negative association between the length of hospitalization and the case fatality rate. Therefore, the estimation of the length of hospitalization by using these macroscopic mathematical methods can be introduced as an indicator to scale the success of the countries fighting the ongoing pandemic.
Keywords: COVID-19, Length of hospitalization, Logarithmic method, Correlation, Diagnosis, Macroscopic method