Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Aug 5, 2021
Date Accepted: Dec 28, 2021
Date Submitted to PubMed: Dec 29, 2021
A novel analysis approach to determining the case fatality rate of COVID-19 in Italy
ABSTRACT
Background:
The Coronavirus Disease 2019 (COVID-19), which emerged in December 2019, has spread rapidly around the world and has become a serious public health event endangering human life.
Objective:
The main objective of this study was to explore the value of the discharged case fatality rate (DCFR) in estimating the severity of COVID-19 in Italy.
Methods:
We retrieved the epidemiological data of COVID-19 in Italy published by the John Hopkins Coronavirus Resource Center between 22nd January 2020 and 31st December 2020. The data included the number of daily confirmed cases, daily confirmed deaths, daily recovered cases, and active confirmed cases. We then used the proportion of daily deaths and total deaths to calculate the total discharged case fatality rate (tDCFR), monthly discharged case fatality rate (mDCFR), and stage discharged case fatality rate (sDCFR).
Results:
Results showed that the tDCFR of COVID-19 in Italy was 4.82 (CI: 4.79~4.86) and the mDCFR was 2.57 (CI: 2.53~2.60) by 31st December 2020. Moreover, we used the ArcGIS version 10.7 software to visualize the spatial distribution of epidemic case fatality rate. The obtained map showed the areas with high DCFR values, which indicated that the severity of COVID-19 could be ignored. We then used the Joinpoint Regression Program to analyze the change trend of mDCFR over time, and determined a segmentation point, which divided the epidemic into two stages: the first stage (from January to May) and the second stage (from June to December). Results showed that the sDCFR of the two stages were 17.50 (17.33~17.67) and 3.03 (3.00~3.06), respectively.
Conclusions:
Our findings have shown that the DCFR can be used to assess disease severity and divide pandemic stages of new infectious diseases, analyze its dynamic trend, and explain the control of infectious diseases.
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