Determining the Case Fatality Rate of COVID-19 in Italy: Novel Epidemiological Study

BackgroundCOVID-19, which emerged in December 2019, has spread rapidly around the world and has become a serious public health event endangering human life. With regard to COVID-19, there are still many unknowns, such as the exact case fatality rate (CFR). ObjectiveThe main objective of this study w...

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Main Authors: Mengqing Yan (Author), Wenjun Kang (Author), Zhifeng Guo (Author), Qi Wang (Author), Peizhong Peter Wang (Author), Yun Zhu (Author), Yongli Yang (Author), Wei Wang (Author)
Format: Book
Published: JMIR Publications, 2022-02-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Mengqing Yan  |e author 
700 1 0 |a Wenjun Kang  |e author 
700 1 0 |a Zhifeng Guo  |e author 
700 1 0 |a Qi Wang  |e author 
700 1 0 |a Peizhong Peter Wang  |e author 
700 1 0 |a Yun Zhu  |e author 
700 1 0 |a Yongli Yang  |e author 
700 1 0 |a Wei Wang  |e author 
245 0 0 |a Determining the Case Fatality Rate of COVID-19 in Italy: Novel Epidemiological Study 
260 |b JMIR Publications,   |c 2022-02-01T00:00:00Z. 
500 |a 2369-2960 
500 |a 10.2196/32638 
520 |a BackgroundCOVID-19, which emerged in December 2019, has spread rapidly around the world and has become a serious public health event endangering human life. With regard to COVID-19, there are still many unknowns, such as the exact case fatality rate (CFR). ObjectiveThe main objective of this study was to explore the value of the discharged CFR (DCFR) to make more accurate forecasts of epidemic trends of COVID-19 in Italy. MethodsWe retrieved the epidemiological data of COVID-19 in Italy published by the John Hopkins Coronavirus Resource Center. We then used the proportion of deaths to discharged cases(including deaths and recovered cases) to calculate the total DCFR (tDCFR), monthly DCFR (mDCFR), and stage DCFR (sDCFR). Furthermore, we analyzed the trend in the mDCFR between January and December 2020 using joinpoint regression analysis, used ArcGIS version 10.7 to visualize the spatial distribution of the epidemic CFR, and assigned different colors to each province based on the CFR or tDCFR. ResultsWe calculated the numbers and obtained the new indices of the tDCFR and mDCFR for calculating the fatality rate. The results showed that the tDCFR and mDCFR fluctuated greatly from January to May. They first showed a rapid increase followed by a rapid decline after reaching the peak. The map showed that the provinces with a high tDCFR were Emilia-Romagna, Puglia, and Lombardia. The change trend of the mDCFR over time was divided into the following 2 stages: the first stage (from January to May) and the second stage (from June to December). With regard to worldwide COVID-19 statistics, among 6 selected countries, the United States had the highest tDCFR (4.26%), while the tDCFR of the remaining countries was between 0.98% and 2.72%. ConclusionsWe provide a new perspective for assessing the fatality of COVID-19 in Italy, which can use ever-changing data to calculate a more accurate CFR and scientifically predict the development trend of the epidemic. 
546 |a EN 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n JMIR Public Health and Surveillance, Vol 8, Iss 2, p e32638 (2022) 
787 0 |n https://publichealth.jmir.org/2022/2/e32638 
787 0 |n https://doaj.org/toc/2369-2960 
856 4 1 |u https://doaj.org/article/2cf174c6ebe541e88c52ffda3534fe6f  |z Connect to this object online.