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Determining the Case Fatality Rate of COVID-19 in Italy: Novel Epidemiological Study.
Yan, Mengqing; Kang, Wenjun; Guo, Zhifeng; Wang, Qi; Wang, Peizhong Peter; Zhu, Yun; Yang, Yongli; Wang, Wei.
Afiliação
  • Yan M; Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Kang W; The Key Laboratory of Nanomedicine and Health Inspection of Zhengzhou, Zhengzhou, China.
  • Guo Z; Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Wang Q; The Key Laboratory of Nanomedicine and Health Inspection of Zhengzhou, Zhengzhou, China.
  • Wang PP; Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Zhu Y; The Key Laboratory of Nanomedicine and Health Inspection of Zhengzhou, Zhengzhou, China.
  • Yang Y; Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Wang W; Center for New Immigrant Wellbeing, Markham, ON, Canada.
JMIR Public Health Surveill ; 8(2): e32638, 2022 02 10.
Article em En | MEDLINE | ID: mdl-34963659
ABSTRACT

BACKGROUND:

COVID-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).

OBJECTIVE:

The 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.

METHODS:

We 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.

RESULTS:

We 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%.

CONCLUSIONS:

We 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Observational_studies Limite: Humans País/Região como assunto: America do norte / Europa Idioma: En Revista: JMIR Public Health Surveill Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Observational_studies Limite: Humans País/Região como assunto: America do norte / Europa Idioma: En Revista: JMIR Public Health Surveill Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China