Evidence map›Paper›PMID 34963659›Full record

ArticleJMIR public health and surveillance2022

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

Mengqing Yan, Wenjun Kang, Zhifeng Guo, Qi Wang, Peizhong Peter Wang, Yun Zhu, Yongli Yang, Wei Wang

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Mengqing YanDepartment of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.ORCID 0000-0002-8711-8786
Wenjun KangDepartment of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.ORCID 0000-0003-3893-6835
Zhifeng GuoDepartment of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.ORCID 0000-0001-6890-2519
Qi WangDepartment of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.ORCID 0000-0002-7091-5666
Peizhong Peter WangCenter for New Immigrant Wellbeing, Markham, ON, Canada.ORCID 0000-0002-0682-6861
Yun ZhuDepartment of Epidemiology and Biostatistics, Tianjin Medical University, Tianjin, China.ORCID 0000-0002-5864-0794
Yongli YangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.ORCID 0000-0002-8220-8133
Wei WangDepartment of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China.ORCID 0000-0001-7492-6795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19Epidemiologic StudiesHumansItalySARS-CoV-2United Statescase fatality rateCOVID-19discharged case fatality ratenew infectious diseases

Identifiers

PMID34963659
PMCPMC8834871

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.