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- Title
Diseases maps of spatial epidemiological data by R.
- Authors
Kubota, Takafumi
- Abstract
Disease maps are essential when analyzing spatial epidemiological data, such as newly detected COVID‐19 positive cases or suicide deaths, because it is necessary to determine the method of analysis in order to perform spatial statistical analysis. Disease maps give an initial overview of the data and provide evidence of regional trends, which the analyst can check. Therefore, in this article, the author aimed to use R, a statistical data analysis tool, to draw spatial epidemiological data in the form of disease maps. This article presents three different methods and analyzes recent trends in COVID‐19 and suicide mortality. The author used monthly data from April, July, and October 2020. The results showed no significant trend in April, but some prefectures showed a negative correlation in July. On the other hand, some prefectures showed a positive correlation in October, confirming the influence of COVID‐19 on suicide by region. This article is categorized under:Statistical and Graphical Methods of Data Analysis > Statistical Graphics and Visualization
- Subjects
DISEASE mapping; COVID-19 pandemic; SUICIDE; COVID-19; STATISTICS
- Publication
WIREs: Computational Statistics, 2023, Vol 15, Issue 4, p1
- ISSN
1939-5108
- Publication type
Article
- DOI
10.1002/wics.1604