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Statistical analysis and visualization of the potential cases of pandemic coronavirus.
Virusdisease. 2020 Jun; 31(2):204-208.V

Abstract

A local outbreak of initially unknown cause pneumonia was detected in Wuhan (Hubei, China) in December 2019 and a novel coronavirus, the severe acute respiratory syndrome coronavirus 2, was quickly found to be causing it. Since then, the epidemic has spread to all of China's mainland provinces as well as 58 other countries and territories, with more than 87,137 confirmed cases around the globe, including 79,968 from China, 7169 from other countries as of 1 March 2020, as stated by the World Health Organization in the COVID-19 situation report-41. In response to this current public health emergency, this study done a statistical analysis and visualized reported cases of coronavirus disease 2019 (COVID-19) based on the open data collection provided by Johns Hopkins University. Where the location and number of confirmed infected cases have been shown, there have also been deaths, recovered cases and comparisons of the growth rates between the Globe countries. This was intended to provide researchers, public health officials and the general public with exposure to the epidemic.

Authors+Show Affiliations

Department of Computer Applications, Dr. Mahalingam College of Engineering and Technology, Anna University, Coimbatore, Tamil Nadu India.Department of Mathematics, P.A. College of Engineering and Technology, Anna University, Coimbatore, Tamil Nadu India.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32656312

Citation

Muthusami, R, and K Saritha. "Statistical Analysis and Visualization of the Potential Cases of Pandemic Coronavirus." Virusdisease, vol. 31, no. 2, 2020, pp. 204-208.
Muthusami R, Saritha K. Statistical analysis and visualization of the potential cases of pandemic coronavirus. Virusdisease. 2020;31(2):204-208.
Muthusami, R., & Saritha, K. (2020). Statistical analysis and visualization of the potential cases of pandemic coronavirus. Virusdisease, 31(2), 204-208. https://doi.org/10.1007/s13337-020-00610-1
Muthusami R, Saritha K. Statistical Analysis and Visualization of the Potential Cases of Pandemic Coronavirus. Virusdisease. 2020;31(2):204-208. PubMed PMID: 32656312.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Statistical analysis and visualization of the potential cases of pandemic coronavirus. AU - Muthusami,R, AU - Saritha,K, Y1 - 2020/06/10/ PY - 2020/04/24/received PY - 2020/05/26/accepted PY - 2020/7/14/entrez PY - 2020/7/14/pubmed PY - 2020/7/14/medline KW - COVID-19 KW - Coronavirus KW - Statistical analysis KW - Visual data analysis SP - 204 EP - 208 JF - Virusdisease JO - Virusdisease VL - 31 IS - 2 N2 - A local outbreak of initially unknown cause pneumonia was detected in Wuhan (Hubei, China) in December 2019 and a novel coronavirus, the severe acute respiratory syndrome coronavirus 2, was quickly found to be causing it. Since then, the epidemic has spread to all of China's mainland provinces as well as 58 other countries and territories, with more than 87,137 confirmed cases around the globe, including 79,968 from China, 7169 from other countries as of 1 March 2020, as stated by the World Health Organization in the COVID-19 situation report-41. In response to this current public health emergency, this study done a statistical analysis and visualized reported cases of coronavirus disease 2019 (COVID-19) based on the open data collection provided by Johns Hopkins University. Where the location and number of confirmed infected cases have been shown, there have also been deaths, recovered cases and comparisons of the growth rates between the Globe countries. This was intended to provide researchers, public health officials and the general public with exposure to the epidemic. SN - 2347-3584 UR - https://www.unboundmedicine.com/medline/citation/32656312/Statistical_analysis_and_visualization_of_the_potential_cases_of_pandemic_coronavirus_ L2 - https://dx.doi.org/10.1007/s13337-020-00610-1 DB - PRIME DP - Unbound Medicine ER -
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