COVID-19 Infection Structure Analysis Based on Minimum Spanning Tree Visualization in the Kingdom of Saudi Arabia Regions

This work aims to study the extent of the association between the numbers of COVID-19 infections among the regions of Saudi Arabia using a graph theory, especially the calculation of the minimum spanning tree. The research also aims mainly to classify the central regions of Saudi Arabia, whose numbe...

Full description

Saved in:
Bibliographic Details
Published in:Journal of chemistry 2022-07, Vol.2022, p.1-8
Main Authors: Alsulami, Samirah H., Bayati, Jalal H.
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Cities
Coronaviruses
COVID-19
Graph theory
Health aspects
Infection
Infections
Structural analysis
Viral diseases
Virus diseases
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c470t-8bc20fee7bd0d3372350a79532df2b8159d775d3b6cb71484e547612c89c35fd3
cites cdi_FETCH-LOGICAL-c470t-8bc20fee7bd0d3372350a79532df2b8159d775d3b6cb71484e547612c89c35fd3
container_end_page 8
container_issue
container_start_page 1
container_title Journal of chemistry
container_volume 2022
creator Alsulami, Samirah H.
Bayati, Jalal H.
description This work aims to study the extent of the association between the numbers of COVID-19 infections among the regions of Saudi Arabia using a graph theory, especially the calculation of the minimum spanning tree. The research also aims mainly to classify the central regions of Saudi Arabia, whose number of COVID-19 virus infections is centrally linked to other provinces, i.e., when the number of infections in these central regions increases, the number of infections in the associated regions increases and when infections decrease in these central regions, infections decrease in the associated regions.
doi_str_mv 10.1155/2022/1726286
format article
fullrecord <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_892750328bc642f19f35e6a22ed77320</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A814825044</galeid><doaj_id>oai_doaj_org_article_892750328bc642f19f35e6a22ed77320</doaj_id><sourcerecordid>A814825044</sourcerecordid><originalsourceid>FETCH-LOGICAL-c470t-8bc20fee7bd0d3372350a79532df2b8159d775d3b6cb71484e547612c89c35fd3</originalsourceid><addsrcrecordid>eNp9kk1vGyEQhldVKzVKc-sPQOqx3QSGZVmOrpsmVhNFqtNcEcuHg-UFF3ZVOb8-OI5SVYoKB0Yzz_sOoKmqjwSfEsLYGWCAM8Khha59Ux0BFrgWmJO3L3FL31cnOa9xWV1HGfCjaje_uVt8q4lAi-CsHn0MaDmmSY9TsmgW1GaXfUZfVbYGldq1D36YBrTcqhB8WKHbZC2683lSG_-gnvQ-oPHeoh-lbOKAokNLNRmPZkn1XqGfdlWo_KF659Qm25Pn87j69f38dn5ZX91cLOazq1o3HI9112vAzlreG2wo5UAZVlwwCsZB3xEmDOfM0L7VPSdN11jW8JaA7oSmzBl6XC0OviaqtdwmP6i0k1F5-ZSIaSVVGr3eWNkJ4AxTKD3bBhwRjjLbKgBbelDAxevTwWub4u_J5lGu45TKJ2UJrRCsoQ1u_lIrVUx9cHFMSg8-aznryhWB4WZPnb5ClW3s4HUM1vmS_0fw5SDQKeacrHt5DMFyPwJyPwLyeQQK_vmA3_tg1B__f_oReT-sCg</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2699543404</pqid></control><display><type>article</type><title>COVID-19 Infection Structure Analysis Based on Minimum Spanning Tree Visualization in the Kingdom of Saudi Arabia Regions</title><source>Publicly Available Content Database</source><source>Wiley Open Access Journals</source><source>Free Full-Text Journals in Chemistry</source><source>Coronavirus Research Database</source><creator>Alsulami, Samirah H. ; Bayati, Jalal H.</creator><contributor>Shaker, Hani ; Hani Shaker</contributor><creatorcontrib>Alsulami, Samirah H. ; Bayati, Jalal H. ; Shaker, Hani ; Hani Shaker</creatorcontrib><description>This work aims to study the extent of the association between the numbers of COVID-19 infections among the regions of Saudi Arabia using a graph theory, especially the calculation of the minimum spanning tree. The research also aims mainly to classify the central regions of Saudi Arabia, whose number of COVID-19 virus infections is centrally linked to other provinces, i.e., when the number of infections in these central regions increases, the number of infections in the associated regions increases and when infections decrease in these central regions, infections decrease in the associated regions.</description><identifier>ISSN: 2090-9063</identifier><identifier>EISSN: 2090-9071</identifier><identifier>DOI: 10.1155/2022/1726286</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Algorithms ; Analysis ; Cities ; Coronaviruses ; COVID-19 ; Graph theory ; Health aspects ; Infection ; Infections ; Structural analysis ; Viral diseases ; Virus diseases</subject><ispartof>Journal of chemistry, 2022-07, Vol.2022, p.1-8</ispartof><rights>Copyright © 2022 Samirah H. Alsulami and Jalal H. Bayati.</rights><rights>COPYRIGHT 2022 John Wiley &amp; Sons, Inc.</rights><rights>Copyright © 2022 Samirah H. Alsulami and Jalal H. Bayati. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c470t-8bc20fee7bd0d3372350a79532df2b8159d775d3b6cb71484e547612c89c35fd3</citedby><cites>FETCH-LOGICAL-c470t-8bc20fee7bd0d3372350a79532df2b8159d775d3b6cb71484e547612c89c35fd3</cites><orcidid>0000-0001-7493-9609</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2699543404/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2699543404?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,38516,43895,44590,74412,75126</link.rule.ids></links><search><contributor>Shaker, Hani</contributor><contributor>Hani Shaker</contributor><creatorcontrib>Alsulami, Samirah H.</creatorcontrib><creatorcontrib>Bayati, Jalal H.</creatorcontrib><title>COVID-19 Infection Structure Analysis Based on Minimum Spanning Tree Visualization in the Kingdom of Saudi Arabia Regions</title><title>Journal of chemistry</title><description>This work aims to study the extent of the association between the numbers of COVID-19 infections among the regions of Saudi Arabia using a graph theory, especially the calculation of the minimum spanning tree. The research also aims mainly to classify the central regions of Saudi Arabia, whose number of COVID-19 virus infections is centrally linked to other provinces, i.e., when the number of infections in these central regions increases, the number of infections in the associated regions increases and when infections decrease in these central regions, infections decrease in the associated regions.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Cities</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Graph theory</subject><subject>Health aspects</subject><subject>Infection</subject><subject>Infections</subject><subject>Structural analysis</subject><subject>Viral diseases</subject><subject>Virus diseases</subject><issn>2090-9063</issn><issn>2090-9071</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kk1vGyEQhldVKzVKc-sPQOqx3QSGZVmOrpsmVhNFqtNcEcuHg-UFF3ZVOb8-OI5SVYoKB0Yzz_sOoKmqjwSfEsLYGWCAM8Khha59Ux0BFrgWmJO3L3FL31cnOa9xWV1HGfCjaje_uVt8q4lAi-CsHn0MaDmmSY9TsmgW1GaXfUZfVbYGldq1D36YBrTcqhB8WKHbZC2683lSG_-gnvQ-oPHeoh-lbOKAokNLNRmPZkn1XqGfdlWo_KF659Qm25Pn87j69f38dn5ZX91cLOazq1o3HI9112vAzlreG2wo5UAZVlwwCsZB3xEmDOfM0L7VPSdN11jW8JaA7oSmzBl6XC0OviaqtdwmP6i0k1F5-ZSIaSVVGr3eWNkJ4AxTKD3bBhwRjjLbKgBbelDAxevTwWub4u_J5lGu45TKJ2UJrRCsoQ1u_lIrVUx9cHFMSg8-aznryhWB4WZPnb5ClW3s4HUM1vmS_0fw5SDQKeacrHt5DMFyPwJyPwLyeQQK_vmA3_tg1B__f_oReT-sCg</recordid><startdate>20220726</startdate><enddate>20220726</enddate><creator>Alsulami, Samirah H.</creator><creator>Bayati, Jalal H.</creator><general>Hindawi</general><general>John Wiley &amp; Sons, Inc</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>COVID</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>KB.</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7493-9609</orcidid></search><sort><creationdate>20220726</creationdate><title>COVID-19 Infection Structure Analysis Based on Minimum Spanning Tree Visualization in the Kingdom of Saudi Arabia Regions</title><author>Alsulami, Samirah H. ; Bayati, Jalal H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c470t-8bc20fee7bd0d3372350a79532df2b8159d775d3b6cb71484e547612c89c35fd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Cities</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Graph theory</topic><topic>Health aspects</topic><topic>Infection</topic><topic>Infections</topic><topic>Structural analysis</topic><topic>Viral diseases</topic><topic>Virus diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Alsulami, Samirah H.</creatorcontrib><creatorcontrib>Bayati, Jalal H.</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>Materials Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alsulami, Samirah H.</au><au>Bayati, Jalal H.</au><au>Shaker, Hani</au><au>Hani Shaker</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>COVID-19 Infection Structure Analysis Based on Minimum Spanning Tree Visualization in the Kingdom of Saudi Arabia Regions</atitle><jtitle>Journal of chemistry</jtitle><date>2022-07-26</date><risdate>2022</risdate><volume>2022</volume><spage>1</spage><epage>8</epage><pages>1-8</pages><issn>2090-9063</issn><eissn>2090-9071</eissn><abstract>This work aims to study the extent of the association between the numbers of COVID-19 infections among the regions of Saudi Arabia using a graph theory, especially the calculation of the minimum spanning tree. The research also aims mainly to classify the central regions of Saudi Arabia, whose number of COVID-19 virus infections is centrally linked to other provinces, i.e., when the number of infections in these central regions increases, the number of infections in the associated regions increases and when infections decrease in these central regions, infections decrease in the associated regions.</abstract><cop>New York</cop><pub>Hindawi</pub><doi>10.1155/2022/1726286</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-7493-9609</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2090-9063
ispartof Journal of chemistry, 2022-07, Vol.2022, p.1-8
issn 2090-9063
2090-9071
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_892750328bc642f19f35e6a22ed77320
source Publicly Available Content Database; Wiley Open Access Journals; Free Full-Text Journals in Chemistry; Coronavirus Research Database
subjects Algorithms
Analysis
Cities
Coronaviruses
COVID-19
Graph theory
Health aspects
Infection
Infections
Structural analysis
Viral diseases
Virus diseases
title COVID-19 Infection Structure Analysis Based on Minimum Spanning Tree Visualization in the Kingdom of Saudi Arabia Regions
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T20%3A46%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=COVID-19%20Infection%20Structure%20Analysis%20Based%20on%20Minimum%20Spanning%20Tree%20Visualization%20in%20the%20Kingdom%20of%20Saudi%20Arabia%20Regions&rft.jtitle=Journal%20of%20chemistry&rft.au=Alsulami,%20Samirah%20H.&rft.date=2022-07-26&rft.volume=2022&rft.spage=1&rft.epage=8&rft.pages=1-8&rft.issn=2090-9063&rft.eissn=2090-9071&rft_id=info:doi/10.1155/2022/1726286&rft_dat=%3Cgale_doaj_%3EA814825044%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c470t-8bc20fee7bd0d3372350a79532df2b8159d775d3b6cb71484e547612c89c35fd3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2699543404&rft_id=info:pmid/&rft_galeid=A814825044&rfr_iscdi=true