Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides

African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used...

Full description

Saved in:
Bibliographic Details
Published in:Scientific reports 2022-03, Vol.12 (1), p.3910-3910, Article 3910
Main Authors: Gao, Shan, Zeng, Zan, Wang, HaoNing, Chen, FangYuan, Huang, LiYa, Wang, XiaoLong
Format: Article
Language:English
Subjects:
631/158
692/699
African horse sickness
African Horse Sickness - epidemiology
African Horse Sickness Virus
Animals
Border stations
Ceratopogonidae
China - epidemiology
Climate
Climate change
Culicoides
Ecosystem
Entropy
Epidemics
Habitats
Horses
Humanities and Social Sciences
Infectious diseases
Insect Vectors
Maximum entropy
multidisciplinary
National security
Risk analysis
Risk Assessment
Science
Science (multidisciplinary)
Spatial analysis
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-c540t-2372d0eea89a9d7ac7f37ac3ebae62cbc54d7d70db3fc4e716db5c0d6e907f593
cites cdi_FETCH-LOGICAL-c540t-2372d0eea89a9d7ac7f37ac3ebae62cbc54d7d70db3fc4e716db5c0d6e907f593
container_end_page 3910
container_issue 1
container_start_page 3910
container_title Scientific reports
container_volume 12
creator Gao, Shan
Zeng, Zan
Wang, HaoNing
Chen, FangYuan
Huang, LiYa
Wang, XiaoLong
description African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used to model AHS and Culicoides separately by using climate and non-climate variables. The least cost path (LCP) method was used to analyze the habitat connectivity of Culicoides with the reclassified land cover and altitude as cost factors. The models showed the mean area under the curve as 0.918 and 0.964 for AHS and Culicoides . The prediction result map shows that there is a high risk area in the southern part of China while the habitats of the Culicoides are connected to each other. Therefore, the risk of introducing AHS into China is high and control of the border area should be strengthened immediately.
doi_str_mv 10.1038/s41598-022-07512-w
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_5a0958459ee443fe9913757fb58318cf</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_5a0958459ee443fe9913757fb58318cf</doaj_id><sourcerecordid>2637832482</sourcerecordid><originalsourceid>FETCH-LOGICAL-c540t-2372d0eea89a9d7ac7f37ac3ebae62cbc54d7d70db3fc4e716db5c0d6e907f593</originalsourceid><addsrcrecordid>eNp9kstu1DAUhiMEolXpC7BAltiURcCXOI43SKNRoZUqgQSsLcc-mXiasQc7aTUPwvvimQylZYEXvv7ns8_xXxSvCX5PMGs-pIpw2ZSY0hILTmh5_6w4pbjiJWWUPn80PynOU1rj3DiVFZEvixPGqWCUkNPi19cI1pnR-RUae0DbkJJr3eDGHQodWnTRGe1RH2IClJy59ZASulhcfXuHnB9jsFMODn6_CGjZO6_RlPa0tNWj0wOKLt0i7fWwSy7liUW9bt2oR2SC95Cj746XLafBmeAspFfFi04PCc6P41nx49Pl9-VVefPl8_VycVMaXuExZyeoxQC6kVpaoY3oWO4ZtBpqatqsssIKbFvWmQoEqW3LDbY1SCw6LtlZcT1zbdBrtY1uo-NOBe3UYSPEldJxdGYAxTWWvKm4BKgq1oGUhAkuupY3jDSmy6yPM2s7tRuwBnJ19PAE-vTEu16twp1qMqmucQZcHAEx_JwgjWrjkoFh0B7ClBStWSOowLjK0rf_SNdhirnGB5VoGK0amlV0VpmYfzVC9_AYgtXeRGo2kcomUgcTqfsc9OZxGg8hfyyTBWwWpHzkVxD_3v0f7G9THtZV</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2637832482</pqid></control><display><type>article</type><title>Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides</title><source>PubMed (Medline)</source><source>Publicly Available Content Database</source><source>Full-Text Journals in Chemistry (Open access)</source><source>Springer Nature - nature.com Journals - Fully Open Access</source><creator>Gao, Shan ; Zeng, Zan ; Wang, HaoNing ; Chen, FangYuan ; Huang, LiYa ; Wang, XiaoLong</creator><creatorcontrib>Gao, Shan ; Zeng, Zan ; Wang, HaoNing ; Chen, FangYuan ; Huang, LiYa ; Wang, XiaoLong</creatorcontrib><description>African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used to model AHS and Culicoides separately by using climate and non-climate variables. The least cost path (LCP) method was used to analyze the habitat connectivity of Culicoides with the reclassified land cover and altitude as cost factors. The models showed the mean area under the curve as 0.918 and 0.964 for AHS and Culicoides . The prediction result map shows that there is a high risk area in the southern part of China while the habitats of the Culicoides are connected to each other. Therefore, the risk of introducing AHS into China is high and control of the border area should be strengthened immediately.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-022-07512-w</identifier><identifier>PMID: 35273211</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/158 ; 692/699 ; African horse sickness ; African Horse Sickness - epidemiology ; African Horse Sickness Virus ; Animals ; Border stations ; Ceratopogonidae ; China - epidemiology ; Climate ; Climate change ; Culicoides ; Ecosystem ; Entropy ; Epidemics ; Habitats ; Horses ; Humanities and Social Sciences ; Infectious diseases ; Insect Vectors ; Maximum entropy ; multidisciplinary ; National security ; Risk analysis ; Risk Assessment ; Science ; Science (multidisciplinary) ; Spatial analysis</subject><ispartof>Scientific reports, 2022-03, Vol.12 (1), p.3910-3910, Article 3910</ispartof><rights>The Author(s) 2022</rights><rights>2022. The Author(s).</rights><rights>The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c540t-2372d0eea89a9d7ac7f37ac3ebae62cbc54d7d70db3fc4e716db5c0d6e907f593</citedby><cites>FETCH-LOGICAL-c540t-2372d0eea89a9d7ac7f37ac3ebae62cbc54d7d70db3fc4e716db5c0d6e907f593</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2637832482/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2637832482?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,74998</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35273211$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gao, Shan</creatorcontrib><creatorcontrib>Zeng, Zan</creatorcontrib><creatorcontrib>Wang, HaoNing</creatorcontrib><creatorcontrib>Chen, FangYuan</creatorcontrib><creatorcontrib>Huang, LiYa</creatorcontrib><creatorcontrib>Wang, XiaoLong</creatorcontrib><title>Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used to model AHS and Culicoides separately by using climate and non-climate variables. The least cost path (LCP) method was used to analyze the habitat connectivity of Culicoides with the reclassified land cover and altitude as cost factors. The models showed the mean area under the curve as 0.918 and 0.964 for AHS and Culicoides . The prediction result map shows that there is a high risk area in the southern part of China while the habitats of the Culicoides are connected to each other. Therefore, the risk of introducing AHS into China is high and control of the border area should be strengthened immediately.</description><subject>631/158</subject><subject>692/699</subject><subject>African horse sickness</subject><subject>African Horse Sickness - epidemiology</subject><subject>African Horse Sickness Virus</subject><subject>Animals</subject><subject>Border stations</subject><subject>Ceratopogonidae</subject><subject>China - epidemiology</subject><subject>Climate</subject><subject>Climate change</subject><subject>Culicoides</subject><subject>Ecosystem</subject><subject>Entropy</subject><subject>Epidemics</subject><subject>Habitats</subject><subject>Horses</subject><subject>Humanities and Social Sciences</subject><subject>Infectious diseases</subject><subject>Insect Vectors</subject><subject>Maximum entropy</subject><subject>multidisciplinary</subject><subject>National security</subject><subject>Risk analysis</subject><subject>Risk Assessment</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><subject>Spatial analysis</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kstu1DAUhiMEolXpC7BAltiURcCXOI43SKNRoZUqgQSsLcc-mXiasQc7aTUPwvvimQylZYEXvv7ns8_xXxSvCX5PMGs-pIpw2ZSY0hILTmh5_6w4pbjiJWWUPn80PynOU1rj3DiVFZEvixPGqWCUkNPi19cI1pnR-RUae0DbkJJr3eDGHQodWnTRGe1RH2IClJy59ZASulhcfXuHnB9jsFMODn6_CGjZO6_RlPa0tNWj0wOKLt0i7fWwSy7liUW9bt2oR2SC95Cj746XLafBmeAspFfFi04PCc6P41nx49Pl9-VVefPl8_VycVMaXuExZyeoxQC6kVpaoY3oWO4ZtBpqatqsssIKbFvWmQoEqW3LDbY1SCw6LtlZcT1zbdBrtY1uo-NOBe3UYSPEldJxdGYAxTWWvKm4BKgq1oGUhAkuupY3jDSmy6yPM2s7tRuwBnJ19PAE-vTEu16twp1qMqmucQZcHAEx_JwgjWrjkoFh0B7ClBStWSOowLjK0rf_SNdhirnGB5VoGK0amlV0VpmYfzVC9_AYgtXeRGo2kcomUgcTqfsc9OZxGg8hfyyTBWwWpHzkVxD_3v0f7G9THtZV</recordid><startdate>20220310</startdate><enddate>20220310</enddate><creator>Gao, Shan</creator><creator>Zeng, Zan</creator><creator>Wang, HaoNing</creator><creator>Chen, FangYuan</creator><creator>Huang, LiYa</creator><creator>Wang, XiaoLong</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><general>Nature Portfolio</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20220310</creationdate><title>Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides</title><author>Gao, Shan ; Zeng, Zan ; Wang, HaoNing ; Chen, FangYuan ; Huang, LiYa ; Wang, XiaoLong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c540t-2372d0eea89a9d7ac7f37ac3ebae62cbc54d7d70db3fc4e716db5c0d6e907f593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>631/158</topic><topic>692/699</topic><topic>African horse sickness</topic><topic>African Horse Sickness - epidemiology</topic><topic>African Horse Sickness Virus</topic><topic>Animals</topic><topic>Border stations</topic><topic>Ceratopogonidae</topic><topic>China - epidemiology</topic><topic>Climate</topic><topic>Climate change</topic><topic>Culicoides</topic><topic>Ecosystem</topic><topic>Entropy</topic><topic>Epidemics</topic><topic>Habitats</topic><topic>Horses</topic><topic>Humanities and Social Sciences</topic><topic>Infectious diseases</topic><topic>Insect Vectors</topic><topic>Maximum entropy</topic><topic>multidisciplinary</topic><topic>National security</topic><topic>Risk analysis</topic><topic>Risk Assessment</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><topic>Spatial analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gao, Shan</creatorcontrib><creatorcontrib>Zeng, Zan</creatorcontrib><creatorcontrib>Wang, HaoNing</creatorcontrib><creatorcontrib>Chen, FangYuan</creatorcontrib><creatorcontrib>Huang, LiYa</creatorcontrib><creatorcontrib>Wang, XiaoLong</creatorcontrib><collection>SpringerOpen</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Biological Sciences</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Science Journals</collection><collection>Biological Science Database</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 Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gao, Shan</au><au>Zeng, Zan</au><au>Wang, HaoNing</au><au>Chen, FangYuan</au><au>Huang, LiYa</au><au>Wang, XiaoLong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2022-03-10</date><risdate>2022</risdate><volume>12</volume><issue>1</issue><spage>3910</spage><epage>3910</epage><pages>3910-3910</pages><artnum>3910</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used to model AHS and Culicoides separately by using climate and non-climate variables. The least cost path (LCP) method was used to analyze the habitat connectivity of Culicoides with the reclassified land cover and altitude as cost factors. The models showed the mean area under the curve as 0.918 and 0.964 for AHS and Culicoides . The prediction result map shows that there is a high risk area in the southern part of China while the habitats of the Culicoides are connected to each other. Therefore, the risk of introducing AHS into China is high and control of the border area should be strengthened immediately.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>35273211</pmid><doi>10.1038/s41598-022-07512-w</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2045-2322
ispartof Scientific reports, 2022-03, Vol.12 (1), p.3910-3910, Article 3910
issn 2045-2322
2045-2322
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_5a0958459ee443fe9913757fb58318cf
source PubMed (Medline); Publicly Available Content Database; Full-Text Journals in Chemistry (Open access); Springer Nature - nature.com Journals - Fully Open Access
subjects 631/158
692/699
African horse sickness
African Horse Sickness - epidemiology
African Horse Sickness Virus
Animals
Border stations
Ceratopogonidae
China - epidemiology
Climate
Climate change
Culicoides
Ecosystem
Entropy
Epidemics
Habitats
Horses
Humanities and Social Sciences
Infectious diseases
Insect Vectors
Maximum entropy
multidisciplinary
National security
Risk analysis
Risk Assessment
Science
Science (multidisciplinary)
Spatial analysis
title Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T20%3A53%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Predicting%20the%20possibility%20of%20African%20horse%20sickness%20(AHS)%20introduction%20into%20China%20using%20spatial%20risk%20analysis%20and%20habitat%20connectivity%20of%20Culicoides&rft.jtitle=Scientific%20reports&rft.au=Gao,%20Shan&rft.date=2022-03-10&rft.volume=12&rft.issue=1&rft.spage=3910&rft.epage=3910&rft.pages=3910-3910&rft.artnum=3910&rft.issn=2045-2322&rft.eissn=2045-2322&rft_id=info:doi/10.1038/s41598-022-07512-w&rft_dat=%3Cproquest_doaj_%3E2637832482%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c540t-2372d0eea89a9d7ac7f37ac3ebae62cbc54d7d70db3fc4e716db5c0d6e907f593%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2637832482&rft_id=info:pmid/35273211&rfr_iscdi=true