The Impact of Human Mobility on HIV Transmission in Kenya
Disease spreads as a result of people moving and coming in contact with each other. Thus the mobility patterns of individuals are crucial in understanding disease dynamics. Here we study the impact of human mobility on HIV transmission in different parts of Kenya. We build an SIR metapopulation mode...
Gespeichert in:
| Veröffentlicht in: | PloS one 2015-11, Vol.10 (11), p.e0142805-e0142805 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e0142805 |
|---|---|
| container_issue | 11 |
| container_start_page | e0142805 |
| container_title | PloS one |
| container_volume | 10 |
| creator | Isdory, Augustino Mureithi, Eunice W Sumpter, David J T |
| description | Disease spreads as a result of people moving and coming in contact with each other. Thus the mobility patterns of individuals are crucial in understanding disease dynamics. Here we study the impact of human mobility on HIV transmission in different parts of Kenya. We build an SIR metapopulation model that incorporates the different regions within the country. We parameterise the model using census data, HIV data and mobile phone data adopted to track human mobility. We found that movement between different regions appears to have a relatively small overall effect on the total increase in HIV cases in Kenya. However, the most important consequence of movement patterns was transmission of the disease from high infection to low prevalence areas. Mobility slightly increases HIV incidence rates in regions with initially low HIV prevalences and slightly decreases incidences in regions with initially high HIV prevalence. We discuss how regional HIV models could be used in public-health planning. This paper is a first attempt to model spread of HIV using mobile phone data, and we also discuss limitations to the approach. |
| doi_str_mv | 10.1371/journal.pone.0142805 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1735911357</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A435602011</galeid><doaj_id>oai_doaj_org_article_cc0aa9c15f004757aa401151a061d48e</doaj_id><sourcerecordid>A435602011</sourcerecordid><originalsourceid>FETCH-LOGICAL-c729t-bbe17e7f4447337a8db1b73bb2880d2312bdad613e095726248308192169f94c3</originalsourceid><addsrcrecordid>eNqNk11v0zAUhiMEYmPwDxBEmoRAosXfjm-QqvHRiqFJUHprOY7TukrsECdA_z1um00N2gXyha3j533tc-yTJM8hmELM4but71unqmnjnZkCSFAG6IPkHAqMJgwB_PBkfZY8CWELAMUZY4-TM8SoEIjz80QsNyZd1I3SXerLdN7XyqVffW4r2-1S79L5YpUuW-VCbUOwMWBd-sW4nXqaPCpVFcyzYb5Ifnz6uLyaT65vPi-uZtcTzZHoJnluIDe8JIRwjLnKihzmHOc5yjJQIAxRXqiCQWyAoBwxRDIMMigQZKIUROOL5OXRt6l8kEPWQUKOqYAQUx6JxZEovNrKprW1anfSKysPAd-upWo7qysjtQZKCQ1pCQDhlCtFAIQUKsBgQTITvd4evcJv0_T5yO2DXc0Obn0vEScY7I9-P1yuz2tTaOO6VlUj1XjH2Y1c-1-SMMoFhtHg9WDQ-p-9CZ2MddamqpQzvj-kyRgXnGURvfwHvb8YA7VWMV_rSh_P1XtTOSOYMoBiwpGa3kPFUZja6vijShvjI8GbkSAynfnTrVUfglx8__b_7M1qzL46YTdGVd0m-Krv4lcLY5AcQd36EFpT3hUZArlviNtqyH1DyKEhouzF6QPdiW47AP8FiYQBhw</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1735911357</pqid></control><display><type>article</type><title>The Impact of Human Mobility on HIV Transmission in Kenya</title><source>MEDLINE</source><source>Public Library of Science</source><source>Full-Text Journals in Chemistry (Open access)</source><source>DOAJ Directory of Open Access Journals</source><source>PubMed Central_</source><source>SWEPUB Freely available online</source><source>EZB Electronic Journals Library</source><creator>Isdory, Augustino ; Mureithi, Eunice W ; Sumpter, David J T</creator><creatorcontrib>Isdory, Augustino ; Mureithi, Eunice W ; Sumpter, David J T</creatorcontrib><description>Disease spreads as a result of people moving and coming in contact with each other. Thus the mobility patterns of individuals are crucial in understanding disease dynamics. Here we study the impact of human mobility on HIV transmission in different parts of Kenya. We build an SIR metapopulation model that incorporates the different regions within the country. We parameterise the model using census data, HIV data and mobile phone data adopted to track human mobility. We found that movement between different regions appears to have a relatively small overall effect on the total increase in HIV cases in Kenya. However, the most important consequence of movement patterns was transmission of the disease from high infection to low prevalence areas. Mobility slightly increases HIV incidence rates in regions with initially low HIV prevalences and slightly decreases incidences in regions with initially high HIV prevalence. We discuss how regional HIV models could be used in public-health planning. This paper is a first attempt to model spread of HIV using mobile phone data, and we also discuss limitations to the approach.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0142805</identifier><identifier>PMID: 26599277</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acquired immune deficiency syndrome ; AIDS ; Cell Phone ; Cell phones ; Complications and side effects ; Disease transmission ; Distribution ; Epidemics ; Health planning ; HIV ; HIV Infections - epidemiology ; HIV Infections - transmission ; HIV Infections - virology ; HIV-1 - pathogenicity ; Human immunodeficiency virus ; Human Migration ; Human motion ; Humans ; Kenya - epidemiology ; Metapopulations ; Mobility ; Models, Theoretical ; Regional planning ; Studies</subject><ispartof>PloS one, 2015-11, Vol.10 (11), p.e0142805-e0142805</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Isdory et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Isdory et al 2015 Isdory et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c729t-bbe17e7f4447337a8db1b73bb2880d2312bdad613e095726248308192169f94c3</citedby><cites>FETCH-LOGICAL-c729t-bbe17e7f4447337a8db1b73bb2880d2312bdad613e095726248308192169f94c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657931/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657931/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,550,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26599277$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-274307$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Isdory, Augustino</creatorcontrib><creatorcontrib>Mureithi, Eunice W</creatorcontrib><creatorcontrib>Sumpter, David J T</creatorcontrib><title>The Impact of Human Mobility on HIV Transmission in Kenya</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Disease spreads as a result of people moving and coming in contact with each other. Thus the mobility patterns of individuals are crucial in understanding disease dynamics. Here we study the impact of human mobility on HIV transmission in different parts of Kenya. We build an SIR metapopulation model that incorporates the different regions within the country. We parameterise the model using census data, HIV data and mobile phone data adopted to track human mobility. We found that movement between different regions appears to have a relatively small overall effect on the total increase in HIV cases in Kenya. However, the most important consequence of movement patterns was transmission of the disease from high infection to low prevalence areas. Mobility slightly increases HIV incidence rates in regions with initially low HIV prevalences and slightly decreases incidences in regions with initially high HIV prevalence. We discuss how regional HIV models could be used in public-health planning. This paper is a first attempt to model spread of HIV using mobile phone data, and we also discuss limitations to the approach.</description><subject>Acquired immune deficiency syndrome</subject><subject>AIDS</subject><subject>Cell Phone</subject><subject>Cell phones</subject><subject>Complications and side effects</subject><subject>Disease transmission</subject><subject>Distribution</subject><subject>Epidemics</subject><subject>Health planning</subject><subject>HIV</subject><subject>HIV Infections - epidemiology</subject><subject>HIV Infections - transmission</subject><subject>HIV Infections - virology</subject><subject>HIV-1 - pathogenicity</subject><subject>Human immunodeficiency virus</subject><subject>Human Migration</subject><subject>Human motion</subject><subject>Humans</subject><subject>Kenya - epidemiology</subject><subject>Metapopulations</subject><subject>Mobility</subject><subject>Models, Theoretical</subject><subject>Regional planning</subject><subject>Studies</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>D8T</sourceid><sourceid>DOA</sourceid><recordid>eNqNk11v0zAUhiMEYmPwDxBEmoRAosXfjm-QqvHRiqFJUHprOY7TukrsECdA_z1um00N2gXyha3j533tc-yTJM8hmELM4but71unqmnjnZkCSFAG6IPkHAqMJgwB_PBkfZY8CWELAMUZY4-TM8SoEIjz80QsNyZd1I3SXerLdN7XyqVffW4r2-1S79L5YpUuW-VCbUOwMWBd-sW4nXqaPCpVFcyzYb5Ifnz6uLyaT65vPi-uZtcTzZHoJnluIDe8JIRwjLnKihzmHOc5yjJQIAxRXqiCQWyAoBwxRDIMMigQZKIUROOL5OXRt6l8kEPWQUKOqYAQUx6JxZEovNrKprW1anfSKysPAd-upWo7qysjtQZKCQ1pCQDhlCtFAIQUKsBgQTITvd4evcJv0_T5yO2DXc0Obn0vEScY7I9-P1yuz2tTaOO6VlUj1XjH2Y1c-1-SMMoFhtHg9WDQ-p-9CZ2MddamqpQzvj-kyRgXnGURvfwHvb8YA7VWMV_rSh_P1XtTOSOYMoBiwpGa3kPFUZja6vijShvjI8GbkSAynfnTrVUfglx8__b_7M1qzL46YTdGVd0m-Krv4lcLY5AcQd36EFpT3hUZArlviNtqyH1DyKEhouzF6QPdiW47AP8FiYQBhw</recordid><startdate>20151124</startdate><enddate>20151124</enddate><creator>Isdory, Augustino</creator><creator>Mureithi, Eunice W</creator><creator>Sumpter, David J T</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>COVID</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>ACNBI</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>DF2</scope><scope>ZZAVC</scope><scope>DOA</scope></search><sort><creationdate>20151124</creationdate><title>The Impact of Human Mobility on HIV Transmission in Kenya</title><author>Isdory, Augustino ; Mureithi, Eunice W ; Sumpter, David J T</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c729t-bbe17e7f4447337a8db1b73bb2880d2312bdad613e095726248308192169f94c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Acquired immune deficiency syndrome</topic><topic>AIDS</topic><topic>Cell Phone</topic><topic>Cell phones</topic><topic>Complications and side effects</topic><topic>Disease transmission</topic><topic>Distribution</topic><topic>Epidemics</topic><topic>Health planning</topic><topic>HIV</topic><topic>HIV Infections - epidemiology</topic><topic>HIV Infections - transmission</topic><topic>HIV Infections - virology</topic><topic>HIV-1 - pathogenicity</topic><topic>Human immunodeficiency virus</topic><topic>Human Migration</topic><topic>Human motion</topic><topic>Humans</topic><topic>Kenya - epidemiology</topic><topic>Metapopulations</topic><topic>Mobility</topic><topic>Models, Theoretical</topic><topic>Regional planning</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Isdory, Augustino</creatorcontrib><creatorcontrib>Mureithi, Eunice W</creatorcontrib><creatorcontrib>Sumpter, David J T</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Opposing Viewpoints Resource Center</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>ProQuest Nursing and Allied Health Journals</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology 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>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>Biological Sciences</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental 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>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SWEPUB Uppsala universitet full text</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Uppsala universitet</collection><collection>SwePub Articles full text</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Isdory, Augustino</au><au>Mureithi, Eunice W</au><au>Sumpter, David J T</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Impact of Human Mobility on HIV Transmission in Kenya</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2015-11-24</date><risdate>2015</risdate><volume>10</volume><issue>11</issue><spage>e0142805</spage><epage>e0142805</epage><pages>e0142805-e0142805</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Disease spreads as a result of people moving and coming in contact with each other. Thus the mobility patterns of individuals are crucial in understanding disease dynamics. Here we study the impact of human mobility on HIV transmission in different parts of Kenya. We build an SIR metapopulation model that incorporates the different regions within the country. We parameterise the model using census data, HIV data and mobile phone data adopted to track human mobility. We found that movement between different regions appears to have a relatively small overall effect on the total increase in HIV cases in Kenya. However, the most important consequence of movement patterns was transmission of the disease from high infection to low prevalence areas. Mobility slightly increases HIV incidence rates in regions with initially low HIV prevalences and slightly decreases incidences in regions with initially high HIV prevalence. We discuss how regional HIV models could be used in public-health planning. This paper is a first attempt to model spread of HIV using mobile phone data, and we also discuss limitations to the approach.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26599277</pmid><doi>10.1371/journal.pone.0142805</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2015-11, Vol.10 (11), p.e0142805-e0142805 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1735911357 |
| source | MEDLINE; Public Library of Science; Full-Text Journals in Chemistry (Open access); DOAJ Directory of Open Access Journals; PubMed Central_; SWEPUB Freely available online; EZB Electronic Journals Library |
| subjects | Acquired immune deficiency syndrome AIDS Cell Phone Cell phones Complications and side effects Disease transmission Distribution Epidemics Health planning HIV HIV Infections - epidemiology HIV Infections - transmission HIV Infections - virology HIV-1 - pathogenicity Human immunodeficiency virus Human Migration Human motion Humans Kenya - epidemiology Metapopulations Mobility Models, Theoretical Regional planning Studies |
| title | The Impact of Human Mobility on HIV Transmission in Kenya |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T19%3A55%3A29IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20Impact%20of%20Human%20Mobility%20on%20HIV%20Transmission%20in%20Kenya&rft.jtitle=PloS%20one&rft.au=Isdory,%20Augustino&rft.date=2015-11-24&rft.volume=10&rft.issue=11&rft.spage=e0142805&rft.epage=e0142805&rft.pages=e0142805-e0142805&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0142805&rft_dat=%3Cgale_plos_%3EA435602011%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1735911357&rft_id=info:pmid/26599277&rft_galeid=A435602011&rft_doaj_id=oai_doaj_org_article_cc0aa9c15f004757aa401151a061d48e&rfr_iscdi=true |