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Modelling optimum use of attractive toxic sugar bait stations for effective malaria vector control in Africa
The development of insecticide resistance and the increased outdoor-biting behaviour of malaria vectors reduce the efficiency of indoor vector control methods. Attractive toxic sugar baits (ATSBs), a method targeting the sugar-feeding behaviours of vectors both indoors and outdoors, is a promising s...
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Published in: | Malaria journal 2015-12, Vol.14 (1), p.492, Article 492 |
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creator | Zhu, Lin Marshall, John M Qualls, Whitney A Schlein, Yosef McManus, John W Arheart, Kris L Hlaing, WayWay M Traore, Sekou F Doumbia, Seydou Müller, Günter C Beier, John C |
description | The development of insecticide resistance and the increased outdoor-biting behaviour of malaria vectors reduce the efficiency of indoor vector control methods. Attractive toxic sugar baits (ATSBs), a method targeting the sugar-feeding behaviours of vectors both indoors and outdoors, is a promising supplement to indoor tools. The number and configuration of these ATSB stations needed for malaria control in a community needs to be determined.
A hypothetical village, typical of those in sub-Saharan Africa, 600 × 600 m, consisting of houses, humans and essential resource requirements of Anopheles gambiae (sugar sources, outdoor resting sites, larval habitats) was simulated in a spatial individual-based model. Resource-rich and resource-poor environments were simulated separately. Eight types of configurations and different densities of ATSB stations were tested. Anopheles gambiae population size, human biting rate (HBR) and entomological inoculation rates (EIR) were compared between different ATSB configurations and densities. Each simulated scenario was run 50 times.
Compared to the outcomes not altered by ATSB treatment in the control scenario, in resource-rich and resource-poor environments, respectively, the optimum ATSB treatment reduced female abundance by 98.22 and 91.80 %, reduced HBR by 99.52 and 98.15 %, and reduced EIR by 99.99 and 100 %. In resource-rich environments, n × n grid design, stations at sugar sources, resting sites, larval habitats, and random locations worked better in reducing vector population and HBRs than other configurations (P < 0.0001). However, there was no significant difference of EIR reductions between all ATSB configurations (P > 0.05). In resource-poor environments, there was no significant difference of female abundances, HBRs and EIRs between all ATSB configurations (P > 0.05). The optimum number of ATSB stations was about 25 for resource-rich environments and nine for resource-poor environments.
ATSB treatment reduced An. gambiae population substantially and reduced EIR to near zero regardless of environmental resource availability. In resource-rich environments, dispersive configurations worked better in reducing vector population, and stations at or around houses worked better in preventing biting and parasite transmission. In resource-poor environments, all configurations worked similarly. Optimum numbers of bait stations should be adjusted according to seasonality when resource availability changes. |
doi_str_mv | 10.1186/s12936-015-1012-9 |
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A hypothetical village, typical of those in sub-Saharan Africa, 600 × 600 m, consisting of houses, humans and essential resource requirements of Anopheles gambiae (sugar sources, outdoor resting sites, larval habitats) was simulated in a spatial individual-based model. Resource-rich and resource-poor environments were simulated separately. Eight types of configurations and different densities of ATSB stations were tested. Anopheles gambiae population size, human biting rate (HBR) and entomological inoculation rates (EIR) were compared between different ATSB configurations and densities. Each simulated scenario was run 50 times.
Compared to the outcomes not altered by ATSB treatment in the control scenario, in resource-rich and resource-poor environments, respectively, the optimum ATSB treatment reduced female abundance by 98.22 and 91.80 %, reduced HBR by 99.52 and 98.15 %, and reduced EIR by 99.99 and 100 %. In resource-rich environments, n × n grid design, stations at sugar sources, resting sites, larval habitats, and random locations worked better in reducing vector population and HBRs than other configurations (P < 0.0001). However, there was no significant difference of EIR reductions between all ATSB configurations (P > 0.05). In resource-poor environments, there was no significant difference of female abundances, HBRs and EIRs between all ATSB configurations (P > 0.05). The optimum number of ATSB stations was about 25 for resource-rich environments and nine for resource-poor environments.
ATSB treatment reduced An. gambiae population substantially and reduced EIR to near zero regardless of environmental resource availability. In resource-rich environments, dispersive configurations worked better in reducing vector population, and stations at or around houses worked better in preventing biting and parasite transmission. In resource-poor environments, all configurations worked similarly. Optimum numbers of bait stations should be adjusted according to seasonality when resource availability changes.</description><identifier>ISSN: 1475-2875</identifier><identifier>EISSN: 1475-2875</identifier><identifier>DOI: 10.1186/s12936-015-1012-9</identifier><identifier>PMID: 26643110</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Africa ; Analysis ; Animals ; Anopheles ; Bites and stings ; Carbohydrates ; Control ; Feeding Behavior - drug effects ; Female ; Humans ; Insecticides ; Longevity - drug effects ; Malaria ; Malaria - drug therapy ; Malaria - prevention & control ; Models, Theoretical ; Mosquito Control - economics ; Pesticide resistance ; Population Density</subject><ispartof>Malaria journal, 2015-12, Vol.14 (1), p.492, Article 492</ispartof><rights>COPYRIGHT 2015 BioMed Central Ltd.</rights><rights>Copyright BioMed Central 2015</rights><rights>Zhu et al. 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c564t-a7bda8b31fd03ee9844565fb9d33514bb4c067636fccf353c7f37d79f050aa553</citedby><cites>FETCH-LOGICAL-c564t-a7bda8b31fd03ee9844565fb9d33514bb4c067636fccf353c7f37d79f050aa553</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/PMC4672472/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1779643732?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,44590,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26643110$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhu, Lin</creatorcontrib><creatorcontrib>Marshall, John M</creatorcontrib><creatorcontrib>Qualls, Whitney A</creatorcontrib><creatorcontrib>Schlein, Yosef</creatorcontrib><creatorcontrib>McManus, John W</creatorcontrib><creatorcontrib>Arheart, Kris L</creatorcontrib><creatorcontrib>Hlaing, WayWay M</creatorcontrib><creatorcontrib>Traore, Sekou F</creatorcontrib><creatorcontrib>Doumbia, Seydou</creatorcontrib><creatorcontrib>Müller, Günter C</creatorcontrib><creatorcontrib>Beier, John C</creatorcontrib><title>Modelling optimum use of attractive toxic sugar bait stations for effective malaria vector control in Africa</title><title>Malaria journal</title><addtitle>Malar J</addtitle><description>The development of insecticide resistance and the increased outdoor-biting behaviour of malaria vectors reduce the efficiency of indoor vector control methods. Attractive toxic sugar baits (ATSBs), a method targeting the sugar-feeding behaviours of vectors both indoors and outdoors, is a promising supplement to indoor tools. The number and configuration of these ATSB stations needed for malaria control in a community needs to be determined.
A hypothetical village, typical of those in sub-Saharan Africa, 600 × 600 m, consisting of houses, humans and essential resource requirements of Anopheles gambiae (sugar sources, outdoor resting sites, larval habitats) was simulated in a spatial individual-based model. Resource-rich and resource-poor environments were simulated separately. Eight types of configurations and different densities of ATSB stations were tested. Anopheles gambiae population size, human biting rate (HBR) and entomological inoculation rates (EIR) were compared between different ATSB configurations and densities. Each simulated scenario was run 50 times.
Compared to the outcomes not altered by ATSB treatment in the control scenario, in resource-rich and resource-poor environments, respectively, the optimum ATSB treatment reduced female abundance by 98.22 and 91.80 %, reduced HBR by 99.52 and 98.15 %, and reduced EIR by 99.99 and 100 %. In resource-rich environments, n × n grid design, stations at sugar sources, resting sites, larval habitats, and random locations worked better in reducing vector population and HBRs than other configurations (P < 0.0001). However, there was no significant difference of EIR reductions between all ATSB configurations (P > 0.05). In resource-poor environments, there was no significant difference of female abundances, HBRs and EIRs between all ATSB configurations (P > 0.05). The optimum number of ATSB stations was about 25 for resource-rich environments and nine for resource-poor environments.
ATSB treatment reduced An. gambiae population substantially and reduced EIR to near zero regardless of environmental resource availability. In resource-rich environments, dispersive configurations worked better in reducing vector population, and stations at or around houses worked better in preventing biting and parasite transmission. In resource-poor environments, all configurations worked similarly. Optimum numbers of bait stations should be adjusted according to seasonality when resource availability changes.</description><subject>Africa</subject><subject>Analysis</subject><subject>Animals</subject><subject>Anopheles</subject><subject>Bites and stings</subject><subject>Carbohydrates</subject><subject>Control</subject><subject>Feeding Behavior - drug effects</subject><subject>Female</subject><subject>Humans</subject><subject>Insecticides</subject><subject>Longevity - drug effects</subject><subject>Malaria</subject><subject>Malaria - drug therapy</subject><subject>Malaria - prevention & control</subject><subject>Models, Theoretical</subject><subject>Mosquito Control - economics</subject><subject>Pesticide resistance</subject><subject>Population Density</subject><issn>1475-2875</issn><issn>1475-2875</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNptUU1v1DAUtBCIlsIP4IIscU7xi7-SC9KqooDUqhc4Wy-OvbhK4sV2VvDv69WWaishH_zxZkbjGULeA7sE6NSnDG3PVcNANsCgbfoX5ByElk3bafny5HxG3uR8zxjoTrevyVmrlOAA7JxMt3F00xSWLY27EuZ1pmt2NHqKpSS0JewdLfFPsDSvW0x0wFBoLlhCXDL1MVHnvTviZpwwBaT7eq8DG5eS4kTDQjc-BYtvySuPU3bvHvcL8vP6y4-rb83N3dfvV5ubxkolSoN6GLEbOPiRcef6TgippB_6kXMJYhiEZUorrry1nktuted61L1nkiFKyS_I56Pubh1mN1pXfeBkdinMmP6aiME8nyzhl9nGvRFKt0K3VeDjo0CKv1eXi7mPa1qqZwNa9zU8zU9QW5ycCYuPh8TmkK3ZCNUz1nEGFXX5H1Rdo5tDjcj5UN-fEeBIsCnmnJx_Mg7MHHo3x95N7d0cejd95Xw4_fET41_R_AEIkKnI</recordid><startdate>20151208</startdate><enddate>20151208</enddate><creator>Zhu, Lin</creator><creator>Marshall, John M</creator><creator>Qualls, Whitney A</creator><creator>Schlein, Yosef</creator><creator>McManus, John W</creator><creator>Arheart, Kris L</creator><creator>Hlaing, WayWay M</creator><creator>Traore, Sekou F</creator><creator>Doumbia, Seydou</creator><creator>Müller, Günter C</creator><creator>Beier, John C</creator><general>BioMed Central Ltd</general><general>BioMed Central</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>3V.</scope><scope>7SS</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>H95</scope><scope>H97</scope><scope>K9.</scope><scope>L.G</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope></search><sort><creationdate>20151208</creationdate><title>Modelling optimum use of attractive toxic sugar bait stations for effective malaria vector control in Africa</title><author>Zhu, Lin ; Marshall, John M ; Qualls, Whitney A ; Schlein, Yosef ; McManus, John W ; Arheart, Kris L ; Hlaing, WayWay M ; Traore, Sekou F ; Doumbia, Seydou ; Müller, Günter C ; Beier, John C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c564t-a7bda8b31fd03ee9844565fb9d33514bb4c067636fccf353c7f37d79f050aa553</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Africa</topic><topic>Analysis</topic><topic>Animals</topic><topic>Anopheles</topic><topic>Bites and stings</topic><topic>Carbohydrates</topic><topic>Control</topic><topic>Feeding Behavior - drug effects</topic><topic>Female</topic><topic>Humans</topic><topic>Insecticides</topic><topic>Longevity - drug effects</topic><topic>Malaria</topic><topic>Malaria - drug therapy</topic><topic>Malaria - prevention & control</topic><topic>Models, Theoretical</topic><topic>Mosquito Control - economics</topic><topic>Pesticide resistance</topic><topic>Population Density</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhu, Lin</creatorcontrib><creatorcontrib>Marshall, John M</creatorcontrib><creatorcontrib>Qualls, Whitney A</creatorcontrib><creatorcontrib>Schlein, Yosef</creatorcontrib><creatorcontrib>McManus, John W</creatorcontrib><creatorcontrib>Arheart, Kris L</creatorcontrib><creatorcontrib>Hlaing, WayWay M</creatorcontrib><creatorcontrib>Traore, Sekou F</creatorcontrib><creatorcontrib>Doumbia, Seydou</creatorcontrib><creatorcontrib>Müller, Günter C</creatorcontrib><creatorcontrib>Beier, John C</creatorcontrib><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>Entomology Abstracts (Full archive)</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</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 Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</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>PubMed Central (Full Participant titles)</collection><jtitle>Malaria journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhu, Lin</au><au>Marshall, John M</au><au>Qualls, Whitney A</au><au>Schlein, Yosef</au><au>McManus, John W</au><au>Arheart, Kris L</au><au>Hlaing, WayWay M</au><au>Traore, Sekou F</au><au>Doumbia, Seydou</au><au>Müller, Günter C</au><au>Beier, John C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modelling optimum use of attractive toxic sugar bait stations for effective malaria vector control in Africa</atitle><jtitle>Malaria journal</jtitle><addtitle>Malar J</addtitle><date>2015-12-08</date><risdate>2015</risdate><volume>14</volume><issue>1</issue><spage>492</spage><pages>492-</pages><artnum>492</artnum><issn>1475-2875</issn><eissn>1475-2875</eissn><abstract>The development of insecticide resistance and the increased outdoor-biting behaviour of malaria vectors reduce the efficiency of indoor vector control methods. Attractive toxic sugar baits (ATSBs), a method targeting the sugar-feeding behaviours of vectors both indoors and outdoors, is a promising supplement to indoor tools. The number and configuration of these ATSB stations needed for malaria control in a community needs to be determined.
A hypothetical village, typical of those in sub-Saharan Africa, 600 × 600 m, consisting of houses, humans and essential resource requirements of Anopheles gambiae (sugar sources, outdoor resting sites, larval habitats) was simulated in a spatial individual-based model. Resource-rich and resource-poor environments were simulated separately. Eight types of configurations and different densities of ATSB stations were tested. Anopheles gambiae population size, human biting rate (HBR) and entomological inoculation rates (EIR) were compared between different ATSB configurations and densities. Each simulated scenario was run 50 times.
Compared to the outcomes not altered by ATSB treatment in the control scenario, in resource-rich and resource-poor environments, respectively, the optimum ATSB treatment reduced female abundance by 98.22 and 91.80 %, reduced HBR by 99.52 and 98.15 %, and reduced EIR by 99.99 and 100 %. In resource-rich environments, n × n grid design, stations at sugar sources, resting sites, larval habitats, and random locations worked better in reducing vector population and HBRs than other configurations (P < 0.0001). However, there was no significant difference of EIR reductions between all ATSB configurations (P > 0.05). In resource-poor environments, there was no significant difference of female abundances, HBRs and EIRs between all ATSB configurations (P > 0.05). The optimum number of ATSB stations was about 25 for resource-rich environments and nine for resource-poor environments.
ATSB treatment reduced An. gambiae population substantially and reduced EIR to near zero regardless of environmental resource availability. In resource-rich environments, dispersive configurations worked better in reducing vector population, and stations at or around houses worked better in preventing biting and parasite transmission. In resource-poor environments, all configurations worked similarly. Optimum numbers of bait stations should be adjusted according to seasonality when resource availability changes.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>26643110</pmid><doi>10.1186/s12936-015-1012-9</doi><oa>free_for_read</oa></addata></record> |
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subjects | Africa Analysis Animals Anopheles Bites and stings Carbohydrates Control Feeding Behavior - drug effects Female Humans Insecticides Longevity - drug effects Malaria Malaria - drug therapy Malaria - prevention & control Models, Theoretical Mosquito Control - economics Pesticide resistance Population Density |
title | Modelling optimum use of attractive toxic sugar bait stations for effective malaria vector control in Africa |
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