Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South).
<p>The map layers were created using publicly available world map data from Natural Earth, accessed via the R package <i>rnaturalearth</i> [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0013315#pntd.0013315.ref024" target="_blank">...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
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| _version_ | 1852018421615558656 |
|---|---|
| author | Yewen Chen (12013847) |
| author2 | Fangzhi Luo (21728888) Leonardo Martinez (702635) Susan Jiang (10776913) Ye Shen (294552) |
| author2_role | author author author author |
| author_facet | Yewen Chen (12013847) Fangzhi Luo (21728888) Leonardo Martinez (702635) Susan Jiang (10776913) Ye Shen (294552) |
| author_role | author |
| dc.creator.none.fl_str_mv | Yewen Chen (12013847) Fangzhi Luo (21728888) Leonardo Martinez (702635) Susan Jiang (10776913) Ye Shen (294552) |
| dc.date.none.fl_str_mv | 2025-07-16T17:44:33Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pntd.0013315.s002 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Baseline_infection_prevalence_across_five_subregions_surrounding_Lake_Victoria_including_two_subregions_in_Tanzania_West_and_East_and_three_in_Kenya_Northwest_Northeast_and_South_/29585714 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Medicine Biotechnology Infectious Diseases Computational Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> compared three key aspects pose extreme challenges incorporate neighboring information identifying key aspects enhance predictive modeling collecting secondary data 9 %, compared hotspot prediction accuracy xlink "> based xlink "> schistosomiasis baseline infection data 5 %- 37 hotspot imbalance distribution hotspot predictions based technique schistosomiasis prevention schistosomiasis consortium transmission areas timely intervention public sources predictor combinations operational research mitigate overfitting limited availability early identification |
| dc.title.none.fl_str_mv | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South). |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>The map layers were created using publicly available world map data from Natural Earth, accessed via the R package <i>rnaturalearth</i> [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0013315#pntd.0013315.ref024" target="_blank">24</a>].</p> <p>(TIF)</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_50105f7a8d99edb839092b8cdd67fd21 |
| identifier_str_mv | 10.1371/journal.pntd.0013315.s002 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29585714 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South).Yewen Chen (12013847)Fangzhi Luo (21728888)Leonardo Martinez (702635)Susan Jiang (10776913)Ye Shen (294552)MedicineBiotechnologyInfectious DiseasesComputational BiologyEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedxlink "> comparedthree key aspectspose extreme challengesincorporate neighboring informationidentifying key aspectsenhance predictive modelingcollecting secondary data9 %, comparedhotspot prediction accuracyxlink "> basedxlink "> schistosomiasisbaseline infection data5 %- 37hotspot imbalance distributionhotspot predictionsbased techniqueschistosomiasis preventionschistosomiasis consortiumtransmission areastimely interventionpublic sourcespredictor combinationsoperational researchmitigate overfittinglimited availabilityearly identification<p>The map layers were created using publicly available world map data from Natural Earth, accessed via the R package <i>rnaturalearth</i> [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0013315#pntd.0013315.ref024" target="_blank">24</a>].</p> <p>(TIF)</p>2025-07-16T17:44:33ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pntd.0013315.s002https://figshare.com/articles/figure/Baseline_infection_prevalence_across_five_subregions_surrounding_Lake_Victoria_including_two_subregions_in_Tanzania_West_and_East_and_three_in_Kenya_Northwest_Northeast_and_South_/29585714CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/295857142025-07-16T17:44:33Z |
| spellingShingle | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South). Yewen Chen (12013847) Medicine Biotechnology Infectious Diseases Computational Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> compared three key aspects pose extreme challenges incorporate neighboring information identifying key aspects enhance predictive modeling collecting secondary data 9 %, compared hotspot prediction accuracy xlink "> based xlink "> schistosomiasis baseline infection data 5 %- 37 hotspot imbalance distribution hotspot predictions based technique schistosomiasis prevention schistosomiasis consortium transmission areas timely intervention public sources predictor combinations operational research mitigate overfitting limited availability early identification |
| status_str | publishedVersion |
| title | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South). |
| title_full | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South). |
| title_fullStr | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South). |
| title_full_unstemmed | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South). |
| title_short | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South). |
| title_sort | Baseline infection prevalence across five subregions surrounding Lake Victoria, including two subregions in Tanzania (West and East) and three in Kenya (Northwest, Northeast, and South). |
| topic | Medicine Biotechnology Infectious Diseases Computational Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> compared three key aspects pose extreme challenges incorporate neighboring information identifying key aspects enhance predictive modeling collecting secondary data 9 %, compared hotspot prediction accuracy xlink "> based xlink "> schistosomiasis baseline infection data 5 %- 37 hotspot imbalance distribution hotspot predictions based technique schistosomiasis prevention schistosomiasis consortium transmission areas timely intervention public sources predictor combinations operational research mitigate overfitting limited availability early identification |