Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands
Publication Date
November 25, 2009
Journal
PLOS ONE
Authors
Natacha Protopopoff, Wim Van Bortel, Niko Speybroeck, Jean Pierre Van Geertruyden, et al
Volume
4
Issue
11
Pages
e8022
DOI
https://dx.plos.org/10.1371/journal.pone.0008022
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0008022
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/19946627
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2778131
Europe PMC
http://europepmc.org/abstract/MED/19946627
Web of Science
000272827800014
Scopus
71049186047
Mendeley
http://www.mendeley.com/research/ranking-malaria-risk-factors-guide-malaria-control-efforts-african-highlands
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Mendeley | Further Information

{"title"=>"Ranking malaria risk factors to guide malaria control efforts in African highlands", "type"=>"journal", "authors"=>[{"first_name"=>"Natacha", "last_name"=>"Protopopoff", "scopus_author_id"=>"22980777900"}, {"first_name"=>"Wim", "last_name"=>"Van Bortel", "scopus_author_id"=>"6603881170"}, {"first_name"=>"Niko", "last_name"=>"Speybroeck", "scopus_author_id"=>"6701719825"}, {"first_name"=>"Jean Pierre", "last_name"=>"Van Geertruyden", "scopus_author_id"=>"35273810000"}, {"first_name"=>"Dismas", "last_name"=>"Baza", "scopus_author_id"=>"22978555300"}, {"first_name"=>"Umberto", "last_name"=>"D'Alessandro", "scopus_author_id"=>"7005042050"}, {"first_name"=>"Marc", "last_name"=>"Coosemans", "scopus_author_id"=>"7006869736"}], "year"=>2009, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"355735337", "sgr"=>"71049186047", "pmid"=>"19946627", "scopus"=>"2-s2.0-71049186047", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "doi"=>"10.1371/journal.pone.0008022", "issn"=>"19326203"}, "id"=>"89bbd78c-b5be-37e5-891d-ac0df085eb98", "abstract"=>"INTRODUCTION: Malaria is re-emerging in most of the African highlands exposing the non immune population to deadly epidemics. A better understanding of the factors impacting transmission in the highlands is crucial to improve well targeted malaria control strategies.\\n\\nMETHODS AND FINDINGS: A conceptual model of potential malaria risk factors in the highlands was built based on the available literature. Furthermore, the relative importance of these factors on malaria can be estimated through \"classification and regression trees\", an unexploited statistical method in the malaria field. This CART method was used to analyse the malaria risk factors in the Burundi highlands. The results showed that Anopheles density was the best predictor for high malaria prevalence. Then lower rainfall, no vector control, higher minimum temperature and houses near breeding sites were associated by order of importance to higher Anopheles density.\\n\\nCONCLUSIONS: In Burundi highlands monitoring Anopheles densities when rainfall is low may be able to predict epidemics. The conceptual model combined with the CART analysis is a decision support tool that could provide an important contribution toward the prevention and control of malaria by identifying major risk factors.", "link"=>"http://www.mendeley.com/research/ranking-malaria-risk-factors-guide-malaria-control-efforts-african-highlands", "reader_count"=>124, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>5, "Librarian"=>1, "Student > Doctoral Student"=>10, "Researcher"=>24, "Student > Ph. D. Student"=>32, "Student > Postgraduate"=>3, "Other"=>4, "Student > Master"=>21, "Student > Bachelor"=>8, "Lecturer"=>4, "Lecturer > Senior Lecturer"=>2, "Professor"=>5}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>5, "Librarian"=>1, "Student > Doctoral Student"=>10, "Researcher"=>24, "Student > Ph. D. Student"=>32, "Student > Postgraduate"=>3, "Other"=>4, "Student > Master"=>21, "Student > Bachelor"=>8, "Lecturer"=>4, "Lecturer > Senior Lecturer"=>2, "Professor"=>5}, "reader_count_by_subject_area"=>{"Unspecified"=>8, "Agricultural and Biological Sciences"=>25, "Veterinary Science and Veterinary Medicine"=>2, "Business, Management and Accounting"=>4, "Computer Science"=>1, "Earth and Planetary Sciences"=>2, "Engineering"=>1, "Environmental Science"=>15, "Nursing and Health Professions"=>6, "Biochemistry, Genetics and Molecular Biology"=>7, "Mathematics"=>1, "Medicine and Dentistry"=>42, "Social Sciences"=>9, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>42}, "Social Sciences"=>{"Social Sciences"=>9}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>8}, "Environmental Science"=>{"Environmental Science"=>15}, "Engineering"=>{"Engineering"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>25}, "Computer Science"=>{"Computer Science"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>2}}, "reader_count_by_country"=>{"Canada"=>1, "Belgium"=>1, "United States"=>5, "United Kingdom"=>4, "Australia"=>1, "Thailand"=>1}, "group_count"=>11}

CrossRef

Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/874107"], "description"=>"<p>Factors are regrouped in 3 main classes (environmental factors: green label, biological factors: grey label and human related factors: blue label). Dependant variables included in the CART analysis are displayed in red and predictor variables are highlighted in white.</p>", "links"=>[], "tags"=>["factors", "affecting", "malaria", "prevalence", "african"], "article_id"=>544550, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Natacha Protopopoff", "Wim Van Bortel", "Niko Speybroeck", "Jean-Pierre Van geertruyden", "Dismas Baza", "Umberto D'Alessandro", "Marc Coosemans"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0008022.g001", "stats"=>{"downloads"=>5, "page_views"=>193, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Conceptual_model_of_important_risk_factors_affecting_malaria_prevalence_in_the_African_Highlands_/544550", "title"=>"Conceptual model of important risk factors affecting malaria prevalence in the African Highlands.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 03:41:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/874490"], "description"=>"<p>Dependant and predictor variables introduced in the CART analysis.</p>", "links"=>[], "tags"=>["predictor", "variables", "introduced"], "article_id"=>544943, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Natacha Protopopoff", "Wim Van Bortel", "Niko Speybroeck", "Jean-Pierre Van geertruyden", "Dismas Baza", "Umberto D'Alessandro", "Marc Coosemans"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0008022.t001", "stats"=>{"downloads"=>2, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dependant_and_predictor_variables_introduced_in_the_CART_analysis_/544943", "title"=>"Dependant and predictor variables introduced in the CART analysis.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 03:43:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/874355"], "description"=>"<p>The selected splitting variables (Minimum temperature the previous month  =  T°min-1; Distance of the houses to the marsh with a cut off of 500 metres; Area sprayed or not; Monthly rainfall in the current month with a cut off of 96.2 mm) are shown in the nodes.</p>", "links"=>[], "tags"=>["trees", "factors"], "article_id"=>544810, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Natacha Protopopoff", "Wim Van Bortel", "Niko Speybroeck", "Jean-Pierre Van geertruyden", "Dismas Baza", "Umberto D'Alessandro", "Marc Coosemans"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0008022.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Regression_trees_representing_the_important_risk_factors_for_the_Anopheles_density_per_house_Ano_density_/544810", "title"=>"Regression trees representing the important risk factors for the <i>Anopheles</i> density per/house (Ano_density).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 03:42:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/874561"], "description"=>"<p>Ranking of predictor variables for <i>Anopheles</i> density by their overall power as discriminant.</p>", "links"=>[], "tags"=>["predictor", "variables"], "article_id"=>545015, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Natacha Protopopoff", "Wim Van Bortel", "Niko Speybroeck", "Jean-Pierre Van geertruyden", "Dismas Baza", "Umberto D'Alessandro", "Marc Coosemans"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0008022.t003", "stats"=>{"downloads"=>3, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ranking_of_predictor_variables_for_Anopheles_density_by_their_overall_power_as_discriminant_/545015", "title"=>"Ranking of predictor variables for <i>Anopheles</i> density by their overall power as discriminant.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 03:43:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/874526"], "description"=>"<p>Ranking of predictor variables for malaria prevalence by their overall power as discriminant.</p>", "links"=>[], "tags"=>["predictor", "variables", "malaria", "prevalence"], "article_id"=>544978, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Natacha Protopopoff", "Wim Van Bortel", "Niko Speybroeck", "Jean-Pierre Van geertruyden", "Dismas Baza", "Umberto D'Alessandro", "Marc Coosemans"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0008022.t002", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ranking_of_predictor_variables_for_malaria_prevalence_by_their_overall_power_as_discriminant_/544978", "title"=>"Ranking of predictor variables for malaria prevalence by their overall power as discriminant.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 03:43:45"}

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  • {"unique-ip"=>"20", "full-text"=>"14", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2016", "month"=>"9"}
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  • {"unique-ip"=>"24", "full-text"=>"24", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"17", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"15", "full-text"=>"16", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
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  • {"unique-ip"=>"17", "full-text"=>"20", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
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  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"22", "full-text"=>"39", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"31", "full-text"=>"33", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
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  • {"unique-ip"=>"111", "full-text"=>"129", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
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  • {"unique-ip"=>"79", "full-text"=>"87", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"92", "full-text"=>"104", "pdf"=>"12", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}
  • {"unique-ip"=>"78", "full-text"=>"99", "pdf"=>"53", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"12"}
  • {"unique-ip"=>"142", "full-text"=>"162", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"113", "full-text"=>"131", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"86", "full-text"=>"103", "pdf"=>"12", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2020", "month"=>"4"}
  • {"unique-ip"=>"82", "full-text"=>"107", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2020", "month"=>"5"}
  • {"unique-ip"=>"63", "full-text"=>"71", "pdf"=>"10", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
  • {"unique-ip"=>"23", "full-text"=>"24", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
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Relative Metric

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