Is Housing Quality Associated with Malaria Incidence among Young Children and Mosquito Vector Numbers? Evidence from Korogwe, Tanzania
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{"title"=>"Is housing quality associated with malaria incidence among young children and mosquito vector numbers? Evidence from Korogwe, Tanzania", "type"=>"journal", "authors"=>[{"first_name"=>"Jenny X.", "last_name"=>"Liu", "scopus_author_id"=>"55321518400"}, {"first_name"=>"Teun", "last_name"=>"Bousema", "scopus_author_id"=>"6506709831"}, {"first_name"=>"Brittany", "last_name"=>"Zelman", "scopus_author_id"=>"36963117600"}, {"first_name"=>"Samwel", "last_name"=>"Gesase", "scopus_author_id"=>"14621527400"}, {"first_name"=>"Ramadhan", "last_name"=>"Hashim", "scopus_author_id"=>"26431350300"}, {"first_name"=>"Caroline", "last_name"=>"Maxwell", "scopus_author_id"=>"7103043091"}, {"first_name"=>"Daniel", "last_name"=>"Chandramohan", "scopus_author_id"=>"7003426215"}, {"first_name"=>"Roly", "last_name"=>"Gosling", "scopus_author_id"=>"15750608700"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84895511156", "sgr"=>"84895511156", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0087358", "pmid"=>"24505285", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pui"=>"372535202"}, "id"=>"a8806a2c-24d2-3913-a226-0e7b5c7f7d45", "abstract"=>"BACKGROUND: Several studies conducted in Northeast Tanzania have documented declines in malaria transmission even before interventions were scaled up. One explanation for these reductions may be the changes in socio-environmental conditions associated with economic development, and in particular improvements in housing construction.\\n\\nOBJECTIVE: This analysis seeks to identify (1) risk factors for malaria incidence among young children and (2) household and environmental factors associated with mosquito vector numbers collected in the child's sleeping area. Both analyses focus on housing construction quality as a key determinant.\\n\\nMETHODOLOGY: For 435 children enrolled in a larger trial of intermittent preventive treatment for malaria in infants in the Korogwe District in Tanga, Northeastern Tanzania, detailed information on their dwelling characteristics were collected in the last year of the trial. Principal components analysis was used to construct an index of housing structure quality and converted to quintile units for regression analysis. Univariate and multivariate random effects negative binomial regressions were used to predict risk factors for child malaria incidence and the mean total number of indoor female Anopheles gambiae and funestus mosquitoes collected per household across three occasions.\\n\\nFINDINGS: Building materials have substantially improved in Korogwe over time. Multivariate regressions showed that residing in rural areas (versus urban) increased malaria incidence rates by over three-fold and mean indoor female A. gambiae and funestus numbers by nearly two-fold. Compared to those residing in the lowest quality houses, children residing in the highest quality houses had one-third lower malaria incidence rates, even when wealth and rural residence were controlled for. Living in the highest quality houses reduced vector numbers while having cattle near the house significantly increased them.\\n\\nCONCLUSIONS: Results corroborate findings from other studies that show associations between malaria incidence and housing quality; associations were concentrated amongst the highest quality houses.", "link"=>"http://www.mendeley.com/research/housing-quality-associated-malaria-incidence-among-young-children-mosquito-vector-numbers-evidence-k", "reader_count"=>67, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Student > Doctoral Student"=>2, "Researcher"=>11, "Student > Ph. D. Student"=>13, "Student > Postgraduate"=>2, "Other"=>2, "Student > Master"=>22, "Student > Bachelor"=>9, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Student > Doctoral Student"=>2, "Researcher"=>11, "Student > Ph. D. Student"=>13, "Student > Postgraduate"=>2, "Other"=>2, "Student > Master"=>22, "Student > Bachelor"=>9, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Agricultural and Biological Sciences"=>19, "Arts and Humanities"=>1, "Computer Science"=>1, "Earth and Planetary Sciences"=>2, "Economics, Econometrics and Finance"=>2, "Engineering"=>1, "Environmental Science"=>10, "Biochemistry, Genetics and Molecular Biology"=>1, "Nursing and Health Professions"=>3, "Mathematics"=>2, "Medicine and Dentistry"=>14, "Psychology"=>1, "Social Sciences"=>6, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>14}, "Social Sciences"=>{"Social Sciences"=>6}, "Psychology"=>{"Psychology"=>1}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>10}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>2}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>19}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "United States"=>1, "Tanzania"=>1, "Brazil"=>1, "Kenya"=>2}, "group_count"=>3}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1377828"], "description"=>"<p>The incidence of malaria decreases as the housing quality index increases (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087358#pone-0087358-g003\" target=\"_blank\">Figure 3</a>). In particular, incidence among children residing in the lowest three quintiles was over two to three times higher than among those residing in the highest quality quintile, and this was consistent across rural and urban areas.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Epidemiological methods", "Infectious diseases", "Parasitic diseases", "malaria", "Tropical diseases (non-neglected)", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Environmental health", "Socioeconomic aspects of health", "Public health", "Child health", "positivity"], "article_id"=>927469, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Jenny X. Liu", "Teun Bousema", "Brittany Zelman", "Samwel Gesase", "Ramadhan Hashim", "Caroline Maxwell", "Daniel Chandramohan", "Roly Gosling"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0087358.g003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Slide_positivity_rate_by_housing_index_quintile_/927469", "title"=>"Slide positivity rate by housing index quintile.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-05 03:50:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1377824"], "description"=>"<p>A historical account of housing improvements was collected by asking respondents for the type of roofs and walls that their housing unit was made of at the time of different life events: when they were first married, when they had their first child, when they had their last child, and at the time of survey. These dates are used to calculate the cumulative density of houses that have attained iron roofs (instead of thatched roofs) and concrete walls (replacing mud walls) since 1975. Whereas the proportion of houses with iron roofs or concrete walls was nearly zero prior to 1985, by 2008, nearly 80% and 40% of houses have these materials, respectively. These trends correspond with increasing national gross domestic product per capita in the country. Notes: GDP per capita (US$2000) obtained from World Bank Indicators.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Epidemiological methods", "Infectious diseases", "Parasitic diseases", "malaria", "Tropical diseases (non-neglected)", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Environmental health", "Socioeconomic aspects of health", "Public health", "Child health", "households", "walls", "roofs"], "article_id"=>927465, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Jenny X. Liu", "Teun Bousema", "Brittany Zelman", "Samwel Gesase", "Ramadhan Hashim", "Caroline Maxwell", "Daniel Chandramohan", "Roly Gosling"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0087358.g002", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Proportion_of_households_with_concrete_walls_and_iron_roofs_over_time_1975_8211_2008_/927465", "title"=>"Proportion of households with concrete walls and iron roofs over time (1975–2008).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-05 03:50:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1377823"], "description"=>"<p>Malaria intervention coverage rates have only recently increased. Greater household ownership of ITNs, ITN use among children under 5, and the proportion of children receiving artemisinin combination therapy (ACT) treatment in Tanzania started in 2004, surpassing 50% coverage only in 2010. Source: Tanzania Demographic and Health Surveys 1999, 2004, 2007, 2010, and 2011.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Epidemiological methods", "Infectious diseases", "Parasitic diseases", "malaria", "Tropical diseases (non-neglected)", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Environmental health", "Socioeconomic aspects of health", "Public health", "Child health", "indicators", "tanzania", "surveys"], "article_id"=>927464, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Jenny X. Liu", "Teun Bousema", "Brittany Zelman", "Samwel Gesase", "Ramadhan Hashim", "Caroline Maxwell", "Daniel Chandramohan", "Roly Gosling"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0087358.g001", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Selected_malaria_indicators_from_Tanzania_Demographic_and_Health_Surveys_1999_2004_2007_2010_and_2011_/927464", "title"=>"Selected malaria indicators from Tanzania Demographic and Health Surveys (1999, 2004, 2007, 2010, and 2011).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-05 03:50:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1377836"], "description"=>"1<p>Incidence rate ratios (IRRs) estimated by random effects negative binomial regression.</p><p>Dependent variable is the mean total number of <i>Anopheles gambiae</i> and <i>funestus</i> caught per household over three occasions.</p>***<p>p<0.01, **p<0.05, *p<0.1.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Epidemiological methods", "Infectious diseases", "Parasitic diseases", "malaria", "Tropical diseases (non-neglected)", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Environmental health", "Socioeconomic aspects of health", "Public health", "Child health", "indoor", "vectors"], "article_id"=>927477, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Jenny X. Liu", "Teun Bousema", "Brittany Zelman", "Samwel Gesase", "Ramadhan Hashim", "Caroline Maxwell", "Daniel Chandramohan", "Roly Gosling"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0087358.t004", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Risk_factors_for_the_mean_total_number_of_indoor_vectors_per_household_collected_over_three_occasions_/927477", "title"=>"Risk factors for the mean total number of indoor vectors per household collected over three occasions.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-05 03:50:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1377835"], "description"=>"<p>Child malaria incidence and mosquito numbers collected per household.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Epidemiological methods", "Infectious diseases", "Parasitic diseases", "malaria", "Tropical diseases (non-neglected)", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Environmental health", "Socioeconomic aspects of health", "Public health", "Child health", "incidence", "mosquito", "numbers"], "article_id"=>927476, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Jenny X. Liu", "Teun Bousema", "Brittany Zelman", "Samwel Gesase", "Ramadhan Hashim", "Caroline Maxwell", "Daniel Chandramohan", "Roly Gosling"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0087358.t001", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Child_malaria_incidence_and_mosquito_numbers_collected_per_household_/927476", "title"=>"Child malaria incidence and mosquito numbers collected per household.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-05 03:50:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1377832"], "description"=>"<p>There does not appear to be a consistent or gradient relationship between house quality and the mean mosquito numbers across urban and rural areas. In urban areas, the highest quality houses in quintile 5 had a median of zero vectors, and vectors were mainly comprised only of female <i>A gambiae</i>. In contrast, in rural areas, vector numbers were a mix of <i>A. gambiae</i> and <i>funestus</i>, and generally decreased as house quality increased, except for houses in quintile 4. More vectors were collected in houses with cattle nearby.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Epidemiological methods", "Infectious diseases", "Parasitic diseases", "malaria", "Tropical diseases (non-neglected)", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Environmental health", "Socioeconomic aspects of health", "Public health", "Child health", "indoor", "mosquitoes", "vectors"], "article_id"=>927473, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Jenny X. Liu", "Teun Bousema", "Brittany Zelman", "Samwel Gesase", "Ramadhan Hashim", "Caroline Maxwell", "Daniel Chandramohan", "Roly Gosling"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0087358.g004", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Total_number_of_indoor_mosquitoes_vectors_collected_per_household_mean_of_three_occasions_by_selected_house_quality_indicators_/927473", "title"=>"Total number of indoor mosquitoes vectors collected per household (mean of three occasions) by selected house quality indicators.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-05 03:50:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1377834"], "description"=>"<p>Housing index component measures across quintiles.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Epidemiological methods", "Infectious diseases", "Parasitic diseases", "malaria", "Tropical diseases (non-neglected)", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Environmental health", "Socioeconomic aspects of health", "Public health", "Child health", "measures"], "article_id"=>927475, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Jenny X. Liu", "Teun Bousema", "Brittany Zelman", "Samwel Gesase", "Ramadhan Hashim", "Caroline Maxwell", "Daniel Chandramohan", "Roly Gosling"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0087358.t002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Housing_index_component_measures_across_quintiles_/927475", "title"=>"Housing index component measures across quintiles.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-05 03:50:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1377833"], "description"=>"1<p>Incidence rate ratios (RRRs) estimated by random effects negative binomial regression specifying exposure time per child.</p>2<p>Regression also controls for the trial arm that the participant was randomized to: mefloquine, sulfadoxine-pyrimethamine, CD, control.</p>***<p>p<0.01, **p<0.05, *p<0.1.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Epidemiological methods", "Infectious diseases", "Parasitic diseases", "malaria", "Tropical diseases (non-neglected)", "Non-clinical medicine", "Health care policy", "Health risk analysis", "Environmental health", "Socioeconomic aspects of health", "Public health", "Child health", "incidence"], "article_id"=>927474, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Jenny X. Liu", "Teun Bousema", "Brittany Zelman", "Samwel Gesase", "Ramadhan Hashim", "Caroline Maxwell", "Daniel Chandramohan", "Roly Gosling"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0087358.t003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Risk_factors_for_malaria_incidence_among_children_/927474", "title"=>"Risk factors for malaria incidence among children.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-05 03:50:01"}

PMC Usage Stats | Further Information

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Relative Metric

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