Childhood Malaria Admission Rates to Four Hospitals in Malawi between 2000 and 2010
Publication Date
April 26, 2013
Journal
PLOS ONE
Authors
Emelda A. Okiro, Lawrence N. Kazembe, Caroline W. Kabaria, Jeffrey Ligomeka, et al
Volume
8
Issue
4
Pages
e62214
DOI
https://dx.plos.org/10.1371/journal.pone.0062214
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0062214
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23638008
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3637378
Europe PMC
http://europepmc.org/abstract/MED/23638008
Web of Science
000318343700040
Scopus
84876871508
Mendeley
http://www.mendeley.com/research/childhood-malaria-admission-rates-four-hospitals-malawi-between-2000-2010
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Mendeley | Further Information

{"title"=>"Childhood Malaria Admission Rates to Four Hospitals in Malawi between 2000 and 2010", "type"=>"journal", "authors"=>[{"first_name"=>"Emelda A.", "last_name"=>"Okiro", "scopus_author_id"=>"10640311700"}, {"first_name"=>"Lawrence N.", "last_name"=>"Kazembe", "scopus_author_id"=>"14830318700"}, {"first_name"=>"Caroline W.", "last_name"=>"Kabaria", "scopus_author_id"=>"25653969300"}, {"first_name"=>"Jeffrey", "last_name"=>"Ligomeka", "scopus_author_id"=>"55669393300"}, {"first_name"=>"Abdisalan M.", "last_name"=>"Noor", "scopus_author_id"=>"7103299616"}, {"first_name"=>"Doreen", "last_name"=>"Ali", "scopus_author_id"=>"7005976715"}, {"first_name"=>"Robert W.", "last_name"=>"Snow", "scopus_author_id"=>"56771582900"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84876871508", "sgr"=>"84876871508", "pui"=>"368819810", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"23638008", "doi"=>"10.1371/journal.pone.0062214"}, "id"=>"1d1fa8ea-c35e-3feb-a8df-cf64f45d403b", "abstract"=>"INTRODUCTION: The last few years have witnessed rapid scaling-up of key malaria interventions in several African countries following increases in development assistance. However, there is only limited country-specific information on the health impact of expanded coverage of these interventions.\\nMETHODS: Paediatric admission data were assembled from 4 hospitals in Malawi reflecting different malaria ecologies. Trends in monthly clinical malaria admissions between January 2000 and December 2010 were analysed using time-series models controlling for covariates related to climate and service use to establish whether changes in admissions can be related to expanded coverage of interventions aimed at reducing malaria infection.\\nRESULTS: In 3 of 4 sites there was an increase in clinical malaria admission rates. Results from time series models indicate a significant month-to-month increase in the mean clinical malaria admission rates at two hospitals (trend P<0.05). At these hospitals clinical malaria admissions had increased from 2000 by 41% to 100%. Comparison of changes in malaria risk and ITN coverage appear to correspond to a lack of disease declines over the period. Changes in intervention coverage within hospital catchments showed minimal increases in ITN coverage from <6% across all sites in 2000 to maximum of 33% at one hospital site by 2010. Additionally, malaria transmission intensity remained unchanged between 2000-2010 across all sites.\\nDISCUSSION: Despite modest increases in coverage of measures to reduce infection there has been minimal changes in paediatric clinical malaria cases in four hospitals in Malawi. Studies across Africa are increasingly showing a mixed set of impact results and it is important to assemble more data from more sites to understand the wider implications of malaria funding investment. We also caution that impact surveillance should continue in areas where intervention coverage is increasing with time, for example Malawi, as decline may become evident within a period when coverage reaches optimal levels", "link"=>"http://www.mendeley.com/research/childhood-malaria-admission-rates-four-hospitals-malawi-between-2000-2010", "reader_count"=>38, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Researcher"=>13, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>3, "Student > Master"=>5, "Other"=>3, "Student > Bachelor"=>4, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Researcher"=>13, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>3, "Student > Master"=>5, "Other"=>3, "Student > Bachelor"=>4, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Environmental Science"=>4, "Nursing and Health Professions"=>3, "Medicine and Dentistry"=>15, "Agricultural and Biological Sciences"=>6, "Social Sciences"=>7, "Immunology and Microbiology"=>1, "Earth and Planetary Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>15}, "Social Sciences"=>{"Social Sciences"=>7}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>6}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>4}}, "reader_count_by_country"=>{"United States"=>2, "Brazil"=>2, "United Kingdom"=>1, "Kenya"=>1}, "group_count"=>6}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1045187"], "description"=>"<p>Data for Salima hospital in 2000 was not available.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Clinical research design", "Disease informatics", "Pediatric epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "pediatrics", "numbers", "all-cause", "paediatric", "admissions", "proportions", "children", "aged", "years"], "article_id"=>692725, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Emelda A. Okiro", "Lawrence N. Kazembe", "Caroline W. Kabaria", "Jeffrey Ligomeka", "Abdisalan M. Noor", "Doreen Ali", "Robert W. Snow"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062214.t002", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Annual_numbers_of_all_cause_paediatric_0_8211_4_years_admissions_malaria_paediatric_admissions_and_proportions_of_clinical_malaria_admissions_for_children_aged_less_than_five_years_by_hospital_site_/692725", "title"=>"Annual numbers of all-cause paediatric (0–4 years) admissions, malaria paediatric admissions and proportions of clinical malaria admissions for children aged less than five years by hospital site.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-04-26 00:45:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/1045186"], "description"=>"<p><b>Notes:</b></p><p>Data on ITN and IRS coverage from clusters within a 40 km radius of each hospital were extracted in ARCGIS 9.2 (ESRI, Inc., Redland, CA, USA) from the Malawian DHS dates of 2000, 2004 and 2010.</p>1<p>ITN Coverage- Coverage defined as the proportion of individuals of all ages who slept under an ITN the night before the surveys.</p><p>ITN- Insecticide treated net; DHS - Demographic Health surveys, HH-Households.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Clinical research design", "Disease informatics", "Pediatric epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "pediatrics", "groups", "irs", "12"], "article_id"=>692724, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Emelda A. Okiro", "Lawrence N. Kazembe", "Caroline W. Kabaria", "Jeffrey Ligomeka", "Abdisalan M. Noor", "Doreen Ali", "Robert W. Snow"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062214.t003", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_ITN_coverage_among_individual_of_all_age_groups_and_IRS_coverage_in_the_last_12_months_/692724", "title"=>"ITN coverage among individual of all age groups and IRS coverage in the last 12 months.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-04-26 00:45:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1045180"], "description"=>"<p>Graph panels show changing paeditaric hospitalizations due to malaria (red line), non-malaria (green dotted line) and total admission in children aged 0–4 years (black line) between 2000 and 2010.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Clinical research design", "Disease informatics", "Pediatric epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "pediatrics", "hospitals", "90", "elevation", "dataset", "topographic", "NASA", "nga", "geospatial-intelligence"], "article_id"=>692721, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Emelda A. Okiro", "Lawrence N. Kazembe", "Caroline W. Kabaria", "Jeffrey Ligomeka", "Abdisalan M. Noor", "Doreen Ali", "Robert W. Snow"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062214.g001", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Location_of_selected_hospitals_blue_squares_shown_on_a_90_m_digital_elevation_model_DEM_dataset_from_the_Shuttle_Radar_Topographic_Mission_SRTM_a_joint_project_between_NASA_and_NGA_National_Geospatial_Intelligence_Agency_77_/692721", "title"=>"Location of selected hospitals (blue squares) shown on a 90 m digital elevation model (DEM) dataset from the Shuttle Radar Topographic Mission (SRTM) a joint project between NASA and NGA (National Geospatial-Intelligence Agency) [<b>77</b>].", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-26 00:45:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/1045190", "https://ndownloader.figshare.com/files/1045195"], "description"=>"<div><p>Introduction</p><p>The last few years have witnessed rapid scaling-up of key malaria interventions in several African countries following increases in development assistance. However, there is only limited country-specific information on the health impact of expanded coverage of these interventions.</p><p>Methods</p><p>Paediatric admission data were assembled from 4 hospitals in Malawi reflecting different malaria ecologies. Trends in monthly clinical malaria admissions between January 2000 and December 2010 were analysed using time-series models controlling for covariates related to climate and service use to establish whether changes in admissions can be related to expanded coverage of interventions aimed at reducing malaria infection.</p><p>Results</p><p>In 3 of 4 sites there was an increase in clinical malaria admission rates. Results from time series models indicate a significant month-to-month increase in the mean clinical malaria admission rates at two hospitals (trend P<0.05). At these hospitals clinical malaria admissions had increased from 2000 by 41% to 100%. Comparison of changes in malaria risk and ITN coverage appear to correspond to a lack of disease declines over the period. Changes in intervention coverage within hospital catchments showed minimal increases in ITN coverage from <6% across all sites in 2000 to maximum of 33% at one hospital site by 2010. Additionally, malaria transmission intensity remained unchanged between 2000–2010 across all sites.</p><p>Discussion</p><p>Despite modest increases in coverage of measures to reduce infection there has been minimal changes in paediatric clinical malaria cases in four hospitals in Malawi. Studies across Africa are increasingly showing a mixed set of impact results and it is important to assemble more data from more sites to understand the wider implications of malaria funding investment. We also caution that impact surveillance should continue in areas where intervention coverage is increasing with time, for example Malawi, as decline may become evident within a period when coverage reaches optimal levels.</p></div>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Clinical research design", "Disease informatics", "Pediatric epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "pediatrics", "rates", "hospitals", "malawi", "2000"], "article_id"=>692727, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Emelda A. Okiro", "Lawrence N. Kazembe", "Caroline W. Kabaria", "Jeffrey Ligomeka", "Abdisalan M. Noor", "Doreen Ali", "Robert W. Snow"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0062214.s001", "https://dx.doi.org/10.1371/journal.pone.0062214.s002"], "stats"=>{"downloads"=>2, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Childhood_Malaria_Admission_Rates_to_Four_Hospitals_in_Malawi_between_2000_and_2010_/692727", "title"=>"Childhood Malaria Admission Rates to Four Hospitals in Malawi between 2000 and 2010", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-04-26 00:45:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/1045188"], "description"=>"<p><b>Notes.</b></p>1<p>Endemicity classes defined as in Hay et al. <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0062214#pone.0062214-Hay1\" target=\"_blank\">[69]</a> where >40% is accepted as highly endemic.</p>2<p>Predicted estimates of <i>Pf</i>PR from within the catchments of hospitals sites in Malawi using ARC GIS.</p>3<p>A digital elevation map (DEM) that has a resolution of 30 meters was used to define altitude (<a href=\"http://www.vterrain.org/Elevation/SRTM/\" target=\"_blank\">http://www.vterrain.org/Elevation/SRTM/</a>).</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Clinical research design", "Disease informatics", "Pediatric epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "pediatrics"], "article_id"=>692726, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Emelda A. Okiro", "Lawrence N. Kazembe", "Caroline W. Kabaria", "Jeffrey Ligomeka", "Abdisalan M. Noor", "Doreen Ali", "Robert W. Snow"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062214.t001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_characteristics_of_malaria_transmission_at_each_hospital_site_/692726", "title"=>"The characteristics of malaria transmission at each hospital site.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-04-26 00:45:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1045183"], "description"=>"<p>Fitted lines illustrate the linear trends from model predictions (dashed line).</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Clinical research design", "Disease informatics", "Pediatric epidemiology", "Infectious diseases", "Parasitic diseases", "malaria", "pediatrics", "predictions", "paediatric", "hospitalization", "rates", "children", "controlling", "non-malaria", "rainfall", "autoregressive", "moving"], "article_id"=>692722, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Emelda A. Okiro", "Lawrence N. Kazembe", "Caroline W. Kabaria", "Jeffrey Ligomeka", "Abdisalan M. Noor", "Doreen Ali", "Robert W. Snow"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0062214.g002", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_predictions_of_paediatric_malaria_hospitalization_rates_in_children_under_5_controlling_for_non_malaria_case_rates_rainfall_and_controlling_for_autoregressive_and_moving_average_effects_solid_black_line_/692722", "title"=>"Model predictions of paediatric malaria hospitalization rates in children under 5 controlling for non-malaria case rates, rainfall and controlling for autoregressive and moving average effects (solid black line).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-26 00:45:22"}

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Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Agriculture", "average_usage"=>[241, 422, 551, 659, 765, 866, 954, 1043, 1142, 1235, 1311, 1397, 1462]}, {"subject_area"=>"/Medicine and health sciences/Parasitic diseases", "average_usage"=>[320, 619, 774, 903, 1012, 1118, 1224, 1333, 1442, 1518, 1600, 1702, 1779]}, {"subject_area"=>"/Medicine and health sciences/Pediatrics", "average_usage"=>[248, 430, 563, 680, 778, 859, 949, 1017, 1115, 1199, 1281, 1364, 1431]}, {"subject_area"=>"/Medicine and health sciences/Tropical diseases", "average_usage"=>[327, 579, 720, 841, 955, 1064, 1151, 1250, 1336, 1437, 1514, 1586, 1677]}]}
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