Global Burden of Sickle Cell Anaemia in Children under Five, 2010–2050: Modelling Based on Demographics, Excess Mortality, and Interventions
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{"title"=>"Global Burden of Sickle Cell Anaemia in Children under Five, 2010-2050: Modelling Based on Demographics, Excess Mortality, and Interventions", "type"=>"journal", "authors"=>[{"first_name"=>"Frédéric B.", "last_name"=>"Piel", "scopus_author_id"=>"56866735900"}, {"first_name"=>"Simon I.", "last_name"=>"Hay", "scopus_author_id"=>"7101875313"}, {"first_name"=>"Sunetra", "last_name"=>"Gupta", "scopus_author_id"=>"7407275054"}, {"first_name"=>"David J.", "last_name"=>"Weatherall", "scopus_author_id"=>"56911177400"}, {"first_name"=>"Thomas N.", "last_name"=>"Williams", "scopus_author_id"=>"35430527200"}], "year"=>2013, "source"=>"PLoS Medicine", "identifiers"=>{"sgr"=>"84881220584", "doi"=>"10.1371/journal.pmed.1001484", "pui"=>"369514193", "issn"=>"15491277", "pmid"=>"23874164", "isbn"=>"1549-1676 (Electronic)\\r1549-1277 (Linking)", "scopus"=>"2-s2.0-84881220584"}, "id"=>"9f12c813-7e69-3deb-bf5f-33f2b0315d6c", "abstract"=>"BACKGROUND: The global burden of sickle cell anaemia (SCA) is set to rise as a consequence of improved survival in high-prevalence low- and middle-income countries and population migration to higher-income countries. The host of quantitative evidence documenting these changes has not been assembled at the global level. The purpose of this study is to estimate trends in the future number of newborns with SCA and the number of lives that could be saved in under-five children with SCA by the implementation of different levels of health interventions.\\n\\nMETHODS AND FINDINGS: First, we calculated projected numbers of newborns with SCA for each 5-y interval between 2010 and 2050 by combining estimates of national SCA frequencies with projected demographic data. We then accounted for under-five mortality (U5m) projections and tested different levels of excess mortality for children with SCA, reflecting the benefits of implementing specific health interventions for under-five patients in 2015, to assess the number of lives that could be saved with appropriate health care services. The estimated number of newborns with SCA globally will increase from 305,800 (confidence interval [CI]: 238,400-398,800) in 2010 to 404,200 (CI: 242,500-657,600) in 2050. It is likely that Nigeria (2010: 91,000 newborns with SCA [CI: 77,900-106,100]; 2050: 140,800 [CI: 95,500-200,600]) and the Democratic Republic of the Congo (2010: 39,700 [CI: 32,600-48,800]; 2050: 44,700 [CI: 27,100-70,500]) will remain the countries most in need of policies for the prevention and management of SCA. We predict a decrease in the annual number of newborns with SCA in India (2010: 44,400 [CI: 33,700-59,100]; 2050: 33,900 [CI: 15,900-64,700]). The implementation of basic health interventions (e.g., prenatal diagnosis, penicillin prophylaxis, and vaccination) for SCA in 2015, leading to significant reductions in excess mortality among under-five children with SCA, could, by 2050, prolong the lives of 5,302,900 [CI: 3,174,800-6,699,100] newborns with SCA. Similarly, large-scale universal screening could save the lives of up to 9,806,000 (CI: 6,745,800-14,232,700) newborns with SCA globally, 85% (CI: 81%-88%) of whom will be born in sub-Saharan Africa. The study findings are limited by the uncertainty in the estimates and the assumptions around mortality reductions associated with interventions.\\n\\nCONCLUSIONS: Our quantitative approach confirms that the global burden of SCA is increasing, and highlights the need to develop specific national policies for appropriate public health planning, particularly in low- and middle-income countries. Further empirical collaborative epidemiological studies are vital to assess current and future health care needs, especially in Nigeria, the Democratic Republic of the Congo, and India.", "link"=>"http://www.mendeley.com/research/global-burden-sickle-cell-anaemia-children-under-five-20102050-modelling-based-demographics-excess-m", "reader_count"=>306, "reader_count_by_academic_status"=>{"Unspecified"=>4, "Professor > Associate Professor"=>8, "Librarian"=>3, "Researcher"=>45, "Student > Doctoral Student"=>15, "Student > Ph. D. Student"=>42, "Student > Postgraduate"=>40, "Student > Master"=>71, "Other"=>16, "Student > Bachelor"=>42, "Lecturer"=>7, "Lecturer > Senior Lecturer"=>6, "Professor"=>7}, "reader_count_by_user_role"=>{"Unspecified"=>4, "Professor > Associate Professor"=>8, "Librarian"=>3, "Researcher"=>45, "Student > Doctoral Student"=>15, "Student > Ph. D. Student"=>42, "Student > Postgraduate"=>40, "Student > Master"=>71, "Other"=>16, "Student > Bachelor"=>42, "Lecturer"=>7, "Lecturer > Senior Lecturer"=>6, "Professor"=>7}, "reader_count_by_subject_area"=>{"Unspecified"=>13, "Agricultural and Biological Sciences"=>43, "Arts and Humanities"=>1, "Business, Management and Accounting"=>4, "Veterinary Science and Veterinary Medicine"=>1, "Chemical Engineering"=>1, "Chemistry"=>6, "Computer Science"=>4, "Decision Sciences"=>2, "Economics, Econometrics and Finance"=>2, "Engineering"=>5, "Environmental Science"=>4, "Biochemistry, Genetics and Molecular Biology"=>17, "Nursing and Health Professions"=>14, "Mathematics"=>1, "Medicine and Dentistry"=>153, "Neuroscience"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>4, "Physics and Astronomy"=>3, "Psychology"=>8, "Social Sciences"=>14, "Immunology and Microbiology"=>3, "Linguistics"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>153}, "Social Sciences"=>{"Social Sciences"=>14}, "Decision Sciences"=>{"Decision Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Psychology"=>{"Psychology"=>8}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>13}, "Environmental Science"=>{"Environmental Science"=>4}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>4}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>5}, "Chemistry"=>{"Chemistry"=>6}, "Neuroscience"=>{"Neuroscience"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>43}, "Computer Science"=>{"Computer Science"=>4}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>14}, "Linguistics"=>{"Linguistics"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>17}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Colombia"=>1, "Cameroon"=>2, "United States"=>5, "United Kingdom"=>2, "Kenya"=>2, "Portugal"=>1, "Canada"=>3, "Brazil"=>1, "Italy"=>1, "Algeria"=>1, "Nigeria"=>6, "Jordan"=>1, "France"=>1}, "group_count"=>15}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1120405"], "description"=>"<p>Projections of estimated number of newborns with SCA (<i>y</i>-axis) between 2010 and 2050 for the DRC, India, and Nigeria (in blue); HbS regions: Eurasia, the Americas, sub-Saharan Africa, Southeast Asia, and Arab-India (in red; defined in Piel et al. <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-Piel2\" target=\"_blank\">[21]</a>); and globally (in green). The dark-shaded areas represent the uncertainty in the demographic data. The light-shaded areas show the uncertainty associated with our estimates of SCA frequency.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "newborns", "sca", "2010"], "article_id"=>746656, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.g005", "stats"=>{"downloads"=>2, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Projections_of_estimated_newborns_with_SCA_between_2010_and_2050_/746656", "title"=>"Projections of estimated newborns with SCA between 2010 and 2050.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120407"], "description"=>"a<p>Calculated as the difference between the number of newborns with SCA surviving in Scenario 2 (50% and 5% excess mortality in low- and middle-income countries and high-income countries, respectively) and in Scenario 1 (90% and 10% excess mortality in low- and middle-income countries and high-income countries, respectively). CIs are based on the interquartile range of the SCA estimates and the low- and high-fertility variants of the projected birth counts.</p>b<p>Calculated as the difference between the number of newborns with SCA surviving in Scenario 3 (10% and 0% excess mortality in low- and middle-income countries and high-income countries, respectively) and in Scenario 1 (90% and 10% excess mortality in low- and middle-income countries and high-income countries, respectively). CIs are based on the interquartile range of the SCA estimates and the low- and high-fertility variants of the projected birth counts.</p>c<p>Calculated as the difference between the number of newborns with SCA surviving in Scenario 4 (5% and 0% excess mortality in low- and middle-income countries and high-income countries, respectively) and in Scenario 1 (90% and 10% excess mortality in low- and middle-income countries and high-income countries, respectively). CIs are based on the interquartile range of the SCA estimates and the low- and high-fertility variants of the projected birth counts.</p>d<p>As defined at <a href=\"http://www.who.int/about/regions/en/index.html\" target=\"_blank\">http://www.who.int/about/regions/en/index.html</a>. AFRO, African Region; AMRO, Region of the Americas; EMRO, Eastern Mediterranean Region; EURO, European Region; SEARO, Southeast Asia Region; WPRO, Western Pacific Region.</p>e<p>As shown in Web Figure 8 of Web Appendix 2 of Piel et al. <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-Piel2\" target=\"_blank\">[21]</a>.</p>f<p>GNI<sub>pc</sub> in US dollars, based on the World Bank classification: low, US$1,005 or less; middle low, US$1,006–US$3,975; middle high, US$3,976–US$12,275; and high, US$12,276 or more.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "lives", "saved", "children", "sca", "comparing", "scenarios", "reduced", "excess", "quo", "measures"], "article_id"=>746658, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.t004", "stats"=>{"downloads"=>2, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimated_number_of_lives_saved_of_children_with_SCA_in_2015_in_2050_and_over_the_period_2015_8211_2050_when_comparing_scenarios_with_reduced_excess_mortality_Scenarios_2_3_and_4_to_a_status_quo_scenario_Scenario_1_based_on_the_implementation_of_measures/746658", "title"=>"Estimated number of lives saved of children with SCA in 2015, in 2050, and over the period 2015–2050 when comparing scenarios with reduced excess mortality (Scenarios 2, 3, and 4) to a status quo scenario (Scenario 1), based on the implementation of measures in 2015.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120408"], "description"=>"<p>Summary of the assumptions and limitations of this study.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "assumptions", "limitations"], "article_id"=>746659, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.t001", "stats"=>{"downloads"=>8, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_the_assumptions_and_limitations_of_this_study_/746659", "title"=>"Summary of the assumptions and limitations of this study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120409"], "description"=>"<p>Summary of the level of public health infrastructure and excess mortality considered per income class and for each of the four scenarios tested.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "excess", "considered", "scenarios"], "article_id"=>746660, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.t002", "stats"=>{"downloads"=>3, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_the_level_of_public_health_infrastructure_and_excess_mortality_considered_per_income_class_and_for_each_of_the_four_scenarios_tested_/746660", "title"=>"Summary of the level of public health infrastructure and excess mortality considered per income class and for each of the four scenarios tested.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120410"], "description"=>"<p>Complete data for all countries are presented in <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484.s002\" target=\"_blank\">Table S1</a>. Proportions per category are indicated for the predicted newborns with SCA. Relative changes are shown within parentheses.</p>a<p>Calculated as the product between the median SCA frequency based on the model outputs described in Piel et al. <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-Piel2\" target=\"_blank\">[21]</a> and the births per year for 2010–2015 from the 2010 revision of the UN World Population Prospects <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-United1\" target=\"_blank\">[22]</a>.</p>b<p>CIs based on the interquartile range of the SCA frequency estimates and the low- and high-fertility variants for birth counts.</p>c<p>Calculated as the product between the median SCA frequency based on the model outputs described in Piel et al. <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-Piel2\" target=\"_blank\">[21]</a>, assuming constant allele frequencies over the study period and using the data on births per year for 2050–2055 from the 2010 revision of the UN World Population Prospects <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-United1\" target=\"_blank\">[22]</a>.</p>d<p>Total estimated newborns with SCA born between 2010 and 2050.</p>e<p>As defined at <a href=\"http://www.who.int/about/regions/en/index.html\" target=\"_blank\">http://www.who.int/about/regions/en/index.html</a>. AFRO, African Region; AMRO, Region of the Americas; EMRO, Eastern Mediterranean Region; EURO, European Region; SEARO, Southeast Asia Region; WPRO, Western Pacific Region.</p>f<p>As shown in Web Figure 8 of Web Appendix 2 of Piel et al. <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-Piel2\" target=\"_blank\">[21]</a>.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "newborns", "sca", "2010", "2050", "affected", "countries", "hbs"], "article_id"=>746661, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.t003", "stats"=>{"downloads"=>6, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Projected_number_of_newborns_with_SCA_born_in_2010_and_2050_for_the_three_most_affected_countries_Nigeria_India_and_the_DRC_WHO_regions_HbS_regions_and_worldwide_/746661", "title"=>"Projected number of newborns with SCA born in 2010 and 2050 for the three most affected countries (Nigeria, India, and the DRC), WHO regions, HbS regions, and worldwide.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120412", "https://ndownloader.figshare.com/files/1120431", "https://ndownloader.figshare.com/files/1120432", "https://ndownloader.figshare.com/files/1120438"], "description"=>"<div><p>Background</p><p>The global burden of sickle cell anaemia (SCA) is set to rise as a consequence of improved survival in high-prevalence low- and middle-income countries and population migration to higher-income countries. The host of quantitative evidence documenting these changes has not been assembled at the global level. The purpose of this study is to estimate trends in the future number of newborns with SCA and the number of lives that could be saved in under-five children with SCA by the implementation of different levels of health interventions.</p><p>Methods and Findings</p><p>First, we calculated projected numbers of newborns with SCA for each 5-y interval between 2010 and 2050 by combining estimates of national SCA frequencies with projected demographic data. We then accounted for under-five mortality (U5m) projections and tested different levels of excess mortality for children with SCA, reflecting the benefits of implementing specific health interventions for under-five patients in 2015, to assess the number of lives that could be saved with appropriate health care services. The estimated number of newborns with SCA globally will increase from 305,800 (confidence interval [CI]: 238,400–398,800) in 2010 to 404,200 (CI: 242,500–657,600) in 2050. It is likely that Nigeria (2010: 91,000 newborns with SCA [CI: 77,900–106,100]; 2050: 140,800 [CI: 95,500–200,600]) and the Democratic Republic of the Congo (2010: 39,700 [CI: 32,600–48,800]; 2050: 44,700 [CI: 27,100–70,500]) will remain the countries most in need of policies for the prevention and management of SCA. We predict a decrease in the annual number of newborns with SCA in India (2010: 44,400 [CI: 33,700–59,100]; 2050: 33,900 [CI: 15,900–64,700]). The implementation of basic health interventions (e.g., prenatal diagnosis, penicillin prophylaxis, and vaccination) for SCA in 2015, leading to significant reductions in excess mortality among under-five children with SCA, could, by 2050, prolong the lives of 5,302,900 [CI: 3,174,800–6,699,100] newborns with SCA. Similarly, large-scale universal screening could save the lives of up to 9,806,000 (CI: 6,745,800–14,232,700) newborns with SCA globally, 85% (CI: 81%–88%) of whom will be born in sub-Saharan Africa. The study findings are limited by the uncertainty in the estimates and the assumptions around mortality reductions associated with interventions.</p><p>Conclusions</p><p>Our quantitative approach confirms that the global burden of SCA is increasing, and highlights the need to develop specific national policies for appropriate public health planning, particularly in low- and middle-income countries. Further empirical collaborative epidemiological studies are vital to assess current and future health care needs, especially in Nigeria, the Democratic Republic of the Congo, and India.</p><p><i>Please see later in the article for the Editors' Summary</i></p></div>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "sickle", "anaemia", "children", "excess"], "article_id"=>746663, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001484.s001", "https://dx.doi.org/10.1371/journal.pmed.1001484.s002", "https://dx.doi.org/10.1371/journal.pmed.1001484.s003", "https://dx.doi.org/10.1371/journal.pmed.1001484.s004"], "stats"=>{"downloads"=>13, "page_views"=>34, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Global_Burden_of_Sickle_Cell_Anaemia_in_Children_under_Five_2010_8211_2050_Modelling_Based_on_Demographics_Excess_Mortality_and_Interventions_/746663", "title"=>"Global Burden of Sickle Cell Anaemia in Children under Five, 2010–2050: Modelling Based on Demographics, Excess Mortality, and Interventions", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120391"], "description"=>"<p>Definition of variables: <i>A</i>, birth counts; <i>B</i>, frequency of SCA; <i>C</i>, mortality rate in under-five children; <i>D</i>, number of births with SCA; <i>E</i>, excess mortality in under-five children with SCA; <i>i</i>, scenario number, from 1 to 4; <i>X</i>, number of infants with SCA surviving; <i>Y</i>, number of lives of infants with SCA saved. U5, under five; UNPD, United Nations Population Division World Population Prospects <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-United1\" target=\"_blank\">[22]</a>.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "overview"], "article_id"=>746642, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.g001", "stats"=>{"downloads"=>3, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_overview_of_our_model_approach_/746642", "title"=>"Schematic overview of our model approach.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120398"], "description"=>"<p>Cartograms of the estimated number of newborns with SCA per country in 2010 (A), 2050 (B), and overall from 2010 to 2050 (C), based on data presented in <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484.s003\" target=\"_blank\">Table S2</a>. The estimates are based on the median of the posterior predictive distribution for SCA frequencies generated by our Bayesian geostatistical model described in Piel et al. <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-Piel2\" target=\"_blank\">[21]</a> and the medium-fertility variant of the birth projections from the 2010 revision of the UN World Population Prospects <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001484#pmed.1001484-United1\" target=\"_blank\">[22]</a>.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "newborns", "sca"], "article_id"=>746649, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.g002", "stats"=>{"downloads"=>5, "page_views"=>32, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cartograms_of_the_estimated_number_of_newborns_with_SCA_per_country_/746649", "title"=>"Cartograms of the estimated number of newborns with SCA per country.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120402"], "description"=>"<p>Limited to countries for which the estimated median SCA frequency in 2010 was higher than 0.001 and the estimated number of newborns with SCA in 2010 was higher than 100.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "ranking", "newborns", "sca", "2010"], "article_id"=>746653, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.g003", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Country_ranking_based_on_estimated_number_of_newborns_with_SCA_in_2010_and_2050_/746653", "title"=>"Country ranking based on estimated number of newborns with SCA in 2010 and 2050.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-16 03:18:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/1120403"], "description"=>"<p>Radar plots for the DRC (A), Nigeria (B), and India (C). bSCA, estimated number of newborns with SCA.</p>", "links"=>[], "tags"=>["genetics", "Human genetics", "Genetic counseling", "population genetics", "geography", "Human geography", "Spatial analysis", "Cartography", "epidemiology", "Disease mapping", "Genetic epidemiology", "Spatial epidemiology", "Global health", "hematology", "Hemoglobinopathies", "Sickle cell disease", "Public health", "Child health", "Health screening", "preventive medicine", "newborns", "under-five"], "article_id"=>746654, "categories"=>["Medicine", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Frédéric B. Piel", "Simon I. Hay", "Sunetra Gupta", "David J. Weatherall", "Thomas N. Williams"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001484.g004", "stats"=>{"downloads"=>2, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Radar_plots_of_newborns_with_SCA_gross_domestic_product_and_under_five_mortality_for_the_DRC_Nigeria_and_India_/746654", "title"=>"Radar plots of newborns with SCA, gross domestic product, and under-five mortality for the DRC, Nigeria, and India.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-16 03:18:22"}

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Relative Metric

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