Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates.

BACKGROUND: Reliable estimates of populations affected by diseases are necessary to guide efficient allocation of public health resources. Sickle haemoglobin (HbS) is the most common and clinically significant haemoglobin structural variant, but no contemporary estimates exist of the global populati...

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Κύριοι συγγραφείς: Piel, F, Patil, A, Howes, R, Nyangiri, O, Gething, P, Dewi, M, Temperley, W, Williams, T, Weatherall, D, Hay, S
Μορφή: Journal article
Γλώσσα:English
Έκδοση: 2013
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author Piel, F
Patil, A
Howes, R
Nyangiri, O
Gething, P
Dewi, M
Temperley, W
Williams, T
Weatherall, D
Hay, S
author_facet Piel, F
Patil, A
Howes, R
Nyangiri, O
Gething, P
Dewi, M
Temperley, W
Williams, T
Weatherall, D
Hay, S
author_sort Piel, F
collection OXFORD
description BACKGROUND: Reliable estimates of populations affected by diseases are necessary to guide efficient allocation of public health resources. Sickle haemoglobin (HbS) is the most common and clinically significant haemoglobin structural variant, but no contemporary estimates exist of the global populations affected. Moreover, the precision of available national estimates of heterozygous (AS) and homozygous (SS) neonates is unknown. We aimed to provide evidence-based estimates at various scales, with uncertainty measures. METHODS: Using a database of sickle haemoglobin surveys, we created a contemporary global map of HbS allele frequency distribution within a Bayesian geostatistical model. The pairing of this map with demographic data enabled calculation of global, regional, and national estimates of the annual number of AS and SS neonates. Subnational estimates were also calculated in data-rich areas. FINDINGS: Our map shows subnational spatial heterogeneities and high allele frequencies across most of sub-Saharan Africa, the Middle East, and India, as well as gene flow following migrations to western Europe and the eastern coast of the Americas. Accounting for local heterogeneities and demographic factors, we estimated that the global number of neonates affected by HbS in 2010 included 5,476,000 (IQR 5,291,000-5,679,000) AS neonates and 312,000 (294,000-330,000) SS neonates. These global estimates are higher than previous conservative estimates. Important differences predicted at the national level are discussed. INTERPRETATION: HbS will have an increasing effect on public health systems. Our estimates can help countries and the international community gauge the need for appropriate diagnoses and genetic counselling to reduce the number of neonates affected. Similar mapping and modelling methods could be used for other inherited disorders. FUNDING: The Wellcome Trust.
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spelling oxford-uuid:11acdfca-aac5-4703-adfe-1d5724211a252022-03-26T10:03:34ZGlobal epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:11acdfca-aac5-4703-adfe-1d5724211a25EnglishSymplectic Elements at Oxford2013Piel, FPatil, AHowes, RNyangiri, OGething, PDewi, MTemperley, WWilliams, TWeatherall, DHay, SBACKGROUND: Reliable estimates of populations affected by diseases are necessary to guide efficient allocation of public health resources. Sickle haemoglobin (HbS) is the most common and clinically significant haemoglobin structural variant, but no contemporary estimates exist of the global populations affected. Moreover, the precision of available national estimates of heterozygous (AS) and homozygous (SS) neonates is unknown. We aimed to provide evidence-based estimates at various scales, with uncertainty measures. METHODS: Using a database of sickle haemoglobin surveys, we created a contemporary global map of HbS allele frequency distribution within a Bayesian geostatistical model. The pairing of this map with demographic data enabled calculation of global, regional, and national estimates of the annual number of AS and SS neonates. Subnational estimates were also calculated in data-rich areas. FINDINGS: Our map shows subnational spatial heterogeneities and high allele frequencies across most of sub-Saharan Africa, the Middle East, and India, as well as gene flow following migrations to western Europe and the eastern coast of the Americas. Accounting for local heterogeneities and demographic factors, we estimated that the global number of neonates affected by HbS in 2010 included 5,476,000 (IQR 5,291,000-5,679,000) AS neonates and 312,000 (294,000-330,000) SS neonates. These global estimates are higher than previous conservative estimates. Important differences predicted at the national level are discussed. INTERPRETATION: HbS will have an increasing effect on public health systems. Our estimates can help countries and the international community gauge the need for appropriate diagnoses and genetic counselling to reduce the number of neonates affected. Similar mapping and modelling methods could be used for other inherited disorders. FUNDING: The Wellcome Trust.
spellingShingle Piel, F
Patil, A
Howes, R
Nyangiri, O
Gething, P
Dewi, M
Temperley, W
Williams, T
Weatherall, D
Hay, S
Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates.
title Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates.
title_full Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates.
title_fullStr Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates.
title_full_unstemmed Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates.
title_short Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates.
title_sort global epidemiology of sickle haemoglobin in neonates a contemporary geostatistical model based map and population estimates
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