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The spatial epidemiology of sickle-cell anaemia in India
Sickle-cell anaemia (SCA) is a neglected chronic disorder of increasing global health importance, with India estimated to have the second highest burden of the disease. In the country, SCA is particularly prevalent in scheduled populations, which comprise the most socioeconomically disadvantaged com...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283872/ https://www.ncbi.nlm.nih.gov/pubmed/30523337 http://dx.doi.org/10.1038/s41598-018-36077-w |
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author | Hockham, Carinna Bhatt, Samir Colah, Roshan Mukherjee, Malay B. Penman, Bridget S. Gupta, Sunetra Piel, Frédéric B. |
author_facet | Hockham, Carinna Bhatt, Samir Colah, Roshan Mukherjee, Malay B. Penman, Bridget S. Gupta, Sunetra Piel, Frédéric B. |
author_sort | Hockham, Carinna |
collection | PubMed |
description | Sickle-cell anaemia (SCA) is a neglected chronic disorder of increasing global health importance, with India estimated to have the second highest burden of the disease. In the country, SCA is particularly prevalent in scheduled populations, which comprise the most socioeconomically disadvantaged communities. We compiled a geodatabase of a substantial number of SCA surveys carried out in India over the last decade. Using generalised additive models and bootstrapping methods, we generated the first India-specific model-based map of sickle-cell allele frequency which accounts for the district-level distribution of scheduled and non-scheduled populations. Where possible, we derived state- and district-level estimates of the number of SCA newborns in 2020 in the two groups. Through the inclusion of an additional 158 data points and 1.3 million individuals, we considerably increased the amount of data in our mapping evidence-base compared to previous studies. Highest predicted frequencies of up to 10% spanned central India, whilst a hotspot of ~12% was observed in Jammu and Kashmir. Evidence was heavily biased towards scheduled populations and remained limited for non-scheduled populations, which can lead to considerable uncertainties in newborn estimates at national and state level. This has important implications for health policy and planning. By taking population composition into account, we have generated maps and estimates that better reflect the complex epidemiology of SCA in India and in turn provide more reliable estimates of its burden in the vast country. This work was supported by European Union’s Seventh Framework Programme (FP7//2007–2013)/European Research Council [268904 – DIVERSITY]; and the Newton-Bhabha Fund [227756052 to CH] |
format | Online Article Text |
id | pubmed-6283872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62838722018-12-07 The spatial epidemiology of sickle-cell anaemia in India Hockham, Carinna Bhatt, Samir Colah, Roshan Mukherjee, Malay B. Penman, Bridget S. Gupta, Sunetra Piel, Frédéric B. Sci Rep Article Sickle-cell anaemia (SCA) is a neglected chronic disorder of increasing global health importance, with India estimated to have the second highest burden of the disease. In the country, SCA is particularly prevalent in scheduled populations, which comprise the most socioeconomically disadvantaged communities. We compiled a geodatabase of a substantial number of SCA surveys carried out in India over the last decade. Using generalised additive models and bootstrapping methods, we generated the first India-specific model-based map of sickle-cell allele frequency which accounts for the district-level distribution of scheduled and non-scheduled populations. Where possible, we derived state- and district-level estimates of the number of SCA newborns in 2020 in the two groups. Through the inclusion of an additional 158 data points and 1.3 million individuals, we considerably increased the amount of data in our mapping evidence-base compared to previous studies. Highest predicted frequencies of up to 10% spanned central India, whilst a hotspot of ~12% was observed in Jammu and Kashmir. Evidence was heavily biased towards scheduled populations and remained limited for non-scheduled populations, which can lead to considerable uncertainties in newborn estimates at national and state level. This has important implications for health policy and planning. By taking population composition into account, we have generated maps and estimates that better reflect the complex epidemiology of SCA in India and in turn provide more reliable estimates of its burden in the vast country. This work was supported by European Union’s Seventh Framework Programme (FP7//2007–2013)/European Research Council [268904 – DIVERSITY]; and the Newton-Bhabha Fund [227756052 to CH] Nature Publishing Group UK 2018-12-06 /pmc/articles/PMC6283872/ /pubmed/30523337 http://dx.doi.org/10.1038/s41598-018-36077-w Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Hockham, Carinna Bhatt, Samir Colah, Roshan Mukherjee, Malay B. Penman, Bridget S. Gupta, Sunetra Piel, Frédéric B. The spatial epidemiology of sickle-cell anaemia in India |
title | The spatial epidemiology of sickle-cell anaemia in India |
title_full | The spatial epidemiology of sickle-cell anaemia in India |
title_fullStr | The spatial epidemiology of sickle-cell anaemia in India |
title_full_unstemmed | The spatial epidemiology of sickle-cell anaemia in India |
title_short | The spatial epidemiology of sickle-cell anaemia in India |
title_sort | spatial epidemiology of sickle-cell anaemia in india |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283872/ https://www.ncbi.nlm.nih.gov/pubmed/30523337 http://dx.doi.org/10.1038/s41598-018-36077-w |
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