Evolutionary Ecology of Infectious Disease Group, Peter Medawar Building for Pathogen Research, Department of Zoology, University of Oxford, Oxford, UK.
The George Institute for Global Health, Sydney, Australia.
Sci Rep. 2018 Dec 6;8(1):17685. doi: 10.1038/s41598-018-36077-w.
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].
镰状细胞贫血症(SCA)是一种被忽视的慢性疾病,其在全球的重要性日益增加,印度估计是该病负担第二高的国家。在该国,镰状细胞贫血症在预定人群中尤其普遍,这些人群构成了最社会经济地位不利的社区。我们汇编了过去十年在印度进行的大量镰状细胞贫血症调查的地理数据库。使用广义加性模型和自举方法,我们生成了第一个基于印度的镰状细胞等位基因频率模型地图,该地图考虑了预定和非预定人群的地区分布。在可能的情况下,我们根据这两个群体在 2020 年的新生儿数量,得出了州和地区级别的估计值。通过纳入另外 158 个数据点和 130 万人,与以前的研究相比,我们在制图证据基础中大大增加了数据量。高达 10%的最高预测频率涵盖了印度中部,而在查谟和克什米尔地区观察到了一个约 12%的热点。证据主要偏向预定人群,而非预定人群的证据仍然有限,这可能导致在国家和州一级对新生儿的估计存在相当大的不确定性。这对卫生政策和规划具有重要意义。通过考虑人口构成,我们生成了地图和估计值,这些地图和估计值更好地反映了印度镰状细胞贫血症的复杂流行病学,从而为该国庞大的镰状细胞贫血症负担提供了更可靠的估计。这项工作得到了欧盟第七框架计划(FP7//2007-2013)/欧洲研究理事会[268904-DIVERSITY]和牛顿-巴哈基金[227756052 用于 CH]的支持。