Abstract
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]
Highlights
Sickle-cell anaemia (SCA), which results from the inheritance of two copies of the sickle β-globin gene variant, is the most common form of sickle-cell disease (SCD)
Thirty-one surveys targeted populations belonging to Other Backward Classes (OBCs), 24 were carried out in General Classes (GCs) and one in OBCs and GCs together
The patterns in our maps are consistent with previous survey[10,22] and continuous maps[9], with the lowest allele frequencies predicted in the northeastern part of the country, the highest frequencies across a central belt, an area of high allele frequency in southern India, and a heterogeneous distribution of the βS allele across the whole country
Summary
Sickle-cell anaemia (SCA), which results from the inheritance of two copies of the sickle β-globin gene variant (βS), is the most common form of sickle-cell disease (SCD). Due to improved survival and population movements, the global burden of SCA is increasing[4], with the annual number of SCA newborns expected to increase from ~300,000 to more than 400,000 between 2010 and 20505. The majority of these births occur in Sub-Saharan Africa. Some of the highest βS allele frequencies have been reported in Indian populations[6,7,8], and India has been ranked the second worst affected country in terms of predicted SCA births, with 42 016 (interquartile range, IQR: 35 347–50 919) babies estimated to be born with SCA in 20109. Public and private institutions in India have made a remarkable effort to quantify SCA prevalence in different parts of the country, ranging from village-level prevalence surveys to state-wide screening programmes (e.g. Patel et al, and Patra et al.[23,24])
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