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Thalassemia in the United Arab Emirates: Why it can be prevented but not eradicated

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  • Sehjeong Kim
  • Abdessamad Tridane

Abstract

Thalassemia is a genetic blood disorder that causes abnormal hemoglobin. Hemoglobin is a protein in red blood cells that carries oxygen and is made of two proteins from four α-globin genes and two β-globin genes. A defect in one or more of these genes causes thalassemia. The treatment of thalassemia mostly depends on life-long blood transfusions and removal of excessive iron from the blood stream. Such tremendous blood consumption puts pressure on the national blood stock in many countries. In particular, in the United Arab Emirates (UAE), various forms of thalassemia prevention have been used and hence, the substantial reduction of the thalassemia major population has been achieved. However, the thalassemia carrier population still remains high, which leads to the potential increase in the thalassemia major population through carrier-carrier marriages. In this work, we investigate the long-term impact and efficacy of thalassemia prevention measures via mathematical modeling at a population level. To our best knowledge, this type of assessment has not been done before and there is no mathematical model that has investigated such a problem for thalassemia or any blood disorders at a population level. By using UAE data, we perform numerical simulations of our model and conduct sensitivity analysis of parameter values to see which parameter values affect most the dynamics of our model. We discover that the prevention measures can contribute to reduce the prevalence of the disease only in the short term but not eradicate the disease in the long term.

Suggested Citation

  • Sehjeong Kim & Abdessamad Tridane, 2017. "Thalassemia in the United Arab Emirates: Why it can be prevented but not eradicated," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-13, January.
  • Handle: RePEc:plo:pone00:0170485
    DOI: 10.1371/journal.pone.0170485
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    References listed on IDEAS

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    1. Soetaert, Karline & Petzoldt, Thomas, 2010. "Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i03).
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