Statistical modelling of genetic disorder in Nigeria: a study of sickle cell disease

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Lekia Nkpordee
Nduka Wonu

Abstract

This present work investigates trend analysis of genetic disorder in Nigeria a case study of Sickle Cell Disease (SCD). Four different trend models of time series were fitted such as; linear, quadratic, exponential and s-curve trend models on sickle cell disease cases in Nigeria (annual data set from 2010 to 2016). The best trend model was then identified using model accuracy measures [Mean Absolute Percentage (MAPE), Mean Absolute Deviation (MAD), & Mean Squared Deviation (MSD)]. The findings showed that of all three model accuracy methodologies tested, the quadratic and s-curve trend models compete favourably. The s-curve trend model, on the other hand, had the lowest MAPE and best fit the data. The s-curve trend model was used to produce a six-year projection of sickle cell disease cases in Nigeria and revealed that the number of sickle cell disease cases in the country (Nigeria) will decline during the following six years, from 2017 to 2022.

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How to Cite
Nkpordee, L., & Wonu, N. (2022). Statistical modelling of genetic disorder in Nigeria: a study of sickle cell disease. Faculty of Natural and Applied Sciences Journal of Scientific Innovations, 3(2), 10–19. Retrieved from https://fnasjournals.com/index.php/FNAS-JSI/article/view/27
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