Modelling and Forecasting Immunization against Measles Disease in Nigeria Using Artificial Neural Networks (ANN)
Abstract
In this research article, the ANN approach was
applied to analyze child immunization against measles in Nigeria. The employed
annual data covers the period 1984-2019 and the out-of-sample period ranges
over the period 2020-2030. The residuals and forecast evaluation criteria
(Error, MSE and MAE) of the applied model indicate that the model is stable in
forecasting child immunization coverage in the country. The ANN (12, 12, 1)
model projections suggest that
immunization against measles in Nigeria is likely to decline from 51% in 2020
to about 23% by 2030.The
Nigerian government is encouraged to intensify child
health surveillance and control programs, in line with our policy
prescriptions.
Country : Zimbabwe
1 Mr. Takudzwa. C. Maradze2 Dr. Smartson. P. NYONI3 Mr. Thabani NYONI
Independent Researcher, Harare, Zimbabwe
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
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