Modelling and Forecasting Immunization against Measles Disease in Chad Using Artificial Neural Networks (ANN)
Abstract
In this research article, the ANN approach was
applied to analyze child immunization rate in Chad. 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 quite stable. The ANN (12, 12,
1) model projections suggest that
child immunization against measles in Chad is likely to range between 39% and
59% per year over the next decade. The government is encouraged to intensify child health
surveillance and control programs in line with our policy recommendations.
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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