Modelling and Forecasting Immunization against Measles Disease in Madagascar Using Artificial Neural Networks (ANN)
Abstract
In this research article, the ANN approach was
applied to assess child immunization against measles in Madagascar. 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 the series under consideration. The ANN (12, 12, 1) model
projections suggest that
child immunization against measles in Madagascar is likely to decline from 69%
in 2020 to about 62% by 2030. The
government of Madagascar is encouraged to intensify child health surveillance
and control programs, particularly adopting the suggested 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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