Modelling and Forecasting Immunization against Measles Disease in Philippines Using Artificial Neural Networks (ANN)
Abstract
In this research article, the ANN approach was applied to analyze child
immunization against measles in Philippines. The employed annual data covers
the period 1982-2019 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
immunization coverage in the country. The ANN (12, 12, 1) model projections
suggest that child immunization against measles in Philippines is likely to
decline to around 4% by 2030. The Philippines government is encouraged to
intensify child health surveillance and control programs in a manner that is
consistent with the policy directions suggested in this study.
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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