Modelling and Forecasting Immunization against Measles Disease in Djibouti Using Artificial Neural Networks (ANN)

Abstract

In this research article, the ANN approach was applied to analyze child immunization rate in Djibouti. 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 very stable. The ANN (12, 12, 1) model projections suggest that child immunization against measles in Djibouti is likely to remain around 90% per year over the next decade. The government is encouraged to intensify child health surveillance and control programs in the country. This can be specifically done by adopting the suggested policy recommendations.

Country : Zimbabwe

1 Mr. Takudzwa. C. Maradze2 Dr. Smartson. P. NYONI3 Mr. Thabani NYONI

  1. Independent Researcher, Harare, Zimbabwe
  2. ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
  3. SAGIT Innovation Center, Harare, Zimbabwe

IRJIET, Volume 5, Issue 3, March 2021 pp. 449-452

doi.org/10.47001/IRJIET/2021.503077

References

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