Prediction of TB Incidence in Cambodia Using the Multilayer Perceptron Neural Network
Abstract
Cambodia is among the 30 countries in the World with high TB disease
burden. Modelling and forecasting the incidence of the disease will help in
planning and responding to the epidemic appropriately and timeously. In this
research paper, the ANN approach was applied to analyze TB incidence in
Cambodia. The employed annual data covers the period 2000-2018 and the
out-of-sample period ranges over the period 2019-2023. The residuals and
forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate
that the model is stable in forecasting TB incidence in Cambodia. The model
predictions suggest that TB incidence will continue to decline but will still
remain high around 290 cases/100000 populations/year. We implore the government
to intensify TB surveillance and control programs, allocate more financial
resources towards TB/HIV program and continue health education among
communities to curb the spread of TB.
Country : Zimbabwe
1 Dr. Smartson. P. NYONI2 Thabani NYONI
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
Department of Economics, University of Zimbabwe, Harare, Zimbabwe
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