In this study, a time series modeling approach is used to determine an聽ARIMA model and advance counterfactual forecasting at a point of policy intervention. We consider monthly data of HIV/AIDS cases from the Ministry of Health (Copperbelt province) of Zambia, for the period 2010 to 2019 and have聽a total of 120 observations. Results indicate that ARIMA (1,聽0,聽0) is an adequate model which best fits the HIV/AIDS time series data and is, therefore, suitable for forecasting cases. The model predicts a reduction from an average of 3500 to 3177 representing 14.29% in HIV/AIDS cases from 2017 (year of policy activation) to 2019, but the actual recorded cases dropped from 3500 to 1514 accounting for 57.4% in the same time frame.
Moyo, E. , Shakalima, J. , Chambashi, G. , Muchinga, J. and Matindih, L. (2021) Modelling HIV/AIDS Cases in Zambia: A Comparative Study of the Impact of Mandatory HIV Testing.聽Open Journal of Statistics,聽11, 409-419. doi:聽10.4236/ojs.2021.113025.