Using the ARIMA Model to forecast sexual and gender-based violence cases reported to a tertiary hospital in Lusaka, Zambia

Abstract

Introduction: sexual and gender-based violence (SGBV) is a global public health problem and women are disproportionally affected. Sexual and gender-based violence has an acute and chronic impact on health. We set out to apply autoregressive integrated moving average (ARIMA) models to make predictions on the number of SGBV cases reported to the Women and Newborn Hospital of the University Teaching Hospitals in Lusaka, Zambia.