Statistical Quantification of the COVID-19 Pandemic’s Continuing Lingering Effect on Economic Losses in the Tourism Sector

The impact of the COVID-19 pandemic on the number of international tourist arrivals in the Republic of South Africa (RSA) is studied in this paper using the seasonal autoregressive integrated moving average (SARIMA) model comprising a pulse function covariate vector evaluated via trial and error as an exogenous variable (SARIMAX). This paper provides a methodological innovation that combines outlier detection with intervention quantification so that tourism academics and practitioners can correctly capture estimated economic losses caused by the COVID-19 pandemic and the response to it. In the pre-intervention modelling, four additive outliers and innovative outliers were detected and incorporated into the SARIMAX ( 1 , 1 , 1 ) ( 0 , 1 , 2 ) 12 model, which significantly lowered the model’s evaluation metrics, making it the best fitting pre-intervention model. Next, from March 2020 to June 2025 (end of dataset), it is shown that the estimated total losses amount to 7,328,919 tourists compared to if there been no pandemic. This means that the number of tourist arrivals in the RSA has not yet returned to the pre-COVID-19 forecasted path as of June 2025, indicating that the COVID-19 pandemic continues to have long-term negative effects on the RSA’s number of tourist arrivals. Therefore, more efforts must be focused on developing innovative and advanced statistical models to assist the RSA government and private entities in creating incentives for investment, planning more effectively, providing societies reliant on tourism with more resources, and creating suitable regulations that boost the economy through the tourism sector.