The profound impact of the coronavirus disease 2019 (COVID-19) pandemic on global tourism activity has rendered forecasts of tourism demand obsolete. Accordingly, scholars have begun to seek the best methods to predict the recovery of tourism from the devastating effects of COVID-19. In this study, econometric and judgmental methods were combined to forecast the possible paths to tourism recovery in Hong Kong. The autoregressive distributed lag-error correction model was used to generate baseline forecasts, and Delphi adjustments based on different recovery scenarios were performed to reflect different levels of severity in terms of the pandemic's influence. These forecasts were also used to evaluate the economic effects of the COVID-19 pandemic on the tourism industry in Hong Kong. Display omitted •A mixed approach is proposed to forecast tourism demand in light of COVID-19.•Quantitative methods are integrated with qualitative, judgmental adjustments.•The ARDL-ECM is used to produce baseline forecasts of tourist arrivals to Hong Kong.•A scenario-based Delphi approach is used to adjust the forecasts in view of crises.•Forecasting recovery potential and tourism income losses benefits crisis management.