Coronavirus disease 2019 (COVID-19) will likely remain a major public health burden; accurate forecast of COVID-19 epidemic outcomes several months into the future is needed to support more proactive planning. Here, we propose strategies to address three major forecast challenges, i.e., error growth, the emergence of new variants, and infection seasonality. Using these strategies in combination we generate retrospective predictions of COVID-19 cases and mortality 6 months in the future for 10 representative US states during July 2020 to September 2022. The optimized forecast approach using all three strategies consistently outperformed a baseline forecast approach across different variant waves and locations, for all forecast targets; overall, probabilistic forecast accuracy improved by 64% and 38% and point prediction accuracy by 133% and 87% for cases and deaths, respectively. Given this superior forecast skill, the strategies could support sensible long-lead forecast of COVID-19 and possibly other infectious diseases.
