We present an overview of the TREC-COVID Challenge, an information retrieval\n(IR) shared task to evaluate search on scientific literature related to\nCOVID-19. The goals of TREC-COVID include the construction of a pandemic search\ntest collection and the evaluation of IR methods for COVID-19. The challenge\nwas conducted over five rounds from April to July, 2020, with participation\nfrom 92 unique teams and 556 individual submissions. A total of 50 topics (sets\nof related queries) were used in the evaluation, starting at 30 topics for\nRound 1 and adding 5 new topics per round to target emerging topics at that\nstate of the still-emerging pandemic. This paper provides a comprehensive\noverview of the structure and results of TREC-COVID. Specifically, the paper\nprovides details on the background, task structure, topic structure, corpus,\nparticipation, pooling, assessment, judgments, results, top-performing systems,\nlessons learned, and benchmark datasets.\n