Background: Delay in treatment of aneurysmal subarachnoid haemorrhage (aSAH) appears to be common, contributing to the poor outcomes of patients. We currently have limited understanding of the causes of these delays. The aim of this systematic review was to identify delays in treatment of patients with aSAH, and to identify factors associated with treatment delay. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed. We searched four electronic databases (MEDLINE, EMBASE, Web of Science, and Google Scholar) for manuscripts published from January 1998 to 2020 using pre-designated search terms and search strategy. Main outcomes were duration of delays of any time intervals from onset of aSAH to definitive treatment and/or factors related to delays. Results: A total of 64 studies met study entry criteria. We identified 16 different time intervals in the pathway of aSAH patients and 17 groups of predictors to delay in treatment. Most studies measured time intervals between four major time points including time of onset, hospital admission, diagnosis, and receiving coiling or clipping. Methods to measure delay in treatment varied largely between studies, using cut-off timepoints or measured absolute time duration using mean or median. Demographic factors (age, sex, race, or socioeconomic status) were not associated with time to treatment. More severe aSAH reduced treatment delay in most studies. Pre-hospital delays (patients delay, late referral, late arrival of ambulance, being transferred between hospitals or arriving at the hospital outside of office hours) were associated with treatment delay. In-hospital factors (complication, having other procedures before definitive treatment, and type of treatment) had two-way association with treatment delay - both increasing and decreasing time to treatment. Conclusions: This review provides the first comprehensive understanding of types and predictors of delays in treatment of aSAH. There is significant opportunity to increase the comparability of aSAH time to treatment data, and to identify pre-hospital and in-hospital factors that currently delay treatment.