Abstract Background To date computer models with multiple assumptions have focussed on predicting the incidence of symptomatic cases of COVID-19. Given emerging vaccines, the aim of this study was to provide simple methods for estimating the hidden prevalence of asymptomatic cases and levels of herd immunity to aid future immunization policy and planning. We applied the method in Ireland. Methods For large scale epidemics, indirect models for estimating prevalence have been developed. One such method is the benchmark multiplier method. A further method is back-calculation, which has been used successfully to produce estimates of the scale of a HIV infected population. The methods were applied from March to October 2020 and are applicable globally. Results Results demonstrated that the number of infected individuals was at least twice and possibly six times the number identified through testing. Our estimates ranged from ∼100 000 to 375 000 cases giving a ratio of 1–6 hidden cases for every known case within the study time frame. While both methods are subject to assumptions and limitations, it was interesting to observe that estimates corroborated government statements noting that 80% of people testing positive were asymptomatic. Conclusions As Europe has now endured several epidemic waves with the emergence globally of new variants, it essential that both policy makers and the public are aware of the scale of the hidden epidemic that may surround them. The need for social distancing is as important as ever as we await global immunization rollout.