Given the rapid spread of the COVID-19 virus, the State has had to respond rapidly and quite severely to flatten the curve and slow the spread of the virus. This has had significant implications for many aspects of life with differential impacts across the population. The lack of timely available data constrains the estimation of the scale and direction of recent changes in the income distribution, which in turn constrain policymakers seeking to monitor such developments. We overcome the lack of data by proposing a dynamic calibrated microsimulation approach to generate counterfactual income distributions as a function of more timely external data than is available in dated income surveys. We combine nowcasting methods using publicly available data and a household income generation model to perform the first calibrated simulation based upon actual data aiming to assess the distributional implications of the COVID-19 crisis in Ireland. We extend the standard definition of disposable income by adjusting for work-related expenditure, housing costs and capital losses. We find that market incomes decreased along the distribution of disposable income, but decreases in euro terms were more pronounced at the top than at the bottom. Despite this, inequality in market incomes as measured by the Gini coefficient increased over the crisis. Once we account for the decline in housing and work-related expenses, households situated among the bottom 70% of the distribution actually improved their financial situation on average, whereas losses are recorded for the top 30%.