question: AIM: To use theory and practice to show how disease progression and regression can be described pre- and post-lockdown using an attack-sustain-decline-respite (ASDR) model and investigate how pre-lockdown disease prevalence and household size impacts on the effectiveness of lockdown. MATERIALS AND METHODS: Computed tomography (CT) scans from major trauma patients (considered as a random population sample) from the radiology department of St George's University Hospitals NHS Trust, London, have been used to explore COVID-19 disease at the population level. RESULTS: At lockdown on 23 March 2020 in the catchment area of St George's University Hospitals NHS Trust, an earlier paper showed that there was a high prevalence of disease of >20%. With further follow-up and at the end of lockdown, it have been now estimated that around 57% of the population had been affected, which was similar to that predicted from a simple model based on average household size and prevalence at lockdown. With an average household size of around three persons, there was a 2-week sustain period and a 5-week decline period before the prevalence of the disease returned to background levels. CONCLUSIONS: The present results suggest that the effect of lockdown is dependent on the disease prevalence at the start of lockdown and the average household size. It may therefore be important to lockdown early in an area with a high average household size. This paper is the second in a series of papers to show how radiology measurements of major trauma patients can be used to help monitor the spread of the COVID-19 pandemic.