Impact of complete lock-down on total infection and death rates: A hierarchical cluster analysis

Introduction and AimsRetarding the spread of SARS-CoV-2 infection by preventive strategies is the first line of management. Several countries have declared a stringent lock-down in order to enforce social distancing and prevent the spread of infection. This analysis was conducted in an attempt to understand the impact of lock-down on infection and death rates over a period of time.Material and MethodsA validated database was used to generate data related to countries with declared lock-down. Simple regression analysis was conducted to assess the rate of change in infection and death rates. Subsequently, a k-means and hierarchical cluster analysis was done to identify the countries that performed similarly. Sweden and South Korea were included as counties without lock-down in a second-phase cluster analysis.ResultsThere was a significant 61% and 43% reduction in infection rates 1-week post lock-down in the overall and India cohorts, respectively, supporting its effectiveness. Countries with higher baseline infections and deaths fared poorly compared to those who declared lock-down early on. Sweden and South Korea fared equally well, as most lock-down countries stemmed the growth of infection and death.ConclusionLock-down has proven to be an effective strategy is slowing down the SARS-CoV-2 disease progression exponentially. However, lessons need to be learned from Sweden and South Korea on arresting the disease progression without imposing such stringent measures.