Impact of complete lockdown on total infection and death rates: A hierarchical cluster analysis

Abstract

Introduction and Aims: Retarding the spread of SARS-CoV-2 infection by preventive strategies is the first line of management. Several countries have declared a stringent lockdown in order to enforce social distancing and prevent the spread of infection. This analysis was conducted in an attempt to understand the impact of lockdown on infection and death rates over a period of time in countries with declared lock-down. Material and methods: A validated database was used to generate data related to countries with declared lockdown. 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 lockdown in a secondphase cluster analysis. Results: There was a significant 61% and 43% reduction in infection rates 1-week post lockdown in the overall and India cohorts, respectively, supporting its effectiveness. Countries with higher baseline infections and deaths (Spain, Germany, Italy, UK, and France-cluster 1) fared poorly compared to those who declared lockdown early on (Belgium, Austria, New Zealand, India, Hungary, Poland and Malaysia-cluster 2). Sweden and South Korea, countries without lock-down, fared as good as the countries in cluster 2. Conclusion: Lockdown has proven to be an effective strategy is slowing down the SARS-CoV-2 disease progression (infection rate and death) exponentially. The success story of non-lock-down countries (Sweden and South Korea) need to be explored in detail, to identify the variables responsible for the positive results.

The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

“…Another group of studies have used empirical data to retrospectively examine whether NPIs have been effective in reducing transmission, using either statistical methods or mechanistic epidemiological models. Many such studies look at single interventions such as travel restrictions (34) or "lockdowns" (35,36) . Hence they are less useful to policy-makers wanting to establish which of a basket of NPIs are most effective.…”

A cross sectional study reveals severe disruption in glycemic control in people with diabetes during and after lockdown in India

“…With no doubts, lockdown measures and mobility restrictions were found effective to control the spread of COVID-19 [ 24 ], but, at the same time, showing their harmful consequences on prevention and control of diabetes and other NCDs [ 25 ]. Barone et al., reported that stricter measures against the pandemic may lead to present and future severe impact on diabetes care in South and Central America [ 26 ].…”

Preliminary Trajectories in Dietary Behaviors during the COVID-19 Pandemic: A Public Health Call to Action to Face Obesity

“…Globally, as of 19 July 2020, there were 14,043,176 confirmed cases of Coronavirus Disease (COVID-19) reported to the World Health Organization (WHO), including 597,583 deaths [ 1 ]. Many countries imposed a stringent lockdown in order to enforce social distancing and prevent the spread of infection [ 2 ]. The use of social distancing, face masks, gloves, and other individual protection measures is having a massive impact on reducing the current peak of active cases but, as recently demonstrated, over time, a decreasing sense of alarm about the pandemic may contribute to a new, larger second wave of epidemics [ 3 ].…”