Introduction and aims:To prevent the spread of coronavirus disease (COVID19) total lockdown is in place in India from 24 th March 2020 for 21 days. In this study, we aim to assess the impact of the duration of the lockdown on glycaemic control and diabetes-related complications. Materials and methods:A systematic search was conducted using Cochrane library. A simulation model was created using glycemic data from previous disasters (taken as similar in impact to current lockdown) taking baseline HBA1c and diabetes-related complications data from India-specific database. A multivariate regression analysis was conducted to analyse the relationship between the duration of lockdown and glycaemic targets & diabetes-related complications. Results:The predictive model was extremely robust (R2=0.99) and predicted outcomes for period of lockdown upto 90 days. The predicted increment in HBA1c from baseline at the end of 30 days and 45 days lockdown was projected as 2.26% & 3.68% respectively. Similarly, the annual predicted percentage increase in complication rates at the end of 30-day lockdown was 2.8% for non-proliferative diabetic retinopathy, 2.9% for proliferative diabetic retinopathy, 1.5% for retinal photocoagulation, 9.3% for microalbuminuria, 14.2% for proteinuria, 2.9% for peripheral neuropathy, 10.5% for lower extremity amputation, 0.9% for myocardial infarction, 0.5% for stroke and 0.5% for infections. Conclusion:The duration of lockdown is directly proportional to the worsening of glycaemic control and diabetes-related complications. Such increase in diabetes-related complications will put additional load on overburdened healthcare system, and also increase COVID19 infections in patients with such uncontrolled glycemia.

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Lockdown due to the Coronavirus disease 2019 (COVID 19) pandemic may cause weight gain and enhance the risk of type 2 diabetes mellitus (T2DM). We aimed to determine this risk in apparently nondiabetic individuals. Material methods: Baseline demographic and clinical data from 100 apparently non-diabetic household members (related or unrelated) of patients with type 2 diabetes mellitus were collected until 49 days of lockdown and analyzed using the XL-STAT statistical software. A two-pronged analytical strategy was employed. First, the metabolic risk profile related to age, sex, weight, family history, and exercise pattern was analyzed. This was followed by an assessment of the risk of developing type 2 diabetes using an established risk assessment engine. Results: There was a trend towards weight gain seen in 40% of the cohort, with 16% of the population experiencing a 2.1e5 kg weight increment. When all the risk parameters were analyzed together using the ADA risk engine, there was an increase in the ADA diabetes risk score in 7% of the population, with 6.66% in the high-risk group. There was a further increase in weight among 3% of the population who were already obese at baseline. Conclusion: We show an increased risk of T2MD consequent to weight gain during 49 days of lockdown in India.

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.

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