Background Studies of the transmission dynamics of COVID-19 have depicted the rate, patterns, and predictions of cases of this pandemic disease. To combat transmission of the disease in India, the government declared a lockdown on March 25, 2020. Even after this strict lockdown was enacted nationwide, the number of COVID-19 cases increased and surpassed 450,000. A positive point to note is that the number of recovered cases began to slowly exceed that of active cases. The survival of patients, taking death as the event that varies by age group and sex, is noteworthy. Objective The aim of this study was to conduct a survival analysis to establish the variability in survivorship of patients with COVID-19 in India by age group and sex at different levels, that is, the national, state, and district levels. Methods The study period was taken from the date of the first reported case of COVID-19 in India, which was January 30, 2020, up to June 30, 2020. Due to the amount of underreported data and removal of missing columns, a total sample of 26,815 patients was considered. Kaplan-Meier survival estimation, the Cox proportional hazard model, and the multilevel survival model were used to perform the survival analysis. Results The Kaplan-Meier survival function showed that the probability of survival of patients with COVID-19 declined during the study period of 5 months, which was supplemented by the log rank test (P<.001) and Wilcoxon test (P<.001) to compare the survival functions. Significant variability was observed in the age groups, as evident from all the survival estimates; with increasing age, the risk of dying of COVID-19 increased. The Cox proportional hazard model reiterated that male patients with COVID-19 had a 1.14 times higher risk of dying than female patients (hazard ratio 1.14; SE 0.11; 95% CI 0.93-1.38). Western and Central India showed decreasing survival rates in the framed time period, while Eastern, North Eastern, and Southern India showed slightly better results in terms of survival. Conclusions This study depicts a grave scenario of decreasing survival rates in various regions of India and shows variability in these rates by age and sex. In essence, we can safely conclude that the critical appraisal of the survival rate and thorough analysis of patient data in this study equipped us to identify risk groups and perform comparative studies of various segments in India. International Registered Report Identifier (IRRID) RR2-10.1101/2020.08.01.20162115
The study of transmission dynamics of COVID-19, have depicted the rate, patterns and predictions of the pandemic cases. In order to combat the disease transmission in India, the Government had declared lockdown on the 25th of March. Even after a strict lockdown nationwide, the cases are increasing and have crossed 4.5 lakh positive cases. A positive point to be noted amongst all that the recovered cases are slowly exceeding the active cases. The survival of the patients, taking death as the event that varies over age groups and gender wise is noteworthy. This study aims in carrying out a survival analysis to establish the variability in survivorship among age groups and sex, at different levels, that is, national, state and district level. The open database of COVID-19 tracker (covid19india.org) of India has been utilized to fulfill the objectives of the study. The study period has been taken from the beginning of the first case which was on 30th Jan 2020 till 30th June. Due to the amount of under-reporting of data and dropping missing columns a total of 26,815 sample patients were considered. The entry point of each patient is different and event of interest is death in the study. Kaplan Meier survival estimation, Cox proportional hazard model and multilevel survival model has been used to perform survival analysis. Kaplan Meier survival function, shows that the probability of survival has been declining during the study period of five months. A significant variability has been observed in the age groups, as evident from all the survival estimates, with increasing age the risk of dying from COVID-19 increases. When Western and Central India show ever decreasing survival rate in the framed time period then Eastern , North Eastern and Southern India shows a slightly better picture in terms of survival. Maharashtra, Gujarat, Delhi, Rajasthan and West bengal showed alrmingly poor survival as well. This study has depicted a grave scenario of gradation of ever decreasing survival rates in various regions and shows the variability by age and gender.
BackgroundAge-appropriate weight or underweight is one of the normative indexes of physical development that describe the nutritional state of children. Northeast India has a wide range of sociocultural child-rearing activities due to the region's varied tribal and ethnic populations which in some or the other way affect the nutritional status among children in early ages. An attempt has been made to assess the prevalence and determine the risk of underweight among children in northeast region in India.MethodsThe present study is based on a publicly available National Family Health Survey (NFHS-4), 2015-16 data. Multilevel random intercept model approach has been used to investigate the impact of independent variables at different social hierarchical levels on the underweight status in the study population.ResultsChildren whose mother's level of education was no education or primary were 1.13 and 1.34 times more likely to be underweight respectively than those with secondary or higher level of education. The risk of being underweight were 2.4 times higher among children of 4 years of age compared to those with age less than 1 year. Poorest wealth quintile had 2.45 times higher chance of being underweight.ConclusionStudy suggests that education of mother’s education, child's sex, age, type of residence, social status, and household’s wealth index affect the underweight among children. Hence, to combat the situation in northeast states, policymakers must make policies with a strong reliance on communities with a higher prevalence and risk.
BACKGROUND Studies of the transmission dynamics of COVID-19 have depicted the rate, patterns, and predictions of cases of this pandemic disease. To combat transmission of the disease in India, the government declared a lockdown on March 25, 2020. Even after this strict lockdown was enacted nationwide, the number of COVID-19 cases increased and surpassed 450,000. A positive point to note is that the number of recovered cases began to slowly exceed that of active cases. The survival of patients, taking death as the event that varies by age group and sex, is noteworthy. OBJECTIVE The aim of this study was to conduct a survival analysis to establish the variability in survivorship of patients with COVID-19 in India by age group and sex at different levels, that is, the national, state, and district levels. METHODS The study period was taken from the date of the first reported case of COVID-19 in India, which was January 30, 2020, up to June 30, 2020. Due to the amount of underreported data and removal of missing columns, a total sample of 26,815 patients was considered. Kaplan-Meier survival estimation, the Cox proportional hazard model, and the multilevel survival model were used to perform the survival analysis. RESULTS The Kaplan-Meier survival function showed that the probability of survival of patients with COVID-19 declined during the study period of 5 months, which was supplemented by the log rank test (<i>P</i><.001) and Wilcoxon test (<i>P</i><.001) to compare the survival functions. Significant variability was observed in the age groups, as evident from all the survival estimates; with increasing age, the risk of dying of COVID-19 increased. The Cox proportional hazard model reiterated that male patients with COVID-19 had a 1.14 times higher risk of dying than female patients (hazard ratio 1.14; SE 0.11; 95% CI 0.93-1.38). Western and Central India showed decreasing survival rates in the framed time period, while Eastern, North Eastern, and Southern India showed slightly better results in terms of survival. CONCLUSIONS This study depicts a grave scenario of decreasing survival rates in various regions of India and shows variability in these rates by age and sex. In essence, we can safely conclude that the critical appraisal of the survival rate and thorough analysis of patient data in this study equipped us to identify risk groups and perform comparative studies of various segments in India. INTERNATIONAL REGISTERED REPORT RR2-10.1101/2020.08.01.20162115
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