Search

Purpose We describe here a multicentric community-dwelling cohort of older adults (>60 years of age) established to estimate incidence, study risk factors, healthcare utilisation and economic burden associated with influenza and respiratory syncytial virus (RSV) in India.Participants The four sites of this cohort are in northern (Ballabgarh), southern (Chennai), eastern (Kolkata) and western (Pune) parts of India. We enrolled 5336 participants across 4220 households and began surveillance in July 2018 for viral respiratory infections with additional participants enrolled annually. Trained field workers collected data about individual-level and household-level risk factors at enrolment and quarterly assessed frailty and grip strength. Trained nurses surveilled weekly to identify acute respiratory infections (ARI) and clinically assessed individuals to diagnose acute lower respiratory infection (ALRI) as per protocol. Nasal and oropharyngeal swabs are collected from all ALRI cases and one-fifth of the other ARI cases for laboratory testing. Cost data of the episode are collected using the WHO approach for estimating the economic burden of seasonal influenza. Handheld tablets with Open Data Kit platform were used for data collection.Findings to date The attrition of 352 participants due to migration and deaths was offset by enrolling 680 new entrants in the second year. All four sites reported negligible influenza vaccination uptake (0.1%–0.4%), low health insurance coverage (0.4%–22%) and high tobacco use (19%–52%). Ballabgarh had the highest proportion (54.4%) of households in the richest wealth quintile, but reported high solid fuel use (92%). Frailty levels were highest in Kolkata (11.3%) and lowest in Pune (6.8%). The Chennai cohort had highest self-reported morbidity (90.1%).Future plans The findings of this cohort will be used to inform prioritisation of strategies for influenza and RSV control for older adults in India. We also plan to conduct epidemiological studies of SARS-CoV-2 using this platform.

Background & Objectives: India has been reporting the cases of coronavirus disease 2019 (COVID-19) since January 30, 2020. The Indian Council of Medical Research (ICMR) formulated and established laboratory surveillance for COVID-19. In this study, an analysis of the surveillance data was done to describe the testing performance and descriptive epidemiology of COVID-19 cases by time, place and person., Methods: The data were extracted from January 22 to April 30, 2020. The frequencies of testing performance were described over time and by place. We described cases by time (epidemic curve by date of specimen collection; seven-day moving average), place (area map) and person (attack rate by age, sex and contact status), and trends were represented along with public health measures and events., Results: Between January 22 and April 30, 2020, a total of 1,021,518 individuals were tested for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Testing increased from about 250 individuals per day in the beginning of March to 50,000 specimens per day by the end of April 2020. Overall, 40,184 (3.9%) tests were reported positive. The proportion of positive cases was highest among symptomatic and asymptomatic contacts, 2-3-fold higher than among those with severe acute respiratory infection, or those with an international travel history or healthcare workers. The attack rate (per million) by age was highest among those aged 50-69 yr (63.3) and was lowest among those under 10 yr (6.1). The attack rate was higher among males (41.6) than females (24.3). The secondary attack rate was 6.0 per cent. Overall, 99.0 per cent of 736 districts reported testing and 71.1 per cent reported COVID-19 cases., Interpretation & Conclusions: The coverage and frequency of ICMR's laboratory surveillance for SARS-CoV-2 improved over time. COVID-19 was reported from most parts of India, and the attack rate was more among men and the elderly and common among close contacts. Analysis of the data indicates that for further insight, additional surveillance tools and strategies at the national and sub-national levels are needed., Competing Interests: None

Background: In this work, we implement a data-driven approach using an aggregation of several analytical methods to study the characteristics of COVID-19 daily infection and death time series and identify correlations and characteristic trends that can be corroborated to the time evolution of this disease. The datasets cover twelve distinct countries across six continents, from January 22, 2020 till March 1, 2022. This time span is partitioned into three windows: (1) pre-vaccine, (2) post-vaccine and pre-omicron (BA.1 variant), and (3) post-vaccine including post-omicron variant. This study enables deriving insights into intriguing questions related to the science of system dynamics pertaining to COVID-19 evolution. Methods: We implement a set of several distinct analytical methods for: (a) statistical studies to estimate the skewness and kurtosis of the data distributions; (b) analyzing the stationarity properties of these time series using the Augmented Dickey-Fuller (ADF) tests; (c) examining co-integration properties for the non-stationary time series using the Phillips-Ouliaris (PO) tests; (d) calculating the Hurst exponent using the rescaled-range (R/S) analysis, along with the Detrended Fluctuation Analysis (DFA), for self-affinity studies of the evolving dynamical datasets. Results: We notably observe a significant asymmetry of distributions shows from skewness and the presence of heavy tails is noted from kurtosis. The daily infection and death data are, by and large, nonstationary, while their corresponding log return values render stationarity. The self-affinity studies through the Hurst exponents and DFA exhibit intriguing local changes over time. These changes can be attributed to the underlying dynamics of state transitions, especially from a random state to either mean-reversion or long-range memory/persistence states. Conclusions: We conduct systematic studies covering a widely diverse time series datasets of the daily infections and deaths during the evolution of the COVID-19 pandemic. We demonstrate the merit of a multiple analytics frameworks through systematically laying down a methodological structure for analyses and quantitatively examining the evolution of the daily COVID-19 infection and death cases. This methodology builds a capability for tracking dynamically evolving states pertaining to critical problems. [ABSTRACT FROM AUTHOR]

Study shows that COVID-19 cases, deaths and recoveries vary in macro level. Geographical phenomena may act as potential controlling factor. The present paper investigates spatial pattern of COVID-19 cases and deaths in West Bengal (WB), India and assumes Kolkata is the source region of this disease in WB. Thematic maps on COVID related issues are prepared with the help of QGIS 3.10 software. As on 15th January 2021, WB has 564032 number of COVID-19 cases which is 0.618% to the total population of the state. However, the COVID-19 case for India is 0.843% and for world is 1.341% to its total population. Lorenz Curve shows skewed distribution of the COVID-19 cases in WB. 17 (90%) districts hold 84.11% of the total population and carry 56.30% of the total COVID-19 cases. However, the remaining two districts—Kolkata and North 24 Parganas—hold remaining 43.70% COVID-19 cases. Correlation coefficient with COVID-19 cases and Population Density, Urban Population and Concrete Roof of their house are significant at 1% level of significance. [ABSTRACT FROM AUTHOR]

Introduction Rotavirus infection accounts for 39% of under-five diarrhoeal deaths globally and 22% of these deaths occur in India. Introduction of rotavirus vaccine in a national immunisation programme is considered to be the most effective intervention in preventing severe rotavirus disease. In 2016, India introduced an indigenous rotavirus vaccine (Rotavac) into the Universal Immunisation Programme in a phased manner. This paper describes the protocol for surveillance to monitor the performance of rotavirus vaccine following its introduction into the routine childhood immunisation programme. Methods An active surveillance system was established to identify acute gastroenteritis cases among children less than 5 years of age. For all children enrolled at sentinel sites, case reporting forms are completed and a copy of vaccination record and a stool specimen obtained. The forms and specimens are sent to the referral laboratory for data entry, analysis, testing and storage. Data from sentinel sites in states that have introduced rotavirus vaccine into their routine immunisation schedule will be used to determine rotavirus vaccine impact and effectiveness. Ethics and dissemination The Institutional Review Board of Christian Medical College, Vellore, and all the site institutional ethics committees approved the project. Results will be disseminated in peer-reviewed journals and with stakeholders of the universal immunisation programme in India. [ABSTRACT FROM AUTHOR]

Objective: To extend a nation-wide rotavirus surveillance network in India, and to generate geographically representative data on rotaviral disease burden and prevalent strains. Design: Hospital-based surveillance. Setting: A comprehensive multicenter, multi-state hospital based surveillance network was established in a phased manner involving 28 hospital sites across 17 states and two union territories in India. Patients: Cases of acute diarrhea among children below 5 years of age admitted in the participating hospitals. Results: During the 28-month study period between September 2012 and December 2014, 11898 children were enrolled and stool samples from 10207 children admitted with acute diarrhea were tested; 39.6% were positive for rotavirus. Highest positivity was seen in Tanda (60.4%) and Bhubaneswar (60.4%) followed by Midnapore (59.5%). Rotavirus infection was seen more among children aged below 2 years with highest (46.7%) positivity in the age group of 12-23 months. Cooler months of September-February accounted for most of the rotavirus-associated gastroenteritis, with highest prevalence seen during December-February (56.4%). 64% of rotavirus-infected children had severe to very severe disease. G1 P[8] was the predominant rotavirus strain (62.7%) during the surveillance period. Conclusions: The surveillance data highlights the high rotaviral disease burden in India. The network will continue to be a platform for monitoring the impact of the vaccine. [ABSTRACT FROM AUTHOR]

Objective: To estimate the burden of rotavirus-associated gastroenteritis in India. Methods: Hospital-based surveillance network was established, with clinical evaluation and laboratory testing for rotavirus among children aged below 5 years hospitalized with acute gastroenteritis. Results: Between September 2012 and December 2014, stool samples from 10207 children were tested and rotavirus was detected in 39.6% of cases. Infections were more commonly seen among younger children (<2 years). Detection rates were higher during cooler months of September-February. Among rotavirus infected-children, 64.0% had severe or very severe disease. G1P[8] was the predominant rotavirus genotype (62.7%) observed during the surveillance period. Conclusions: Surveillance data highlights the high rotavirus disease burden and emphasizes the need for close monitoring to reduce morbidity and mortality associated with rotavirus gastroenteritis in India. [ABSTRACT FROM AUTHOR]

Objective: To analyze variation in rotavirus-positivity using simple alternative statistical measures. Methods: Hospital-based rotavirus surveillance among children admitted with acute gastroenteritis between 2005 and 2009. Prevalence, adjusted proportions and symmetrized index were calculated. Results: Rotavirus prevalence was 40% (range 37% - 44%). Adjusted proportion analysis revealed higher level of deviation from annual prevalence in seasons (December-February and September-November); age groups (<12 months and 12-23 months) and regions (East and South). Analysis of symmetrized index revealed higher estimates of variation in all years, except in 2006. Conclusion: Proposed statistical measures are useful as refined measures to study extent of disease spread in surveillance programmes, aiding evaluation of the load and pattern of disease burden in different regions over time. [ABSTRACT FROM AUTHOR]

Objective: To estimate the burden of rotavirus-associated gastroenteritis in India., Methods: Hospital based surveillance network was established, with clinical evaluation and laboratory testing for rotavirus among children aged below 5 years hospitalized with acute gastroenteritis., Results: Between September 2012 and December 2014, stool samples from 10207 children were tested and rotavirus was detected in 39.6% of cases. Infections were more commonly seen among younger children (<2 years). Detection rates were higher during cooler months of September February. Among rotavirus infected children, 64.0% had severe or very severe disease. G1P[8] was the predominant rotavirus genotype (62.7%) observed during the surveillance period., Conclusions: Surveillance data highlights the high rotavirus disease burden and emphasizes the need for close monitoring to reduce morbidity and mortality associated with rotavirus gastroenteritis in India.