scholarly journals Epidemiology and transmission dynamics of COVID-19 in two Indian states

Science ◽  
2020 ◽  
Vol 370 (6517) ◽  
pp. 691-697 ◽  
Author(s):  
Ramanan Laxminarayan ◽  
Brian Wahl ◽  
Shankar Reddy Dudala ◽  
K. Gopal ◽  
Chandra Mohan B ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Andhra Pradesh ◽  
Case Fatality ◽  
Control Measures ◽  
Primary Data ◽  
Demographic Differences ◽  
Indian States ◽  
Low Resource ◽  
High Incidence ◽  
Transmission Pathways

Although most cases of coronavirus disease 2019 (COVID-19) have occurred in low-resource countries, little is known about the epidemiology of the disease in such contexts. Data from the Indian states of Tamil Nadu and Andhra Pradesh provide a detailed view into severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission pathways and mortality in a high-incidence setting. Reported cases and deaths have been concentrated in younger cohorts than would be expected from observations in higher-income countries, even after accounting for demographic differences across settings. Among 575,071 individuals exposed to 84,965 confirmed cases, infection probabilities ranged from 4.7 to 10.7% for low-risk and high-risk contact types, respectively. Same-age contacts were associated with the greatest infection risk. Case fatality ratios spanned 0.05% at ages of 5 to 17 years to 16.6% at ages of 85 years or more. Primary data from low-resource countries are urgently needed to guide control measures.

scholarly journals Epidemiology and transmission dynamics of COVID-19 in two Indian states

2020 ◽  
Author(s):  
Ramanan Laxminarayan ◽  
Brian Wahl ◽  
Shankar Reddy Dudala ◽  
K Gopal ◽  
Chandra Mohan ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Andhra Pradesh ◽  
Case Fatality ◽  
Control Measures ◽  
Contact Tracing ◽  
Primary Data ◽  
Indian States ◽  
Middle Income ◽  
Time To Death ◽  
Middle Income Countries

Although most COVID-19 cases have occurred in low-resource countries, there is scarce information on the epidemiology of the disease in such settings. Comprehensive SARS-CoV-2 testing and contact-tracing data from the Indian states of Tamil Nadu and Andhra Pradesh reveal stark contrasts from epidemics affecting high-income countries, with 92.1% of cases and 59.7% of deaths occurring among individuals <65 years old. The per-contact risk of infection is 9.0% (95% confidence interval: 7.5-10.5%) in the household and 2.6% (1.6-3.9%) in the community. Superspreading plays a prominent role in transmission, with 5.4% of cases accounting for 80% of infected contacts. The case-fatality ratio is 1.3% (1.0-1.6%), and median time-to-death is 5 days from testing. Primary data are urgently needed from low- and middle-income countries to guide locally-appropriate control measures.

Current Status of Ground Water Arsenic Contamination in India and Recent Advancements in Removal Techniques from Drinking Water

2016 ◽  
Vol 2 (1-2) ◽  
Author(s):  
Seema Mishra ◽  
Sanjay Dwivedi ◽  
Amit Kumar ◽  
Jürgen Mattusch ◽  
R.D. Tripathi
Keyword(s):  
Drinking Water ◽  
Ground Water ◽  
Tamil Nadu ◽  
Andhra Pradesh ◽  
South India ◽  
North India ◽  
Current Status ◽  
Indian States ◽  
Jammu And Kashmir ◽  
The Government

India is consisting of 29 states and 7 union territories, including a national capital, Delhi. Elevated concentrations (>10 g l ) of arsenic (As) in ground water (GW)  -1 of many states of India have become a major concern in recent years. Up to now about 0.2 million GW samples have been analyzed for As contamination from all over India by various researchers and Government agencies. About 90% of these cover only the Eastern part of India while several states and UTs are still unexplored. However, from the available data, GW of eighteen Indian states and three union territories has been found to be As contaminated to different extents through natural or anthropogenic origin. Among these, As >300 μg l has been reported from at least one locality from fourteen states. The -1 maximum level of As (7350 μg l ) in GW has been reported from a highly industrialized -1 area, Patancheru in Medak district of Andhra Pradesh. However, the gravity of problem is more in West Bengal followed by Bihar and Uttar Pradesh. Five out of eight North-Eastern states are also affected by As contamination. Manipur is ranked first and Assam as second followed by Arunachal Pradesh, Tripura and Nagaland. The GW in these regions is naturally As enriched, and therefore wide spatial distribution of As has been found in these areas. In North India, Punjab and Haryana and in South India, Andhra Pradesh and Karnataka are suffering with GW As contamination. Low level of As (up to 17 μg l ) has also -1 been reported in Tamil Nadu from South India. Many of the states like Jammu and Kashmir, Uttarakhand, Odisha, Gujrat, Kerala, Telengana, Goa etc. are still unexplored for GW As contamination. Thus, according to current reports out of 640 districts in India, 141 are As affected (As >10 g l-1), among them 120 are above 50 g l-1. Considering its severity, the issue of As contamination in drinking water has been taken up by the Government of India and mitigation efforts are being initiated. In order to provide safe drinking water, different agencies/ organizations have developed eco-friendly, cost effective devices/ filtration techniques having higher As removal capacity. Here we elucidated the current status of GWAs contamination in different states of India and the new developments of mitigation options.

scholarly journals Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic

2020 ◽  
Vol 27 (8) ◽  
Author(s):  
Sarita Azad ◽  
Sushma Devi
Keyword(s):  
Tamil Nadu ◽  
National Level ◽  
International Travel ◽  
Primary Data ◽  
Eigenvector Centrality ◽  
Indian States ◽  
Social Network Structure ◽  
History Of ◽  
Influential Node ◽  
The Uk

Abstract Background The coronavirus pandemic (COVID-19) has spread worldwide via international travel. This study traced its diffusion from the global to national level and identified a few superspreaders that played a central role in the transmission of this disease in India. Data and methods We used the travel history of infected patients from 30 January to 6 April 6 2020 as the primary data source. A total of 1386 cases were assessed, of which 373 were international and 1013 were national contacts. The networks were generated in Gephi software (version 0.9.2). Results The maximum numbers of connections were established from Dubai (degree 144) and the UK (degree 64). Dubai’s eigenvector centrality was the highest that made it the most influential node. The statistical metrics calculated from the data revealed that Dubai and the UK played a crucial role in spreading the disease in Indian states and were the primary sources of COVID-19 importations into India. Based on the modularity class, different clusters were shown to form across Indian states, which demonstrated the formation of a multi-layered social network structure. A significant increase in confirmed cases was reported in states like Tamil Nadu, Delhi and Andhra Pradesh during the first phase of the nationwide lockdown, which spanned from 25 March to 14 April 2020. This was primarily attributed to a gathering at the Delhi Religious Conference known as Tabliqui Jamaat. Conclusions COVID-19 got induced into Indian states mainly due to International travels with the very first patient travelling from Wuhan, China. Subsequently, the contacts of positive cases were located, and a significant spread was identified in states like Gujarat, Rajasthan, Maharashtra, Kerala and Karnataka. The COVID-19’s spread in phase one was traced using the travelling history of the patients, and it was found that most of the transmissions were local.

scholarly journals District level correlates of COVID-19 pandemic in India

2020 ◽  
Author(s):  
Vandana Tamrakar ◽  
Ankita Srivastava ◽  
Mukesh C. Parmar ◽  
Sudheer Kumar Shukla ◽  
Shewli Shabnam ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Population Density ◽  
Prevalence Rate ◽  
Urban Population ◽  
Tamil Nadu ◽  
Andhra Pradesh ◽  
District Level ◽  
Indian States ◽  
Number Of Patients ◽  
Health Related

AbstractBackgroundThe number of patients with coronavirus infection (COVID-19) has amplified in India. Understanding the district level correlates of the COVID-19 infection ratio (IR) is therefore essential for formulating policies and intervention.ObjectivesThe present study examines the association between socio-economic and demographic characteristics of India’s population and the COVID-19 infection ratio at district level…Data and MethodsUsing crowdsourced data on the COVID-19 prevalence rate, we analyzed state and district level variation in India from March 14 to July 31 2020. We identified hotspot and cold spot districts for COVID-19 cases and infection ratio. We have also carried out a regression analysis to highlight the district level demographic, socio-economic, infrastructure, and health-related correlates of the COVID-19 infection ratio.ResultsThe results showed that the IR is 42.38 per one hundred thousand population in India. The highest IR was observed in Andhra Pradesh (145.0), followed by Maharashtra (123.6), and was the lowest in Chhattisgarh (10.1). About 80 per cent of infected cases, and 90 per cent of deaths were observed in nine Indian states (Tamil Nadu, Andhra Pradesh, Telangana, Karnataka, Maharashtra, Delhi, Uttar Pradesh, West Bengal, and Gujarat). Moreover, we observed COVID-19 cold-spots in central, northern, western, and north-eastern regions of India. Out of 736 districts, six metropolitan cities (Mumbai, Chennai, Thane, Pune, Bengaluru, and Hyderabad) emerged as the major hotspots in India, containing around 30 per cent of confirmed total COVID-19 cases in the country. Simultaneously, parts of the Konkan coast in Maharashtra, parts of Delhi, the southern part of Tamil Nadu, the northern part of Jammu & Kashmir were identified as hotspots of COVID-19 infection. Moran’s-I value of 0.333showed a positive spatial clusteringlevel in the COVID-19 IR case over neighboring districts. Our regression analysis found that district-level population density (β: 0.05, CI:004-0.06), the percent of urban population (β:3.08, CI: 1.05-5.11), percent of Scheduled Caste Population (β: 3.92, CI: 0.12-7.72),and district-level testing ratio (β: 0.03, CI: 0.01-0.04) are positively associated with the prevalence of COVID-19.ConclusionCOVID-19 cases were heavily concentrated in 9 states of India. Several demographic, socio-economic, and health-related variables are correlated with COVID-19 prevalence rate. However, after adjusting the role of socio-economic and health-related factors, the COVID-19 infection rate was found to be more rampant in districts with a higher population density, a higher percentage of the urban population, and a higher percentage of deprived castes and with a higher level of testing ratio. The identified hotspots and correlates in this study give crucial information for policy discourse.

scholarly journals Regression Analysis of COVID-19 Spread in India and its Different States

2020 ◽  
Author(s):  
Poonam Chauhan ◽  
Ashok Kumar ◽  
Pooja Jamdagni
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Tamil Nadu ◽  
Polynomial Regression ◽  
Case Fatality ◽  
Epidemiological Data ◽  
Fatality Rate ◽  
Indian States ◽  
Number Of Patients ◽  
Polynomial Regression Model

AbstractLinear and polynomial regression model has been used to investigate the COVID-19 outbreak in India and its different states using time series epidemiological data up to 26th May 2020. The data driven analysis shows that the case fatality rate (CFR) for India (3.14% with 95% confidence interval of 3.12% to 3.16%) is half of the global fatality rate, while higher than the CFR of the immediate neighbors i.e. Bangladesh, Pakistan and Sri Lanka. Among Indian states, CFR of West Bengal (8.70%, CI: 8.21–9.18%) and Gujrat (6.05%, CI: 4.90–7.19%) is estimated to be higher than national rate, whereas CFR of Bihar, Odisha and Tamil Nadu is less than 1%. The polynomial regression model for India and its different states is trained with data from 21st March 2020 to 19th May 2020 (60 days). The performance of the model is estimated using test data of 7 days from 20th May 2020 to 26th May 2020 by calculating RMSE and % error. The model is then used to predict number of patients in India and its different states up to 16th June 2020 (21 days). Based on the polynomial regression analysis, Maharashtra, Gujrat, Delhi and Tamil Nadu are continue to remain most affected states in India.

scholarly journals Epidemiological study on cardiac emergencies in Indian states having GVK Emergency Management and Research Institute services

2016 ◽  
Vol 04 (02) ◽  
pp. 121-126
Author(s):  
G. Ramana Rao ◽  
H. Rajanarsing Rao ◽  
G. Reddy ◽  
M. Prasad
Keyword(s):  
Emergency Management ◽  
Tamil Nadu ◽  
Andhra Pradesh ◽  
Poverty Line ◽  
State Governments ◽  
Indian States ◽  
The Mean ◽  
Access To Medical Care ◽  
Cardiac Emergencies ◽  
Research Institute

Abstract Background: Emergency medical service (EMS) is critical for the healthcare system as it saves lives by providing care immediately. Rapid access to medical care after a major cardiovascular event decreases morbidity and mortality. GVK Emergency Management and Research Institute (GVK EMRI) is a pioneer in emergency management services operated as a public private partnership (PPP) with various state governments. GVK EMRI coordinates medical, fire, and police-related emergencies through a single toll-free number, 108, across 15 states and 2 union territories of India. Material and Methods: This is a retrospective study of reported cases of cardiac emergencies in 2015 across 11 states with GVK EMRI services: Andhra Pradesh, Telangana, Assam, Goa, Gujarat, Karnataka, Madhya Pradesh, Meghalaya, Rajasthan, Tamil Nadu and Uttarakhand. Descriptive statistics using frequencies, proportions and means were calculated. Results and Discussion: This study aimed to describe the epidemiology of cardiac emergencies presenting to GVK EMRI across 11 states in India in 2015. There were increased cases of cardiac emergencies reported by higher age group individual across all states. The mean age was reported between 43 years to 62 years across the states. In this study, men called EMS for cardiac emergencies more often than women, except in the state of Gujarat. A higher number of cardiac emergency cases were reported by individuals living below the poverty line in Andhra Pradesh, Telangana, Assam, and Goa. Often (82.8%) people called 108 greater than six hours of symptom onset. Variation in call volume per day was minimal between the days of the week. At 48 hours, there were 2,675 reported deaths (1.1%). Conclusions: The current study stresses the scale and seriousness of the emerging challenge of cardiac emergencies, with particular emphasis on socioeconomic deprived groups in the operated states of GVK EMRI.

scholarly journals Parasitism of Rust, Early and Late Leafspot Pathogens of Peanut by Verticillium Lecanii

1990 ◽  
Vol 17 (1) ◽  
pp. 1-4 ◽  
Author(s):  
P. Subrahmanyam ◽  
P. M. Reddy ◽  
D. McDonald
Keyword(s):  
Biological Control ◽  
Leaf Area ◽  
Tamil Nadu ◽  
Andhra Pradesh ◽  
Verticillium Lecanii ◽  
Indian States ◽  
Potential Use

Abstract Verticillium lecanii was found parasitizing rust, early and late leafspot pathogens of peanut in the glasshouse at ICRISAT Center and in fanners' fields in the Indian States of Andhra Pradesh, Karnataka and Tamil Nadu. In inoculation experiments, there was a significant reduction in the extent of rust and late leafspot development on peanut leaves inoculated with V. lecanii. Receptivity and percentage leaf area damage of rust and late leafspot were reduced when inoculated with V. lecanii. The potential use of V. lecanii in biological control of rust and leafspot diseases of peanut is discussed.

TRENDS IN CONSANGUINITY IN SOUTH INDIA

2001 ◽  
Vol 33 (2) ◽  
pp. 185-197 ◽  
Author(s):  
S. KRISHNAMOORTHY ◽  
N. AUDINARAYANA
Keyword(s):  
Tamil Nadu ◽  
Andhra Pradesh ◽  
South India ◽  
Family Health ◽  
Social Situation ◽  
National Family Health Survey ◽  
Indian States ◽  
The Past ◽  
South Indian ◽  
National Family

This study uses data from the 1992–93 National Family Health Survey to assess trends in consanguinity in the South Indian states of Andhra Pradesh, Karnataka, Kerala and Tamil Nadu. In Kerala, the frequency of consanguineous marriages is very low and one type of preferred marriage of the Dravidian marriage system – uncle–niece marriage – is conspicuously absent. In the other states of South India, consanguinity and the coefficient of inbreeding are high. While no change in consanguinity is observed during the past three to four decades in Karnataka, a definite decline is observed in Andhra Pradesh and Tamil Nadu. Due to recent changes in the demographic and social situation in these states, this decline in consanguinity is likely to continue.

scholarly journals Comparative analysis and epidemiological study of SARS-CoV-2 in first wave among different states of India

2021 ◽  
Author(s):  
Rakesh Kaushik ◽  
Nikita ◽  
Rishabh ◽  
Yogita Lugani ◽  
Suman Lata
Keyword(s):  
Case Fatality Rate ◽  
Age Groups ◽  
Case Fatality ◽  
Fatality Rate ◽  
Indian States ◽  
Health Crisis ◽  
The Poor ◽  
North Eastern ◽  
Western Zone ◽  
Transmission Pathways

Abstract SARS-CoV-2 has now spread worldwide, and various governments are attempting to control the disease's spread before it becomes a global health crisis. Data from 28 Indian states and 8 Union Territories (UTs) provides a detailed look at the transmission pathways and case fatality rate (CFR) of the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). The case fatality ratios were calculated in each zone of India i.e. Central, Eastern, North Eastern, and Northern, Southern and Western zone. Moreover, the CFR was calculated in different periods of month. The CFR wassignificantly higher (P<0.01) in April to June period of 2020. The period of month had significantly different (P<0.01) on CFR. CFR was compared in different zones in India, western zone showed highest CFR as compared to other zones. The effect of Covid-19 was compared with different age groups and co-morbidities patients. This analysis showed that the mortality in Maharashtra was higher because of the poor adherence to the safety norms and due to the most visited and crowded place of India.

scholarly journals New plant distribution records to Indian states and addition to the flora of Myanmar

2019 ◽  
Vol 11 (6) ◽  
pp. 13795-13804
Author(s):  
Kanakasabhapathi Pradheep ◽  
Ganjalagatta Dasaiah Harish ◽  
Ranbir Singh Rathi ◽  
Joseph John Kattukkunnel ◽  
Sheikh Mohmmad Sultan ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Andhra Pradesh ◽  
Germplasm Collection ◽  
Plant Distribution ◽  
Botanical Survey ◽  
Crop Species ◽  
Indian States ◽  
Resource Collection ◽  
Nicobar Islands ◽  
Union Territory

Plant genetic resource collection expedition across various parts of India and herbarium study of Amaranthus and Luffa genera at Botanical Survey of India (BSI), Kolkata and Coimbatore revealed the distribution of 18 plant taxa new to various Indian states/union territory, viz., Arunachal Pradesh (7), Andaman & Nicobar Islands (5), Jammu & Kashmir (3), Andhra Pradesh (2), Manipur (1), and Tamil Nadu (1).  Out of these, 14 taxa have importance as wild relatives of 12 crop species.  In addition, herbarium studies at the BSI, Kolkata revealed the natural distribution of a cucurbitaceous species – Siraitia siamensis in Myanmar, which remained unnoticed and unreported so far.  Locality of herbarium/ germplasm collection, habitat and other field observations have been highlighted here.

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