Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
Add more filters










Language
Publication year range
1.
Prateek Singh; Rajat Ujjainiya; Satyartha Prakash; Salwa Naushin; Viren Sardana; Nitin Bhatheja; Ajay Pratap Singh; Joydeb Barman; Kartik Kumar; Raju Khan; Karthik Bharadwaj Tallapaka; Mahesh Anumalla; Amit Lahiri; Susanta Kar; Vivek Bhosale; Mrigank Srivastava; Madhav Nilakanth Mugale; C.P Pandey; Shaziya Khan; Shivani Katiyar; Desh Raj; Sharmeen Ishteyaque; Sonu Khanka; Ankita Rani; Promila; Jyotsna Sharma; Anuradha Seth; Mukul Dutta; Nishant Saurabh; Murugan Veerapandian; Ganesh Venkatachalam; Deepak Bansal; Dinesh Gupta; Prakash M Halami; Muthukumar Serva Peddha; Gopinath M Sundaram; Ravindra P Veeranna; Anirban Pal; Ranvijay Kumar Singh; Suresh Kumar Anandasadagopan; Parimala Karuppanan; Syed Nasar Rahman; Gopika Selvakumar; Subramanian Venkatesan; MalayKumar Karmakar; Harish Kumar Sardana; Animika Kothari; DevendraSingh Parihar; Anupma Thakur; Anas Saifi; Naman Gupta; Yogita Singh; Ritu Reddu; Rizul Gautam; Anuj Mishra; Avinash Mishra; Iranna Gogeri; Geethavani Rayasam; Yogendra Padwad; Vikram Patial; Vipin Hallan; Damanpreet Singh; Narendra Tirpude; Partha Chakrabarti; Sujay Krishna Maity; Dipyaman Ganguly; Ramakrishna Sistla; Narender Kumar Balthu; Kiran Kumar A; Siva Ranjith; Vijay B Kumar; Piyush Singh Jamwal; Anshu Wali; Sajad Ahmed; Rekha Chouhan; Sumit G Gandhi; Nancy Sharma; Garima Rai; Faisal Irshad; Vijay Lakshmi Jamwal; MasroorAhmad Paddar; Sameer Ullah Khan; Fayaz Malik; Debashish Ghosh; Ghanshyam Thakkar; Saroj K Barik; Prabhanshu Tripathi; Yatendra Kumar Satija; Sneha Mohanty; Md. Tauseef Khan; Umakanta Subudhi; Pradip Sen; Rashmi Kumar; Anshu Bhardwaj; Pawan Gupta; Deepak Sharma; Amit Tuli; Saumya Ray Chaudhuri; Srinivasan Krishnamurthi; Prakash L; Ch V Rao; B N Singh; Arvindkumar Chaurasiya; Meera Chaurasiyar; Mayuri Bhadange; Bhagyashree Likhitkar; Sharada Mohite; Yogita Patil; Mahesh Kulkarni; Rakesh Joshi; Vaibhav Pandya; Amita Patil; Rachel Samson; Tejas Vare; Mahesh Dharne; Ashok Giri; Shilpa Paranjape; G. Narahari Sastry; Jatin Kalita; Tridip Phukan; Prasenjit Manna; Wahengbam Romi; Pankaj Bharali; Dibyajyoti Ozah; Ravi Kumar Sahu; Prachurjya Dutta; Moirangthem Goutam Singh; Gayatri Gogoi; Yasmin Begam Tapadar; Elapavalooru VSSK Babu; Rajeev K Sukumaran; Aishwarya R Nair; Anoop Puthiyamadam; PrajeeshKooloth Valappil; Adrash Velayudhan Pillai Prasannakumari; Kalpana Chodankar; Samir Damare; Ved Varun Agrawal; Kumardeep Chaudhary; Anurag Agrawal; Shantanu Sengupta; Debasis Dash.
Preprint in English | medRxiv | ID: ppmedrxiv-21267889

ABSTRACT

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the effectiveness of interventions. Asymptomatic breakthrough infections have been a major problem during the ongoing surge of Delta variant globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines used in the higher-income regions. Here, we show for the first time how statistical and machine learning (ML) approaches can discriminate SARS-CoV-2 infection from immune response to an inactivated whole virion vaccine (BBV152, Covaxin, India), thereby permitting real-world vaccine effectiveness assessments from cohort-based serosurveys in Asia and Africa where such vaccines are commonly used. Briefly, we accessed serial data on Anti-S and Anti-NC antibody concentration values, along with age, sex, number of doses, and number of days since the last vaccine dose for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine (SVM) model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, 724 were classified as infected. Since the vaccine contains wild-type virus and the antibodies induced will neutralize wild type much better than Delta variant, we determined the relative ability of a random subset of such samples to neutralize Delta versus wild type strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, Delta variant, was neutralized more effectively than the wild type, which cannot happen without infection. The fraction rose to 71.8% (28 of 39) in subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period.

2.
Preprint in English | medRxiv | ID: ppmedrxiv-21260555

ABSTRACT

BackgroundCOVID-19 emerged as a global pandemic in 2020, rapidly spreading to most parts of the world. The proportion of infected individuals in a population can be reliably estimated via sero-surveillance, making it a valuable tool for planning control measures. We conducted a serosurvey study to investigate SARS-CoV-2 seroprevalence in the urban population of Hyderabad at the end of the first wave of infections. MethodsThe cross-sectional survey conducted in January 2021 included males and females aged 10 years and above, selected by multi-stage random sampling. 9363 samples were collected from 30 wards distributed over 6 zones of Hyderabad and tested for antibodies against SARS-CoV-2 nucleocapsid antigen. ResultsOverall seropositivity was 54.2%, ranging from 50-60% in most wards. Highest exposure appeared to be among 30-39y and 50-59y olds, with women showing greater seropositivity. Seropositivity increased with family size, with only marginal differences among people with varying levels of education. Seroprevalence was significantly lower among smokers. Only 11% of the survey subjects reported any COVID-19 symptoms, while 17% had appeared for Covid testing. ConclusionOver half the citys population was infected within a year of onset of the pandemic. However, [~]46% people were still susceptible, contributing to subsequent waves of infection. Highlights National level serosurveys under-estimate localised prevalence in dense urban areas SARS-CoV-2 seroprevalence in Hyderabad city was 54.2% after the first wave A large proportion of the population remains at risk over a year into the pandemic

3.
Salwa Naushin; Viren Sardana; Rajat Ujjainiya; Nitin Bhatheja; Rintu Kutum; Akash Kumar Bhaskar; Shalini Pradhan; Satyartha Prakash; Raju Khan; Birendra Singh Rawat; Giriraj Ratan Chandak; Karthik Bharadwaj Tallapaka; Mahesh Anumalla; Amit Lahiri; Susanta Kar; Shrikant Ramesh Mulay; Madhav Nilakanth Mugale; Mrigank Srivastava; Shaziya Khan; Anjali Srivastava; Bhawna Tomar; Murugan Veerapandian; Ganesh Venkatachalam; Selvamani Raja Vijayakumar; Ajay Agarwal; Dinesh Gupta; Prakash M Halami; Muthukumar Serva Peddha; Gopinath M; Ravindra P Veeranna; Anirban Pal; Vinay Kumar Agarwal; Anil Ku Maurya; Ranvijay Kumar Singh; Ashok Kumar Raman; Suresh Kumar Anandasadagopan; Parimala Karupannan; Subramanian Venkatesan; Harish Kumar Sardana; Anamika Kothari; Rishabh Jain; Anupma Thakur; Devendra Singh Parihar; Anas Saifi; Jasleen Kaur; Virendra Kumar; Avinash Mishra; Iranna Gogeri; Geetha Vani Rayasam; Praveen Singh; Rahul Chakraborty; Gaura Chaturvedi; Pinreddy Karunakar; Rohit Yadav; Sunanda Singhmar; Dayanidhi Singh; Sharmistha Sarkar; Purbasha Bhattacharya; Sundaram Acharya; Vandana Singh; Shweta Verma; Drishti Soni; Surabhi Seth; Firdaus Fatima; Shakshi Vashisht; Sarita Thakran; Akash Pratap Singh; Akanksha Sharma; Babita Sharma; Manikandan Subramanian; Yogendra Padwad; Vipin Hallan; Vikram Patial; Damanpreet Singh; Narendra Vijay Tirpude; Partha Chakrabarti; Sujay Krishna Maity; Dipyaman Ganguly; Jit Sarkar; Sistla Ramakrishna; Balthu Narender Kumar; Kiran A Kumar; Sumit G. Gandhi; Piyush Singh Jamwal; Rekha Chouhan; Vijay Lakshmi Jamwal; Nitika Kapoor; Debashish Ghosh; Ghanshyam Thakkar; Umakanta Subudhi; Pradip Sen; Saumya Raychaudhri; Amit Tuli; Pawan Gupta; Rashmi Kumar; Deepak Sharma; Rajesh P. Ringe; Amarnarayan D; Mahesh Kulkarni; Dhanasekaran Shanmugam; Mahesh Dharne; Syed G Dastager; Rakesh Joshi; Amita P. Patil; Sachin N Mahajan; Abu Junaid Khan; Vasudev Wagh; Rakeshkumar Yadav; Ajinkya Khilari; Mayuri Bhadange; Arvindkumar H. Chaurasiya; Shabda E Kulsange; Krishna khairnar; Shilpa Paranjape; Jatin Kalita; G.Narahari Sastry; Tridip Phukan; Prasenjit Manna; Wahengbam Romi; Pankaj Bharali; Dibyajyoti Ozah; Ravi Kumar Sahu; Elapaval VSSK Babu; Rajeev K Sukumaran; Aishwarya R Nair; Anoop Puthiyamadam; Prajeesh Kooloth Valappil; Adarsh Velayudhanpillai; Kalpana Chodankar; Samir Damare; Yennapu Madhavi; Ved Varun Agrawal; Sumit Dahiya; Anurag Agrawal; Debasis Dash; Shantanu Sengupta.
Preprint in English | medRxiv | ID: ppmedrxiv-21249713

ABSTRACT

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India), conducted a sero-survey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS CoV2 anti-nucleocapsid (anti-NC) antibodies; 95% with surrogate neutralization activity. Three-fourth recalled no symptoms. Repeat serology tests at 3 (n=346) and 6 (n=35) months confirmed stability of antibody response and neutralization potential. Local sero-positivity was higher in densely populated cities and was inversely correlated with a 30 day change in regional test positivity rates (TPR). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of sero-positivity were high-exposure work (Odds Ratio, 95% CI, p value; 2{middle dot}23, 1{middle dot}92-2{middle dot}59, 6{middle dot}5E-26), use of public transport (1{middle dot}79, 1{middle dot}43-2{middle dot}24, 2{middle dot}8E-06), not smoking (1{middle dot}52, 1{middle dot}16-1{middle dot}99, 0{middle dot}02), non-vegetarian diet (1{middle dot}67, 1{middle dot}41-1{middle dot}99, 3{middle dot}0E-08), and B blood group (1{middle dot}36,1{middle dot}15-1{middle dot}61, 0{middle dot}001). Impact StatementWidespread asymptomatic and undetected SARS-CoV2 infection affected more than a 100 million Indians by September 2020. Declining new cases thereafter may be due to persisting humoral immunity amongst sub-communities with high exposure. FundingCouncil of Scientific and Industrial Research, India (CSIR)

4.
Article in English | WPRIM (Western Pacific) | ID: wpr-52114

ABSTRACT

BACKGROUND: Most of the people associated with tailoring occupation in Nepal are still using mechanical sewing machine as an alternative of new technology for tailoring. Common peroneal nerves of both right and left legs are exposed to strenuous and chronic stress exerted by vibration and paddling of mechanical sewing machine. METHODS: The study included 30 healthy male tailors and 30 healthy male individuals. Anthropometric variables as well as cardio respiratory variables were determined for each subject. Standard Nerve Conduction Techniques using constant measured distances were applied to evaluate common peroneal nerve (motor) in both legs of each individual. Data were analyzed and compared between study and control groups using Man Whitney U test setting the significance level p ≤ 0.05. RESULTS: Anthropometric and cardio respiratory variables were not significantly altered between the study and control groups. The Compound muscle action potential (CMAP) latency of common peroneal nerves of both right [(11.29 ± 1.25 vs. 10.03 ± 1.37), P < 0.001] and left [(11.28 ± 1.38 vs. 10.05 ± 1.37), P < 0.01] legs was found to be significantly prolonged in study group as compared to control group. The Amp-CMAP of common peroneal nerves of both right [(4.57 ± 1.21 vs. 6.22 ± 1.72), P < 0.001] and left [(4.31 ± 1.55 vs. 6.25 ± 1.70), P < 0.001] legs was found significantly reduced in study group as compared to control group. Similarly, the motor nerve conduction velocity (MNCV) of common peroneal nerves of both right [(43.72 ± 3.25 vs. 47.49 ± 4.17), P < 0.001] and left [(42.51 ± 3.82 vs. 46.76 ± 4.51), P < 0.001] legs was also found to be significantly reduced in study group in comparison to control group. CONCLUSION: Operating mechanical sewing machine by paddling chronically and arduously could have attributed to abnormal nerve conduction study parameters due to vibration effect of the machine on right and left common peroneal nerves. The results of present study follow the trend towards presymptomatic or asymptomatic neuropathy similar to subclinical neuropathy.


Subject(s)
Humans , Male , Action Potentials , Leg , Nepal , Neural Conduction , Occupations , Peroneal Nerve , Vibration
SELECTION OF CITATIONS
SEARCH DETAIL