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774 results on '"Murhekar, Manoj"'

2. Cost of TB care and equity in distribution of catastrophic TB care costs across income quintiles in India

Author

Jeyashree, Kathiresan, Thangaraj, Jeromie W. V., Shanmugasundaram, Devika, Giridharan, Sri Lakshmi Priya, Pandey, Sumit, Shanmugasundaram, Prema, Ramasamy, Sabarinathan, Janagaraj, Venkateshprabhu, Arunachalam, Sivavallinathan, Sharma, Rahul, Shah, Vaibhav, Bagepally, Bhavani Shankara, Chadwick, Joshua, Shewade, Hemant Deepak, Chowdhury, Aniket, Iyer, Swati, Rao, Raghuram, Mattoo, Sanjay K., and Murhekar, Manoj V.

Published
2024
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3. Need for operational simplicity and timely disbursal of benefits—a qualitative exploration of the implementation of a direct benefit transfer scheme for persons with tuberculosis in India

Author

Mohan, Malu, Thangaraj, Jeromie W. V., Pandey, Sumit, Sri Lakshmi Priya, G., Arunachalam, Sivavallinathan, Sharma, Rahul, Shewade, Hemant Deepak, Aishwarya, B., Afeeq, K., Khatoon, Afsana, Gokulvijay, B., Sireesha, Gude, Chandra, Kavita, Nandhakumar, S., Samuel, Prince, Nanditha Viswanathan, C., Shanmugasundaram, Devika, Rao, Raghuram, Murhekar, Manoj V., and Jeyashree, Kathiresan

Published
2024
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4. Direct benefit transfer for nutritional support of patients with TB in India—analysis of national TB program data of 3.7 million patients, 2018–2022

Author

Jeyashree, Kathiresan, Shanmugasundaram, Prema, Shanmugasundaram, Devika, Priya G, Sri Lakshmi, Thangaraj, Jeromie W V, TS, Sumitha, Pandey, Sumit, Ramasamy, Sabarinathan, Sharma, Rahul, Arunachalam, Sivavallinathan, Shah, Vaibhav, Janagaraj, Venkateshprabhu, Sundari S, Sivakami, Chadwick, Joshua, Shewade, Hemant Deepak, Chowdhury, Aniket, Iyer, Swati, Rao, Raghuram, Mattoo, Sanjay K, and Murhekar, Manoj V

Published
2024
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6. MDR in Candida: The Real Storm

Author

Srivastava, Prashansha, Tiwari, Shashikant, Kumar, Manoj, Murhekar, Manoj V., Dwivedi, Gaurav Raj, Hameed, Saif, editor, and Vijayaraghavan, Pooja, editor

Published
2024
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7. Estimates of the burden of human rabies deaths and animal bites in India, 2022–23: a community-based cross-sectional survey and probability decision-tree modelling study

Author

Patil, Deepak B, Paramasivam, Raja, Pharande, Rajesh Raghunath, Singh, Karam Pal, Abraham, Swapna Susan, Sujatha, Aparna, Manoharan, Parthiban, Gopal, Dhinakar Raj, George, Sheela Saly T, Zaman, Kamran, Pandey, Krishna, Singh, Neha, Chander, Manda Punam, Pati, Sanghamitra, Singh, Srashti, Menon, Vishnu B, Bathini, Viswanath Guru, Ali, Atefh, Mahajan, Hemant, Jain, Kamalesh, Kant, Rajni, Varkey, Reshmi Ann, Gandhamalla, Sabitha Rani, Chinnappan, Prabakaran, Ramakrishnan, Gopinath, Paparaju, Ashok Kumar, Arunachalam, Suresh, Duraisamy, Augustine, Kannniyappan, Ramu, Karunakaran, Sathish Kumar, K, Afeeq, Kumarababu, Aparna, Arumugam, Suresh, Thangaraj, Jeromie Wesley Vivian, Krishna, Navaneeth S, Devika, Shanmugasundaram, Egambaram, Suganya, Dhanapal, Sudha Rani, Khan, Siraj Ahmed, Srivastava, Ashok Kumar, Mishra, Ayush, Shrinivasa, Basavaraj, Gour, Devendra, Madhukar, Major, Verma, Nirmal, Sharma, Parul, Soni, Ravinder Kumar, Ramasamy, Sabarinathan, Mohandas, Sreelakshmi, Baidya, Subrata, Rehman, Tanveer, Yeldandi, Vijay V, Singh, Akashdeep, Sreedevi, Aswathy, Tandale, Babasaheb V, Purakayastha, Debjani Ram, Reddy, Mahendra M, Toppo, Manju, Solanki, Nitinkumar Valjibhai, Ghosh, Pramit, Jaiswal, Prashant, Vyas, Shaili, Das, Shampa, Palo, Subrata Kumar, Prasanth, Venela, Rozario, Amanda G A, Durairajan, Chokkalingam, Delli, Anitha, Sasi, Aruna, Pandiyan, Chandhini, Ashwathnarayana, Doddabale Hanumanthaiah, Joy, Sam, Isloor, Srikrishna, Sudarshan, Mysore Kalappa, Rahi, Manju, and Murhekar, Manoj V

Published
2025
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8. Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic

Author

Piraveenan, Mahendra, Sawleshwarkar, Shailendra, Walsh, Michael, Zablotska, Iryna, Bhattacharyya, Samit, Farooqui, Habib Hassan, Bhatnagar, Tarun, Karan, Anup, Murhekar, Manoj, Zodpey, Sanjay, Rao, K. S. Mallikarjuna, Pattison, Philippa, Zomaya, Albert, and Perc, Matjaz

Subjects
Computer Science - Computer Science and Game Theory, Physics - Physics and Society, Quantitative Biology - Populations and Evolution
Abstract

Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic., Comment: 15 pages, 1 figure; published in Royal Society Open Science

Published
2020
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9. Profile of cardiac lesions among laboratory confirmed congenital rubella syndrome (CRS) infants: a nationwide sentinel surveillance, India, 2016–22

Author

Kumar, Praveen, Gupta, Parul Chawla, Munjal, Sanjay, Sankhyan, Naveen, Dash, Nabaneeta, Gupta, Madhu, Sai, Ria, Sharma, Vishaly, Gupta, Neeraj, Vyas, Varuna, Kaushal, Nidhi, Suhanimanasa, Shivanna, Niranjan Hunasanahalli, Kumar P, Prem, John, Deepa, Alexander, Arun, Kasturi, Nirupama, Bethou, Adhisivam, Singh, Varsha, Prasad, Nidhi, Ghosh, Aniruddha, Majumdar, Agniva, Dutta, Shanta, Gunasekaran, Pradeep Kumar, Shanmugasundaram, Devika, Santhanam, Sridhar, Verma, Sanjay, Singh, Kuldeep, Dwibedi, Bhagirathi, Awasthi, Shally, Singh, Himabindu, Sangappa, Mahantesh, Mondal, Nivedita, Sreenivasan, Priya, Saradakutty, Geetha, Malik, Shikha, Jain, Manish, Viswanathan, Rajlakshmi, Sapkal, Gajanan, Tripathi, Shalini, Patel, Bhupeshwari, Jain, Mahendra Kumar, Naganur, Sanjeev Hanumantacharya, Baranwal, Arun, Rohit, Manoj K, Deora, Surender, Sharma, Akhil, Anantharaj, Avinash, Pillai, Lakshmi Sadasivan, Kumar, Amber, Ramasamy, Sabarinathan, Rajendran, Padma Priya, Singh, Mini P., Ratho, Radha Kanta, Nag, Vijaylakshmi, Gadepalli, Ravishekhar, Mishra, Baijayantimala, Som, Tapas Kumar, Jain, Amita, Devara, Sudha Madhuri, Vannavada, Sudha Rani, Munivenkatappa, Ashok, Abraham, Asha Mary, Dhodapkar, Rahul, Ali, Syed, Biswas, Debasis, Pratkeye, Deepashri, Bavdekar, Ashish, Prakash, Jayant, Ray, Jaydeb, and Murhekar, Manoj

Published
2023
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10. Congenital rubella syndrome surveillance in India, 2016–21: Analysis of five years surveillance data

Author

Shanmugasundaram, Devika, Verma, Sanjay, Singh, Kuldeep, Dwibedi, Bhagirathi, Awasthi, Shally, Mahantesh, S., Singh, Himabindu, Santhanam, Sridhar, Mondal, Nivedita, S, Geetha, Sreenivasan, Priya, Malik, Shikha, Jain, Manish, Viswanathan, Rajlakshmi, Tripathi, Shalini, Patel, Bhupeshwari, Sapkal, Gajanan, Sabarinathan, R., Singh, Mini P., Ratho, R.K., Nag, Vijaylakshmi, Gadepalli, Ravishekhar, Som, Tapas Kumar, Mishra, Baijayantimala, Jain, Amita, Ashok, M., Madhuri, Devara Sudha, Rani, V Sudha, Abraham, Asha Mary, John, Deepa, Dhodapkar, Rahul, Syed Ali, A., Biswas, Debasis, Pratyeke, Deepashri, Bavdekar, Ashish, Prakash, Jayant, Singh, Varsha, Prasad, Nidhi, Ray, Jaydeb, Majumdar, Agniva, Dutta, Shanta, Gupta, Nivedita, and Murhekar, Manoj

Published
2023
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11. India's 2021 differentiated TB care guidance: Is it feasible to implement and act upon?

Author

Shewade, Hemant Deepak, Frederick, Asha, Kalyanasundaram, Madhanraj, Ravichandran, Prabhadevi, Lokesh, S., Suma, K.V., Aarthi, S., Kiruthika, G., Chadwick, Joshua, Rajasekar, T. Daniel, Gayathri, K., Vijayaprabha, R., Pathinathan, Delphina Peter, Nivetha, M. Bhavani, Chidambaram, Deiveegan, Pradeep, S. Kiran, Bhatnagar, Tarun, Devika, Shanmugasundaram, Rajkumar, S., Sakthivel, M., Mathavi, T., Vellasamy, S., Rajaprakash, A.R., Ganapathy, S., Sundaralingam, K., Savithri, S., Sudha, G., Balasubramaniam, M., Megala, B., Keerthivasan, S., Arunchandar, V., Mallan, Ganga, Khaleel, A. Muhammed, Anbanantham, K., Natesh, S., Bairavi, V., Krishnamoorthy, K., Hameed, O.M. Rahman Shahul, Sathishkumar, P., Saravanan, P., Illakiyaselvan, P.T., Praveenkumar, S., Murugan, S., Ganeshkumar, K., Manoj, G., Sivaprakasam, A., Sangamithira, G., Chandrika, A., Sacred Selvin, A. Alffer, Ranjini, S.V. Asha, Babu, K. Anand, Arunshankar, V., Selvavinayagam, T.S., Ramachandran, Ranjani, and Murhekar, Manoj V.

Published
2023
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12. Evaluating the effect of measles and rubella mass vaccination campaigns on seroprevalence in India: a before-and-after cross-sectional household serosurvey in four districts, 2018–2020

Author

Murhekar, Manoj V, Gupta, Nivedita, Hasan, Alvira Z, Kumar, Muthusamy Santhosh, Kumar, V Saravana, Prosperi, Christine, Sapkal, Gajanan N, Thangaraj, Jeromie Wesley Vivian, Kaduskar, Ojas, Bhatt, Vaishali, Deshpande, Gururaj Rao, Thankappan, Ullas Padinjaremattathil, Bansal, Avi Kumar, Chauhan, Sanjay L, Grover, Gangandeep Singh, Jain, Arun Kumar, Kulkarni, Ragini N, Sharma, Santanu Kumar, Chaaithanya, Itta K, Kharwal, Sanchit, Mishra, Sunil K, Salvi, Neha R, Sharma, Sandeep, Sarmah, Nilanju P, Sabarinathan, R, Duraiswamy, Augustine, Rani, D Sudha, Kanagasabai, K, Lachyan, Abhishek, Gawali, Poonam, Kapoor, Mitali, Shrivastava, Arpit Kumar, Chonker, Saurabh Kumar, Tilekar, Bipin, Tandale, Babasaheb V, Ahmad, Mohammad, Sangal, Lucky, Winter, Amy, Mehendale, Sanjay M, Moss, William J, and Hayford, Kyla

Published
2022
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13. Effectiveness of BBV152/Covaxin and AZD1222/Covishield vaccines against severe COVID-19 and B.1.617.2/Delta variant in India, 2021: a multi-centric hospital-based case-control study

Author

Bhatnagar, Tarun, Chaudhuri, Sirshendu, Ponnaiah, Manickam, Yadav, Pragya D, Sabarinathan, R, Sahay, Rima R, Ahmed, Faheem, Aswathy, S, Bhardwaj, Pankaj, Bilimale, Anil, Kumar, M Santhosh, Logaraj, M., Narlawar, Uday, Palanivel, C, Patel, Prakash, Rai, Sanjay K, Saxena, Vartika, Singh, Arvind, Thangaraj, Jeromie WV, Agarwal, Ashwini, Alvi, Yasir, Amoghashree, Ashok, P, Babu, Dinesh, Bahurupi, Yogesh, Bhalavi, Sangita, Behera, Priyamadhaba, Biswas, Priyanka Pandit, Charan, Jaykaran, Chauhan, Nishant Kumar, Chetak, KB, Dar, Lalit, Das, Ayan, Deepashree, R, Dhar, Minakshi, Dhodapkar, Rahul, Dipu, TS, Dudeja, Mridu, Dudhmal, Manisha, Gadepalli, Ravisekhar, Garg, Mahendra Kumar, Gayathri, AV, Goel, Akhil Dhanesh, Gowdappa, H Basavana, Guleria, Randeep, Gupta, Manoj Kumar, Islam, Farzana, Jain, Mannu, Jain, Vineet, Jawahar, M Lanord Stanley, Joshi, Rajendra, Kant, Shashi, Kar, Sitanshu Sekhar, Kalita, Deepjyoti, Khapre, Meenakshi, Khichar, Satyendra, Kombade, Sarika Prabhakar, Kohli, Sunil, Kumar, Abhinendra, Kumar, Anil, Kumar, Deepak, Kulirankal, Kiran G, Leela, KV, Majumdar, Triparna, Mishra, Baijayantimala, Misra, Puneet, Misra, Sanjeev, Mohapatra, Prasanta Raghab, Murthy, M Narayana, Nyayanit, Dimpal A, Patel, Manish, Pathania, Monika, Patil, Savita, Patro, Binod Kumar, Jalandra, Ramniwas, Rathod, Pragati, Shah, Naimesh, Shete, Anita, Shukla, Deepak, Shwethashree, M, Sinha, Smita, Sumana, MN, Surana, Ashish, Trikha, Anjan, Tejashree, A, Venkateshan, Mahalingam, Vijaykrishnan, G, Wadhava, Sarita, Wig, Naveet, Gupta, Nivedita, Abraham, Priya, and Murhekar, Manoj V

Published
2022
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15. Safety and immunogenicity of the Rotavac and Rotasiil rotavirus vaccines administered in an interchangeable dosing schedule among healthy Indian infants: a multicentre, open-label, randomised, controlled, phase 4, non-inferiority trial

Author

Kanungo, Suman, Chatterjee, Pranab, Bavdekar, Ashish, Murhekar, Manoj, Babji, Sudhir, Garg, Richa, Samanta, Sandip, Nandy, Ranjan K, Kawade, Anand, Boopathi, Kangusamy, Kanagasabai, Kaliaperumal, Kamal, Vineet Kumar, Kumar, Velusamy Saravana, Gupta, Nivedita, and Dutta, Shanta

Published
2022
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16. Prediction of mortality and prioritisation to tertiary care using the 'OUR-ARCad' risk score gleaned from the second wave of COVID-19 pandemic—A retrospective cohort study from South India.

Author

Gopalan, Narendran, Viswanathan, Vinod Kumar, Srinivasalu, Vignes Anand, Arumugam, Saranya, Bhaskar, Adhin, Manoharan, Tamizhselvan, Chandrasekar, Santosh Kishor, Bujagaruban, Divya, Arumugham, Ramya, Jagadeeswaran, Gopi, Pandian, Saravanan Madurai, Ponniah, Arunalatha, Senguttuvan, Thirumaran, Chinnaiyan, Ponnuraja, Dhanraj, Baskaran, Chadha, Vineet Kumar, Purushotham, Balaji, and Murhekar, Manoj Vasanth

Subjects
DISEASE risk factors, COVID-19 pandemic, MORTALITY risk factors, COVID-19, TERTIARY care
Abstract

Background: Judicious utilisation of tertiary care facilities through appropriate risk stratification assumes priority, in a raging pandemic, of the nature of delta variant-predominated second wave of COVID-19 pandemic in India. Prioritisation of tertiary care, through a scientifically validated risk score, would maximise recovery without compromising individual safety, but importantly without straining the health system. Methods: De-identified data of COVID-19 confirmed patients admitted to a tertiary care hospital in South India, between April 1, 2021 and July 31, 2021, corresponding to the peak of COVID-19 second wave, were analysed after segregating into 'survivors' or 'non-survivors' to evaluate the risk factors for COVID-19 mortality at admission and formulate a risk score with easily obtainable but clinically relevant parameters for accurate patient triaging. The predictive ability was ascertained by the area under the receiver operator characteristics (AUROC) and the goodness of fit by the Hosmer-Lemeshow test and validated using the bootstrap method. Results: Of 617 COVID-19 patients (325 survivors, 292 non-survivors), treated as per prevailing national guidelines, with a slight male predilection (358/617 [58.0%]), fatalities in the age group above and below 50 years were (217/380 [57.1%]) and (75/237 [31.6%]), p<0.001. The relative distribution of the various parameters among survivors and non-survivors including self-reported comorbidities helped to derive the individual risk scores from parameters significant in the multivariable logistic regression. The 'OUR-ARCad' risk score components were—Oxygen saturation SaO2<94%-23, Urea > 40mg/dL-15, Neutrophil/Lymphocytic ratio >3–23, Age > 50 years-8, Pulse Rate >100–8 and Coronary Artery disease-15. A summated score above 50, mandated tertiary care management (sensitivity-90%, specificity-75%; AUC-0.89), validated in 2000 bootstrap dataset. Conclusions: The OUR-ARCad risk score, could potentially maximize recovery in a raging COVID-19 pandemic, through prioritisation of tertiary care services, neither straining the health system nor compromising patient's safety, delivering and diverting care to those who needed the most. [ABSTRACT FROM AUTHOR]

Published
2025
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17. Evaluation of the Drug-Resistant Tuberculosis (DR-TB) management component under the National Tuberculosis Elimination Program (NTEP) in Kerala, India, 2021-22.

Author

Vaman, Raman Swathy, Kalyanasundaram, Madhanraj, Mohan, Malu, Pradeepa, Narayana, and Murhekar, Manoj V.

Subjects
MULTIDRUG-resistant tuberculosis, AIRBORNE infection, HEALTH facilities, PERSONNEL management, PSYCHOLOGICAL tests
Abstract

Background and Objective: We evaluated the DR-TB component of the National Tuberculosis Elimination Program (NTEP) in a high-burden district in Kerala to identify the programmatic gaps, if any, in screening, diagnosis, treatment, and follow-up of notified DR-TB patients. Methods: A mixed-methods design was used, and the evaluation was performed in two steps. In the first step, we reviewed the program documents and conducted stakeholder interviews to develop a detailed description of the program design and developed a logical framework to evaluate program performance. Consequently, in the next step, we conducted programmatic data reviews, facility surveys, and in-depth interviews with key stakeholders to identify the programmatic gaps in implementation, guided by the logic framework. Results: Of the 494 microbiologically confirmed TB patients during 2021-22, 342 (69%) were tested for drug sensitivity, and 30 DR-TB patients were identified. There was no separate district DR-TB treatment center with airborne infection control facilities, and only 16% (66/422) of the various categories of staff were trained in recent guidelines. Only 30% (9/30) of DR-TB patients were provided with any psychological assessment. The favorable treatment outcome was 80% Interviews revealed poor readiness and motivation from the private sector for screening, contextual barriers in human resource availability, transportation, and financial barriers to the beneficiary despite providing financial benefits. Conclusion: Prioritizing the establishment of a district DR-TB treatment center and sputum transport mechanism, posting a clinical psychologist dedicated to counseling patients on therapy, and training all categories of staff on DR-TB management guidelines will significantly contribute to improving program outcomes. [ABSTRACT FROM AUTHOR]

Published
2025
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21. Restoration of dendritic cell homeostasis and Type I/Type III interferon levels in convalescent COVID-19 individuals

Author

Rajamanickam, Anuradha, Kumar, Nathella Pavan, Pandiaraj, Arul Nancy, Selvaraj, Nandhini, Munisankar, Saravanan, Renji, Rachel Mariam, Venkatramani, Vijayalakshmi, Murhekar, Manoj, Thangaraj, Jeromie Wesley Vivian, Kumar, Muthusamy Santhosh, Kumar, Chethrapilly Purushothaman Girish, Bhatnagar, Tarun, Ponnaiah, Manickam, Sabarinathan, Ramasamy, Saravanakumar, Velusamy, and Babu, Subash

Published
2022
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22. Outbreak of ceftriaxone-resistant Salmonella enterica serotype Typhi-Tiruchirappalli, Tamil Nadu, India, June 2018

Author

Dzeyie, Kevisetuo A., Dhanapaul, Sankara, Rubeshkumar, Polani, Desing, SaravanaKumar, Vignesh, M S, Raveendran, I, Kumar, Prem, Kathuria, Shallu, Choudhary, Sushma, Saroha, Ekta, Siromany, Valan, Raju, Mohankumar, Ganeshkumar, Parasuraman, Ponnaiah, Manickam, Sodha, Samir V., Laserson, Kayla, Bhatnagar, Tarun, Kapoor, Lata, Bahl, Arti, Jain, Sudhir K, Gupta, Sunil, Murhekar, Manoj V, and Singh, Sujeet K

Published
2021
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24. SARS-CoV-2 seroprevalence among the general population and healthcare workers in India, December 2020–January 2021

Author

Anand, Tanu, Babu, Giridhara R., Chauhan, Himanshu, Dikid, Tanzin, Gangakhedkar, Raman R., Kant, Shashi, Kulkarni, Sanket, Muliyil, J.P., Pandey, Ravindra Mohan, Sarkar, Swarup, Shah, Naman, Shrivastava, Aakash, Singh, Sujeet K., Zodpe, Sanjay, Hindupur, Anusha, Asish, P.R., Chellakumar, M., Chokkalingam, D., Dasgupta, Sauvik, Gowtham, M.M.E., Jose, Annamma, Kalaiyarasi, K., Karthik, N.N., Karunakaran, T., Kiruthika, G., Dinesh Kumar, H., Sarath Kumar, S., Sarath Kumar, M.P., Michaelraj, E., Pradhan, Josephine, Arun Prasath, E.B., Gladys Angelin Rachel, D., Rani, Sudha, Rozario, Amanda, Sivakumar, R., Gnana Soundari, P., Sujeetha, K., Vinod, Arya, Murhekar, Manoj V., Bhatnagar, Tarun, Thangaraj, Jeromie Wesley Vivian, Saravanakumar, V., Kumar, Muthusamy Santhosh, Selvaraju, Sriram, Rade, Kiran, Kumar, C.P. Girish, Sabarinathan, R., Turuk, Alka, Asthana, Smita, Balachandar, Rakesh, Bangar, Sampada Dipak, Bansal, Avi Kumar, Chopra, Vishal, Das, Dasarathi, Deb, Alok Kumar, Devi, Kangjam Rekha, Dhikav, Vikas, Dwivedi, Gaurav Raj, Khan, S. Muhammad Salim, Kumar, M. Sunil, Laxmaiah, Avula, Madhukar, Major, Mahapatra, Amarendra, Rangaraju, Chethana, Turuk, Jyotirmayee, Yadav, Rajiv, Andhalkar, Rushikesh, Arunraj, K., Bharadwaj, Dinesh Kumar, Bharti, Pravin, Bhattacharya, Debdutta, Bhat, Jyothi, Chahal, Ashrafjit S., Chakraborty, Debjit, Chaudhury, Anshuman, Deval, Hirawati, Dhatrak, Sarang, Dayal, Rakesh, Elantamilan, D., Giridharan, Prathiksha, Haq, Inaamul, Hudda, Ramesh Kumar, Jagjeevan, Babu, Kalliath, Arshad, Kanungo, Srikanta, Krishnan, Nivethitha N., Kshatri, Jaya Singh, Kumar, Alok, Kumar, Niraj, Kumar, V.G. Vinoth, Lakshmi, G.G.J. Naga, Mehta, Ganesh, Mishra, Nandan Kumar, Mitra, Anindya, Nagbhushanam, K., Nimmathota, Arlappa, Nirmala, A.R., Pandey, Ashok Kumar, Prasad, Ganta Venkata, Qurieshi, Mariya Amin, Reddy, Sirasanambatti Devarajulu, Robinson, Aby, Sahay, Seema, Saxena, Rochak, Sekar, Krithikaa, Shukla, Vijay Kumar, Singh, Hari Bhan, Singh, Prashant Kumar, Singh, Pushpendra, Singh, Rajeev, Srinivasan, Nivetha, Varma, Dantuluri Sheethal, Viramgami, Ankit, Wilson, Vimith Cheruvathoor, Yadav, Surabhi, Yadav, Suresh, Zaman, Kamran, Chakrabarti, Amit, Das, Aparup, Dhaliwal, R.S., Dutta, Shanta, Kant, Rajni, Khan, A.M., Narain, Kanwar, Narasimhaiah, Somashekar, Padmapriyadarshini, Chandrasekaran, Pandey, Krishna, Pati, Sanghamitra, Patil, Shripad, Rajkumar, Hemalatha, Ramarao, Tekumalla, Sharma, Y.K., Singh, Shalini, Panda, Samiran, Reddy, D.C.S., and Bhargava, Balram

Published
2021
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25. Immunity against diphtheria among children aged 5–17 years in India, 2017–18: a cross-sectional, population-based serosurvey

Author

Karunakaran, T, Govindhasamy, C, Daniel Rajasekar, T, Jeyakumar, A, Suresh, A, Augustine, D, Ashok Kumar, P, Jose, Annamma, Sivakumar, R, Banerjee John, JW, Murhekar, Manoj V, Kamaraj, Pattabi, Kumar, Muthusamy Santhosh, Khan, Siraj Ahmed, Allam, Ramesh Reddy, Barde, Pradip V, Dwibedi, Bhagirathi, Kanungo, Suman, Mohan, Uday, Mohanty, Suman Sundar, Roy, Subarna, Sagar, Vivek, Savargaonkar, Deepali, Tandale, Babasaheb V, Topno, Roshan Kamal, Kumar, C P Girish, Sabarinathan, Ramasamy, Bitragunta, Sailaja, Grover, Gagandeep Singh, Lakshmi, P V M, Mishra, Chandra Mauli, Sadhukhan, Provash, Sahoo, Prakash Kumar, Singh, Shivendra Kumar, Yadav, Chander Prakash, Kumar, Rajesh, Dutta, Shanta, Toteja, G S, Gupta, Nivedita, and Mehendale, Sanjay M

Published
2021
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28. SARS-CoV-2 antibody seroprevalence in India, August–September, 2020: findings from the second nationwide household serosurvey

Author

Andhalkar, Rushikesh, Chaudhury, Anshuman, Deval, Hirawati, Dhatrak, Sarang, Gupta, Rajeev Ranjan, Ilayaperumal, Ezhilarasan, Jagjeevan, Babu, Jha, Ramesh Chandra, Kiran, K, Krishnan, Nivethitha N, Kumar, Alok, Kumar, VG Vinoth, Nagbhushanam, K, Nimmathota, Arlappa, Pandey, Ashok Kumar, Pawar, Harpreet Singh, Rathore, Kushal Singh, Robinson, Aby, Singh, Hari Bhan, Wilson, Vimith Cheruvathoor, Yadav, Ashwini, Yadav, Rajiv, Karunakaran, T, Pradhan, Josephine, Sivakumar, T, Jose, Annamma, Kalaiyarasi, K, Dasgupta, Sauvik, Anusha, R, Anand, Tanu, Babu, Giridhara R, Chauhan, Himanshu, Dikid, Tanzin, Gangakhedkar, Raman R, Kant, Shashi, Kulkarni, Sanket, Muliyil, J P, Pandey, Ravindra Mohan, Sarkar, Swarup, Shrivastava, Aakash, Singh, Sujeet K, Zodpey, Sanjay, Das, Aparup, Das, Pradeep, Dutta, Shanta, Kant, Rajni, Narain, Kanwar, Narasimhaiah, Somashekar, Pati, Sanghamitra, Patil, Shripad, Rajkumar, Hemalatha, Ramarao, Tekumalla, Sarkar, Kamalesh, Singh, Shalini, Toteja, Gurudayal S, Zaman, Kamran, Murhekar, Manoj V, Bhatnagar, Tarun, Selvaraju, Sriram, Saravanakumar, V, Thangaraj, Jeromie Wesley Vivian, Shah, Naman, Kumar, Muthusamy Santhosh, Rade, Kiran, Sabarinathan, R, Asthana, Smita, Balachandar, Rakesh, Bangar, Sampada Dipak, Bansal, Avi Kumar, Bhat, Jyothi, Chopra, Vishal, Das, Dasarathi, Deb, Alok Kumar, Devi, Kangjam Rekha, Dwivedi, Gaurav Raj, Khan, S Muhammad Salim, Kumar, C P Girish, Kumar, M Sunil, Laxmaiah, Avula, Madhukar, Major, Mahapatra, Amarendra, Mohanty, Suman Sundar, Rangaraju, Chethana, Turuk, Alka, Baradwaj, Dinesh Kumar, Chahal, Ashrafjit S, Debnath, Falguni, Haq, Inaamul, Kalliath, Arshad, Kanungo, Srikanta, Kshatri, Jaya Singh, Lakshmi, G G J Naga, Mitra, Anindya, Nirmala, A R, Prasad, Ganta Venkata, Qurieshi, Mariya Amin, Sahay, Seema, Sangwan, Ramesh Kumar, Sekar, Krithikaa, Shukla, Vijay Kumar, Singh, Prashant Kumar, Singh, Pushpendra, Singh, Rajeev, Varma, Dantuluri Sheethal, Viramgami, Ankit, Panda, Samiran, Reddy, D C S, and Bhargava, Balram

Published
2021
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29. Seroprevalence of chikungunya virus infection in India, 2017: a cross-sectional population-based serosurvey

Author

Kumar, Muthusamy Santhosh, Kamaraj, Pattabi, Khan, Siraj Ahmed, Allam, Ramesh Reddy, Barde, Pradip V, Dwibedi, Bhagirathi, Kanungo, Suman, Mohan, Uday, Mohanty, Suman Sundar, Roy, Subarna, Sagar, Vivek, Savargaonkar, Deepali, Tandale, Babasaheb V, Topno, Roshan Kamal, Kumar, Chethrapilly P Girish, Sabarinathan, Ramasamy, Kumar, Velusamy Saravana, Bitragunta, Sailaja, Grover, Gagandeep Singh, Lakshmi, Pinnaka V M, Mishra, Chandra Mauli, Sadhukhan, Provash, Sahoo, Prakash Kumar, Singh, Shivendra K, Yadav, Chander Prakash, Dinesh, Elangovan Ramya, Karunakaran, Thiyagarajan, Govindhasamy, Chinnasamy, Rajasekar, Thomas Daniel, Jeyakumar, Annadurai, Suresh, Arunachalam, Augustine, Duraisamy, Kumar, Paparaju Ashok, Kumar, Rajesh, Dutta, Shanta, Toteja, Gurudayal S, Gupta, Nivedita, Clapham, Hannah E, Mehendale, Sanjay M, and Murhekar, Manoj V

Published
2021
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30. Bridging the "know-do" gap to improve active case finding for tuberculosis in India: A qualitative exploration into national tuberculosis elimination program staffs' perspectives.

Author

Shewade, Hemant Deepak, Ravichandran, Prabhadevi, Pradeep, S. Kiran, Kiruthika, G., Shanmugasundaram, Devika, Chadwick, Joshua, Iyer, Swati, Chowdhury, Aniket, Tumu, Dheeraj, Shah, Amar N., Vadera, Bhavin, Roddawar, Venkatesh, Mattoo, Sanjay K., Rade, Kiran, Rao, Raghuram, and Murhekar, Manoj V.

Subjects
RAPID diagnostic tests, MANAGEMENT information systems, INFORMATION resources management, SECONDARY analysis, CAPACITY building
Abstract

Background: In 2022, India's national tuberculosis (TB) elimination program (NTEP) commissioned a national level evaluation of active case finding (ACF) for TB to guide evidence-based strategic planning. As part of this evaluation, based on secondary data analysis we observed that the quality of ACF was suboptimal in 2021. Hence, this study aimed to understand the enablers, barriers, and suggested solutions to improve ACF for TB in India from NTEP staff (provider) perspective. Methods: This was a descriptive qualitative study involving key informant interviews from six districts and eight states, conducted between February and August 2023. We purposively selected key state- district- and sub-district-level program managers and implementers who were experienced and vocal. The interviews were audio recorded and transcribed verbatim by research interns and investigators. Two investigators independently did manual descriptive thematic analysis, and a third investigator resolved inconsistencies. The themes and categories emerged by collating together the results of the coding process. Results: A total of 34 key informant interviews were conducted and of these, four were repeat interviews. Adequate budgets for ACF including incentives, performance review mechanism, engagement of all stakeholders, adopting a community friendly approach, use of rapid diagnostic tests and digitalization were the perceived enablers. In some states ACF was implemented in general population (not restricted to high-risk population) following directives at state level. There were limited mechanisms to ensure ACF quality indicators were met before disbursing incentives and cross-verification of the aggregate ACF care cascade numbers that were reported in Ni-kshay (electronic TB information management system under NTEP). In addition to the state and district level implementers having limited understanding of concepts around ACF (quality indicators, number needed to screen and yield), we also inferred the presence of a 'know-do' gap for many activities under ACF. The suggested solutions were around capacity building and quality improvement strategies. Conclusion: The existing national ACF guidance should be revised to emphasize capacity building, need to carry out ACF in high-risk (not general) population, quality control-linked incentives, and regular implementation monitoring of the activities. This should contribute towards better coverage and improved quality translating into better ACF outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Seropositivity of chikungunya in hospital setting, India: A systematic review and meta-analysis.

Author

Nagarajan, Ramya, Ayyasamy, Lavanya, Ganeshkumar, Parasuraman, Velusamy, Saravanakumar, and Murhekar, Manoj

Abstract

Backround: Information about the chikungunya disease burden by age groups and geographic distribution is necessary to guide appropriate control measures. With this, we conducted a systematic review and meta-analysis to estimate the disease burden of chikungunya fever in India. Material and Methods: We conducted this systematic review according to the Cochrane Collaboration guidelines. We retrieved relevant articles from PubMed and a free online search. Two investigators screened titles and abstracts and extracted data from the relevant articles. Our primary outcome is the proportion of laboratory-confirmed Chikungunya fever among clinically suspected patients. We used a random effect model to estimate the pooled proportion of Chikungunya fever. Result: A total of 20 articles were included in the quantitative syntheses. The pooled proportion of laboratory-confirmed chikungunya fever from 20 studies estimated using the random effects model is 24% (95%CI: 15-34%). We found the pooled proportion in the southern region was 35% (95%CI: 4-66%), 28% (95%CI: 3-58%) in the western region, 24% (95%CI: 1-48%) in the eastern region, 20% (95%CI: 12-29%) in the northern region, and 4% (95%CI: 1-6%) in North-eastern region. Conclusion: This review emphasizes the need to strengthen the surveillance of disease burden using multiple diagnostic tests and the need for an appropriate molecular diagnostic for early detection of the chikungunya virus. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Analysis of Cholera Risk in India: Insights from 2017–18 Serosurvey Data Integrated with Epidemiologic data and Societal Determinants from 2015–2019.

Author

Kanungo, Suman, Nandy, Ranjan Kumar, Talukdar, Rounik, Murhekar, Manoj, Azman, Andrew S., Hegde, Sonia T., Chatterjee, Pranab, Chakraborty, Debjit, Das, Madhuchhanda, Kamaraj, P, Kumar, Muthusamy Santhosh, and Dutta, Shanta

Subjects
CHOLERA, VIBRIO cholerae, TASK forces, DEVELOPING countries, SANITATION, RISK assessment
Abstract

Background: Indian subcontinent being an important region in the fight to eliminate cholera needs better cholera surveillance. Current methods miss most infections, skewing disease burden estimates. Triangulating serosurvey data, clinical cases, and risk factors could reveal India's true cholera risk. Methods: We synthesized data from a nationally representative serosurvey, outbreak reports and risk factors like water, sanitation and the Multidimensional Poverty Index, to create a composite vulnerability index for assessing state-wise cholera risk in India. We tested 7,882 stored sera samples collected during 2017–18 from individuals aged 9–45 years, for vibriocidal antibodies to Vibrio cholerae O1 using a cut-off titre ≥320 defining as elevated titre. We also extracted data from the 2015–19 Integrated Disease Surveillance Programme and published cholera reports. Results: Overall, 11.7% (CI: 10.4–13.3%) of the sampled population had an elevated titre of cholera vibriocidal antibodies (≥320). The Southern region experienced the highest incidence (16.8%, CI: 12.1–22.8), followed by the West (13.2%, CI: 10.0–17.3) and North (10.7%, CI: 9.3–12.3). Proportion of samples with an elevated vibriocidal titre (≥320) was significantly higher among individuals aged 18–45 years (13.0% CI: 11.2–15.1) compared to children 9–17 years (8.6%, CI 7.3–10.0, p<0.05); we found no differences between sex or urbanicity. Between 2015–2019, the Integrated Disease Surveillance Program (IDSP) reported 29,400 cases of cholera across the country. Using the composite vulnerability index, we found Karnataka, Madhya Pradesh, and West Bengal were the most vulnerable states in India in terms of risk of cholera. Conclusion: The present study showed that cholera infection is present in all five regions across India. The states with high cholera vulnerability could be prioritized for targeted prevention interventions. Author summary: Cholera remains a significant public health threat in areas with inadequate water, sanitation, and hygiene (WASH). The World Health Organization's Global Task Force on Cholera Control (GTFCC) launched "Ending Cholera: A Global Roadmap to 2030" to reduce cholera deaths and eliminate the disease in 20 countries by 2030 through targeted interventions, including improved WASH practices and disease surveillance. cholera surveillance, especially in developing countries seldom poses difficulty in terms of the need for laboratory infrastructure, and other resource constraints. Thereby, in this study, we utilized a viable approach with serosurvey data from 2017, cholera outbreak data, WASH indicators, and the Multidimensional Poverty Index (MPI) to create a composite vulnerability index for cholera risk in India. Overall, 11.7% of the sampled population had detectable levels of cholera antibodies reflecting previous infection. The Southern region of India experienced the highest incidence, followed by the West and North. the study showed that cholera infection is present in all five regions across India. Further, the vulnerability index which we built could be utilized in other settings so that effective tailored interventions could be applied in identified priority areas. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Epidemiology and outcomes of drug-resistant tuberculosis cases notified in a low-resource district in Kerala, India 2017–2021 – A 5-year retrospective analysis.

Author

Vaman, Raman Swathy, Kalyanasundaram, Madhanraj, Amina, T. P., and Murhekar, Manoj V.

Subjects
MULTIDRUG-resistant tuberculosis, TREATMENT failure, MANAGEMENT information systems, TREATMENT effectiveness, BODY mass index
Abstract

Objectives: Kasaragod district reports the highest drug-resistant tuberculosis (DR-TB) case notification rates in Kerala. We conducted a cross-sectional study in Kasaragod to describe the DR-TB cases notified from January 2017 to December 2021 and to identify the factors associated with unfavorable treatment outcomes in DR-TB patients. Materials and Methods: We analyzed the programmatic data from the "Nikshay portal" (a web-based patient management information system for [TB] under the National TB Elimination Program), DR-TB treatment cards, and treatment registers available with the district TB center for all the DR-TB patients notified during the study period. We described the DR-TB cases by year, local self-government area (the local administrative setup), age, gender, income level, and treatment outcomes. We compared sociodemographic, anthropometric, and clinical factors among the DR-TB patients with favorable (cured and treatment completed) and unfavorable (died, lost to follow-up, and treatment failure) treatment outcomes. Results: From January 2017 to December 2021, 128 DR-TB cases were notified from Kasaragod. Annual notification rates varied from 1.4 to 3.4/100,000 population with the highest notification in 2019. The proportion of new TB cases notified tested for drug sensitivity rose from 22% in 2017 to 86% in 2021. Seven of 41 local self-government areas had not notified DR-TB cases during 2017–2021. The notification was higher in inter-state border areas and the coastal belt of the district. The notification of DR-TB cases was highest among the 45–59 age group (17/100,000), followed by the 60 above group (11/100,000). Males and those living below the poverty line had higher notification rates. Among the outcomes evaluated 118 DR-TB patients, 89 (75.4%) had favorable outcomes, whereas the remaining 24.6% had unfavorable outcomes (death 18 [15.3%], loss to follow-up 7 [6%], and treatment failure 4 [3.4%]). Age more than 45 years adjusted odds ratio (aOR) 3.1 (95% confidence interval [CI] 1.1–8.8), income category below the poverty line aOR 6 (95% CI 1.2–28.6), admitted at least twice during treatment aOR 9.2 (95% CI 2.8–30.3), and body mass index at diagnosis <18.5 kg/m2 aOR 3 (95% CI 1.1–10.3) were found to be significantly associated with unfavorable treatment outcomes. Conclusion: DR-TB notifications have increased in the Kasaragod district from 2017 to 2021, with a high burden among males aged 45 years and above. The favorable treatment outcome is better than the national and state average. Regular monitoring and follow-up of multidrug-resistant patients with low incomes, above 45 years, and underweight may improve the final treatment outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Hepatitis-B virus infection in India: Findings from a nationally representative serosurvey, 2017-18

Author

Karunakaran, T., Jose, Annamma, Augustine, D., Govindhasamy, C., Daniel Rajasekar, T., Jeyakumar, A., Suresh, A., Ashok Kumar, P., Sivakumar, R., Banerjee John, J.W., Murhekar, Manoj V., Santhosh Kumar, Muthusamy, Kamaraj, P., Khan, Siraj Ahmed, Allam, Ramesh Reddy, Barde, Pradip, Dwibedi, Bhagirathi, Kanungo, Suman, Mohan, Uday, Mohanty, Suman Sundar, Roy, Subarna, Sagar, Vivek, Savargaonkar, Deepali, Tandale, Babasaheb V., Topno, Roshan Kamal, Girish Kumar, C.P., Sabarinathan, R., Bitragunta, Sailaja, Grover, Gagandeep Singh, Lakshmi, P.V.M., Mishra, Chandra Mauli, Sadhukhan, Provash, Sahoo, Prakash Kumar, Singh, S.K., Yadav, Chander Prakash, Kumar, Rajesh, Dutta, Shanta, Toteja, G.S., Gupta, Nivedita, and Mehendale, Sanjay M.

Published
2020
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37. Population-Based Serosurvey for Severe Acute Respiratory Syndrome Coronavirus 2 Transmission, Chennai, India

Author

Selvaraju, Sriram, Kumar, Muthusamy Santhosh, Thangaraj, Jeromie Wesley Vivian, Bhatnagar, Tarun, Saravanakumar, Velusamy, Kumar, Chethrapilly Purushothaman Girish, Sekar, Krithikaa, Ilayaperumal, Ezhilarasan, Sabarinathan, Ramasamy, Jagadeesan, Murugesan, Hemalatha, Masanam Sriramulu, and Murhekar, Manoj Vasant

Subjects
Diagnosis, Identification and classification, Care and treatment, Models, Methods, Disease transmission -- Models, Sentinel surveillance -- Methods, COVID-19 -- Diagnosis -- Care and treatment, Immunoglobulin G -- Identification and classification, Sentinel health events -- Methods
Abstract

On August 15, 2020, India had the third highest number of coronavirus disease (COVID-19) cases globally (1). The Indian state of Tamil Nadu reported 332,105 cases and 5,641 deaths on [...]

Published
2021
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40. Dynamic alterations in monocyte numbers, subset frequencies and activation markers in acute and convalescent COVID-19 individuals

Author

Rajamanickam, Anuradha, Kumar, Nathella Pavan, Pandiarajan, Arul Nancy, Selvaraj, Nandhini, Munisankar, Saravanan, Renji, Rachel Mariam, Venkatramani, Vijayalakshmi, Murhekar, Manoj, Thangaraj, Jeromie W. V., Kumar, Muthusamy Santhosh, Kumar, C. P. Girish, Bhatnagar, Tarun, Ponnaiah, Manickam, Sabarinathan, R., Saravanakumar, V., and Babu, Subash

Published
2021
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41. Burden of dengue infection in India, 2017: a cross-sectional population based serosurvey

Author

Murhekar, Manoj V, Kamaraj, P, Kumar, Muthusamy Santhosh, Khan, Siraj Ahmed, Allam, Ramesh Reddy, Barde, Pradip, Dwibedi, Bhagirathi, Kanungo, Suman, Mohan, Uday, Mohanty, Suman Sundar, Roy, Subarna, Sagar, Vivek, Savargaonkar, Deepali, Tandale, Babasaheb V, Topno, Roshan Kamal, Sapkal, Gajanan, Kumar, C P Girish, Sabarinathan, R, Kumar, Velusamy Saravana, Bitragunta, Sailaja, Grover, Gagandeep Singh, Lakshmi, P V M, Mishra, Chandra Mauli, Sadhukhan, Provash, Sahoo, Prakash Kumar, Singh, S K, Yadav, Chander Prakash, Bhagat, Asha, Srivastava, Rashi, Dinesh, E Ramya, Karunakaran, T, Govindhasamy, C, Rajasekar, T Daniel, Jeyakumar, A, Suresh, A, Augustine, D, Kumar, P Ashok, Kumar, Rajesh, Dutta, Shanta, Toteja, G S, Gupta, Nivedita, and Mehendale, Sanjay M

Published
2019
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43. Triaging for Severe Illness amongst Adults with Tuberculosis Followed by Referral and Inpatient Care: A Statewide Pilot in Tamil Nadu, India

Author

Shewade, Hemant D., primary, Frederick, Asha, additional, Kalyanasundaram, Madhanraj, additional, Chadwick, Joshua, additional, Kiruthika, G, additional, Rajasekar, T Daniel, additional, Gayathri, K, additional, Vijayaprabha, R, additional, Sabarinathan, R, additional, Shivakumar, Shri Vijay Bala Yogendra, additional, Jeyashree, Kathiresan, additional, Bhavani, P K, additional, Aarthi, S, additional, Suma, K V, additional, Pathinathan, Delphina P., additional, Parthasarathy, Raghavan, additional, Nivetha, M Bhavani, additional, Thampi, Jerome G, additional, Chidambaram, Deiveegan, additional, Bhatnagar, Tarun, additional, Lokesh, S, additional, Devika, Shanmugasundaram, additional, Laux, Timothy S., additional, Viswanathan, Stalin, additional, Sridhar, R, additional, Krishnamoorthy, K, additional, Sakthivel, M, additional, Karunakaran, S, additional, Rajkumar, S, additional, Ramachandran, M., additional, Kanagaraj, K D, additional, Durai, V P, additional, Saravanan, R, additional, Sugantha, A, additional, Khan, S Zufire Hassan Mohamed, additional, Sangeetha, P, additional, Vasudevan, R, additional, Nedunchezhian, R, additional, Sankari, M, additional, Jeevanandam, N, additional, Ganapathy, S, additional, Rajasekaran, V, additional, Mathavi, T, additional, Rajaprakash, A R, additional, Murali, Lakshmi, additional, Pugal, U, additional, Sundaralingam, K, additional, Savithri, S, additional, Vellasamy, S, additional, Dheenadayal, D, additional, Ashok, P, additional, Sudhakar, R, additional, Rajan, K P, additional, Tharageshwari, N, additional, Chokkalingam, D, additional, Anandrajkumar, S M, additional, Selvavinayagam, T S, additional, Padmapriyadarshini, C, additional, Ramachandran, Ranjani, additional, and Murhekar, Manoj V, additional

Published
2024
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44. Baseline findings of a multicentric ambispective cohort study (2021–2022) among hospitalised mucormycosis patients in India

Author

Abdulkader, Rizwan Suliankatchi, primary, Ponnaiah, Manickam, additional, Bhatnagar, Tarun, additional, S, Devika, additional, Rozario, Amanda G.A, additional, K, Gayathri, additional, Mohan, Malu, additional, E, Michaelraj, additional, Saravanakumar, Divya, additional, Moorthy, Aditya, additional, Tyagi, Amit Kumar, additional, Parmar, Bhagirathsinh D, additional, Devaraja, K, additional, Medikeri, Gaurav, additional, Ojah, Jutika, additional, Srivastava, Kajal, additional, K, Karthikeyan, additional, Das, Nandini, additional, B, Niharika, additional, Sharma, Parul, additional, Kumar Parida, Pradipta, additional, Kumar Saravanam, Prasanna, additional, Kulkarni, Praveen, additional, S, Priya, additional, Patil S, Pushpa, additional, Kumar Bagla, Rahul, additional, D, Ramesh, additional, S Melkundi, Renuka, additional, S Satpute, Satish, additional, Narayanan, Seetharaman, additional, Jahagirdar, Shubhashri, additional, Dube, Simmi, additional, Kumar Panigrahi, Sunil, additional, Babu D, Surendra, additional, Saini, Vaibhav, additional, Singh Saxena, Rita, additional, Srivastava, Abhinav, additional, Chandra Baishya, Achyut, additional, Garg, Ajai, additional, Kumar Mishra, Amit, additional, Jyoti Talukdar, Anjan, additional, Kankaria, Ankita, additional, Karat, Arathi, additional, Sundaresh Kumar, Arul, additional, Chug, Ashi, additional, Vankundre, Ashok, additional, Ramaswamy, Balakrishnan, additional, MB, Bharathi, additional, R Jadav, Bhargav, additional, Dhiwakar, Muthuswamy, additional, Ghate, Girija, additional, Shah, Hardik V, additional, Saha, Ipsita, additional, Sivapuram, Kavya, additional, J Joshi, Krupal, additional, Singh, Mahendra, additional, Chand Bairwa, Mukesh, additional, K, Divya, additional, E, Muthurajesh, additional, Samagh, Navneh, additional, Dinakaran, Nethra, additional, Gupta, Nikhil, additional, Gupta, Nitin, additional, M Nagarkar, Nitin, additional, Solanki, Nitin, additional, Kumar Panda, Prasan, additional, Bachalli, Prithvi, additional, Shanbag, Raghunath, additional, Patil, Rajashri, additional, Kumar A, Rajesh, additional, Narayan Patil, Rakesh, additional, Thookkanaickenpalayam Vijayaraghavan, Ramanikanth, additional, Hanumantappa, Ramesh, additional, A, Rathinavel, additional, Mandal, Saleel Kumar, additional, Kishve, Sanjay Pandharinath, additional, Varghese Thomas, Sara, additional, Sarkar, Saurav, additional, Thakur, Shalini, additional, Patil, Siddaram, additional, Lakshmanan, Somu, additional, D Rao, Srinivas, additional, V, Sumathi, additional, Nayak, Tulasi, additional, Dixit, Umesh R, additional, B, Unnikrishnan, additional, Backiavathy, Varsha, additional, Shenoy, Vijendra, additional, Hallur, Vinay Kumar, additional, Bhatnagar, Aparna, additional, and Murhekar, Manoj V, additional

Published
2024
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45. Interplay of missed opportunity for vaccination and poor response to the vaccine led to measles outbreak in a slum area of Eastern Mumbai, India

Author

Yadav, Reetika Malik, primary, Gomare, Mangala, additional, Gaikwad, Arun, additional, Waghmare, Upalimitra, additional, Betodkar, Utkarsh, additional, Vashi, Meeta Dhaval, additional, Kamal, Vineet Kumar, additional, Thangaraj, Jeromie Wesley Vivian, additional, Bangar, Sampada, additional, Bhatnagar, Tarun, additional, and Murhekar, Manoj, additional

Published
2024
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46. Neutralizing antibody responses to SARS-CoV-2 Omicron variants: Post six months following two-dose & three-dose vaccination of ChAdOx1 nCoV-19 or BBV152

Author

Sapkal, GajananN, primary, Yadav, PragyaD, additional, Sardana, Viren, additional, Deshpande, GururajRao, additional, Shinde, PradnyaV, additional, Vivian Thangaraj, JeromieWesley, additional, George, LeyannaS, additional, Patil, DeepakY, additional, Sahay, RimaR, additional, Shete, AnitaM, additional, Joshi, Madhavi, additional, Murhekar, Manoj, additional, Godbole, Sheela, additional, Gupta, Nivedita, additional, Prakash, Satyartha, additional, Rathore, Mamta, additional, Ujjainiya, Rajat, additional, Singh, AjayPratap, additional, Mishra, Aastha, additional, Dash, Debasis, additional, Chaudhary, Kumardeep, additional, and Sengupta, Shantanu, additional

Published
2024
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47. Lessons Learned From a Peer-Supported Differentiated Care and Nutritional Supplementation for People With TB in a Southern Indian State.

Author

Shewade, Hemant Deepak, Jeyakumar Jaisingh, A. James, Ravichandran, Prabhadevi, Pradeep, S. Kiran, Pandurangan, Sripriya, Mohanty, Subrat, Rajasekar, T. Daniel, Vijayaprabha, R., Kiruthika, G., Suma, K. V., Pathinathan, Delphina Peter, Chidambaram, Deiveegan, Sivagami, K., Srinivasan, Anupama, Swamickan, Reuben, Goswami, Amrita, Sivaranjani, D., Ananthakrishnan, Ramya, Frederick, Asha, and Murhekar, Manoj V.

Published
2024
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48. Association between COVID-19 Vaccination (ChAdOx1-S) and Thromboembolic, Thrombocytopenic, Hemorrhagic Events: A Systematic Review and Meta-analysis of Analytical Epidemiological Studies.

Author

Vaman, Raman S., Kumar, Muthusamy S., Jeyashree, Kathiresan, Periasami, Ashok, Abdulkader, Rizwan S., and Murhekar, Manoj

Subjects
IMMUNIZATION, MEDICAL information storage & retrieval systems, CEREBRAL embolism & thrombosis, VEINS, VENOUS thrombosis, COVID-19 vaccines, META-analysis, DESCRIPTIVE statistics, THROMBOCYTOPENIA, SYSTEMATIC reviews, MEDLINE, THROMBOEMBOLISM, ADVERSE health care events, CONFIDENCE intervals, HEMORRHAGE, DISEASE risk factors
Abstract

We conducted a systematic review of analytical epidemiological studies to assess the association between ChAdOx1-S vaccination and thromboembolic, thrombocytopenic, and hemorrhagic events. We searched Medline, Embase, Google Scholar, WHO-COVID-19 database, and medRxiv for studies evaluating the association between ChAdOx1-S and vascular events. Primary outcomes of interest were cerebral venous sinus thrombosis, peripheral venous thrombosis (PVT), and thrombocytopenia. Two independent reviewers screened for eligible studies, extracted data, and assessed the risk of bias. The DerSimonian-Laird random effects model was used to pool the incidence rate ratios (IRRs) separately for the first and second doses. Heterogeneity was assessed using I2 statistics. Twenty studies were included, of which 11 were self-controlled case series, and nine were cohort studies (254 million participants). Pooling of 17 studies showed a higher risk of cerebrovascular thrombosis (IRR = 3.5, 95% CI = 2.2-5.4, I² = 79%), PVT (IRR = 2.0, 95% CI = 1.1-3.5, I² = 95%) and thrombocytopenia (IRR = 1.6, 95% CI = 1.4-1.9, I² = 93%) among those who received ChAdOx1-S vaccination as compared to controls. No increased risk was seen after the second dose or for secondary outcomes. There is moderate-to-high certainty of the evidence for the increased risk of cerebral venous sinus thrombosis, PVT, and thrombocytopenia following the first dose of the ChAdOx1-S vaccine. Systematic Review Registration: PROSPERO CRD42022372768. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Validation of the Scrub Typhus Encephalitis Assessment Tool for the Management of Acute Encephalitis Syndrome.

Author

Rath, Rama Shankar, Abdulkader, Rizwan S., Srivastava, Neha, Deval, Hirawati, Gupta, Urmila, Sharma, Bhoopendra, Mittal, Mahim, Singh, Vijay, Kumar, Manish, Kharya, Pradip, Gupta, Nivedita, Kant, Rajni, Murhekar, Manoj, and Mittal, Mahima

Subjects
CEREBROSPINAL fluid, ENCEPHALITIS, MACHINE learning, CHILD mortality, SENSITIVITY & specificity (Statistics)
Abstract

Introduction: Acute encephalitis syndrome (AES) is one of the important causes of mortality among children in India. Active management of the cases, followed by addressing the cause of AES, is the key strategy for preventing mortality. Lack of laboratory facility and difficulty of sampling blood and cerebrospinal fluid (CSF) for assessing causes is one of the important barriers to early initiation of treatment. The main objective of the study is to validate the Scrub Typhus Encephalitis Assessment Tool (SEAT) for the management of AES. Methods: The study is a continuation of a study conducted in a tertiary care hospital in Eastern Uttar Pradesh. A machine learning (LightGBM) model was built to predict the probability of scrub typhus diagnosis among patients with acute encephalitis. Three models were built: one with sociodemographic characters, the second with Model 1 variables and blood parameters, and the third with Model 2 variables and CSF parameters. Results: The sensitivity of diagnosing the scrub typhus case was 71%, 77.5%, and 83% in Model 1, Model 2, and Model 3, respectively, and specificity was 61.5%, 75.5%, and 76.3%, respectively, in the models. In Model 1 fever duration, in Models 2 and 3, neutrophil/lymphocyte ratio was the most important predictor for differentiating the scrub and nonscrub cases. Conclusion: With the available sensitivity and specificity of the tool, the SEAT can be a valuable tool for the prediction of scrub typhus as a cause of AES cases in remote areas. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Sentinel Surveillance for Congenital Rubella Syndrome — India, 2016–2017

Author

Murhekar, Manoj, Bavdekar, Ashish, Benakappa, Asha, Santhanam, Sridhar, Singh, Kuldeep, Verma, Sanjay, Sapkal, Gajanan N., Gupta, Nivedita, Verghese, Valsan Philip, Viswanathan, Rajlakshmi, Abraham, Asha Mary, Choudhary, Shyama, Deshpande, Gururajrao N., George, Suji, Goyal, Garima, Gupta, Parul Chawla, Jhamb, Ishani, John, Deepa, Philip, Swetha, Kadam, Sandeep, Sachdeva, Ravinder Kaur, Kumar, Praveen, Lepcha, Anjali, Mahantesh, S., Manasa, S., Nehra, Urvashi, Munjal, Sanjay Kumar, Nag, Vijaya Lakshmi, Naik, Sadanand, Raj, Naga, Ram, Jagat, Ratho, R.K., Raut, C.G., Rohit, Manoj Kumar, Sabarinathan, R., Shah, Sanjay, Singh, Pratibha, Singh, Mini P., Tiwari, Ashish, and Vaid, Neelam

Published
2018

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