Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2

  1. Salwa Naushin
  2. Viren Sardana
  3. Rajat Ujjainiya
  4. Nitin Bhatheja
  5. Rintu Kutum
  6. Akash Kumar Bhaskar
  7. Shalini Pradhan
  8. Satyartha Prakash
  9. Raju Khan
  10. Birendra Singh Rawat
  11. Karthik Bharadwaj Tallapaka
  12. Mahesh Anumalla
  13. Giriraj Ratan Chandak
  14. Amit Lahiri
  15. Susanta Kar
  16. Shrikant Ramesh Mulay
  17. Madhav Nilakanth Mugale
  18. Mrigank Srivastava
  19. Shaziya Khan
  20. Anjali Srivastava
  21. Bhawana Tomar
  22. Murugan Veerapandian
  23. Ganesh Venkatachalam
  24. Selvamani Raja Vijayakumar
  25. Ajay Agarwal
  26. Dinesh Gupta
  27. Prakash M Halami
  28. Muthukumar Serva Peddha
  29. Gopinath M Sundaram
  30. Ravindra P Veeranna
  31. Anirban Pal
  32. Vinay Kumar Agarwal
  33. Anil Ku Maurya
  34. Ranvijay Kumar Singh
  35. Ashok Kumar Raman
  36. Suresh Kumar Anandasadagopan
  37. Parimala Karuppanan
  38. Subramanian Venkatesan
  39. Harish Kumar Sardana
  40. Anamika Kothari
  41. Rishabh Jain
  42. Anupama Thakur
  43. Devendra Singh Parihar
  44. Anas Saifi
  45. Jasleen Kaur
  46. Virendra Kumar
  47. Avinash Mishra
  48. Iranna Gogeri
  49. Geethavani Rayasam
  50. Praveen Singh
  51. Rahul Chakraborty
  52. Gaura Chaturvedi
  53. Pinreddy Karunakar
  54. Rohit Yadav
  55. Sunanda Singhmar
  56. Dayanidhi Singh
  57. Sharmistha Sarkar
  58. Purbasha Bhattacharya
  59. Sundaram Acharya
  60. Vandana Singh
  61. Shweta Verma
  62. Drishti Soni
  63. Surabhi Seth
  64. Sakshi Vashisht
  65. Sarita Thakran
  66. Firdaus Fatima
  67. Akash Pratap Singh
  68. Akanksha Sharma
  69. Babita Sharma
  70. Manikandan Subramanian
  71. Yogendra S Padwad
  72. Vipin Hallan
  73. Vikram Patial
  74. Damanpreet Singh
  75. Narendra Vijay Tripude
  76. Partha Chakrabarti
  77. Sujay Krishna Maity
  78. Dipyaman Ganguly
  79. Jit Sarkar
  80. Sistla Ramakrishna
  81. Balthu Narender Kumar
  82. Kiran A Kumar
  83. Sumit G Gandhi
  84. Piyush Singh Jamwal
  85. Rekha Chouhan
  86. Vijay Lakshmi Jamwal
  87. Nitika Kapoor
  88. Debashish Ghosh
  89. Ghanshyam Thakkar
  90. Umakanta Subudhi
  91. Pradip Sen
  92. Saumya Ray Chaudhury
  93. Rashmi Kumar
  94. Pawan Gupta
  95. Amit Tuli
  96. Deepak Sharma
  97. Rajesh P Ringe
  98. Amarnarayan D
  99. Mahesh Kulkarni
  100. Dhansekaran Shanmugam
  101. Mahesh S Dharne
  102. Sayed G Dastager
  103. Rakesh Joshi
  104. Amita P Patil
  105. Sachin N Mahajan
  106. Abujunaid Habib Khan
  107. Vasudev Wagh
  108. Rakesh Kumar Yadav
  109. Ajinkya Khilari
  110. Mayuri Bhadange
  111. Arvindkumar H Chaurasiya
  112. Shabda E Kulsange
  113. Krishna Khairnar
  114. Shilpa Paranjape
  115. Jatin Kalita
  116. Narahari G Sastry
  117. Tridip Phukan
  118. Prasenjit Manna
  119. Wahengbam Romi
  120. Pankaj Bharali
  121. Dibyajyoti Ozah
  122. Ravi Kumar Sahu
  123. Elapavalooru VSSK Babu
  124. Rajeev Sukumaran
  125. Aiswarya R Nair
  126. Prajeesh Kooloth Valappil
  127. Anoop Puthiyamadam
  128. Adarsh Velayudhanpillai
  129. Kalpana Chodankar
  130. Samir Damare
  131. Yennapu Madhavi
  132. Ved Varun Aggarwal
  133. Sumit Dahiya
  134. Anurag Agrawal
  135. Debasis Dash  Is a corresponding author
  136. Shantanu Sengupta  Is a corresponding author
  1. CSIR-Institute of Genomics and Integrative Biology, India
  2. Academy of Scientific and Innovative Research (AcSIR), India
  3. CSIR-Advanced Materials and Processes Research Institute, India
  4. CSIR-Central Building Research Institute, India
  5. CSIR-Centre for Cellular Molecular Biology, India
  6. CSIR-Central Drug Research Institute, India
  7. CSIR-Central Electrochemical Research Institute, India
  8. CSIR-Central Electronics Engineering Research Institute, India
  9. CSIR-Central Food Technological Research Institute, India
  10. CSIR-Central Institute of Medicinal Aromatic Plants, India
  11. CSIR-Central Institute of Mining and Fuel Research, India
  12. CSIR-Central Leather Research Institute, India
  13. CSIR-Central Scientific Instruments Organization, India
  14. CSIR-Central Salt Marine Chemicals Research Institute, India
  15. CSIR Fourth Paradigm Institute, India
  16. CSIR- Headquarters, Rafi Marg, India
  17. CSIR-Institute of Himalayan Bioresource Technology, India
  18. CSIR-Indian Institute of Chemical Biology, India
  19. CSIR-Indian Institute of Chemical Technology, India
  20. CSIR-Indian Institute of Integrative Medicine, India
  21. CSIR-Indian Institute of Petroleum, India
  22. CSIR-Institute of Minerals and Materials Technology, India
  23. CSIR-Institute of Microbial Technology, India
  24. CSIR- National Aerospace Laboratories, India
  25. CSIR-National Chemical Laboratory, India
  26. CSIR-National Environmental Engineering Research Institute, India
  27. CSIR-North - East Institute of Science and Technology, India
  28. CSIR-National Geophysical Research Institute, India
  29. CSIR-National Institute for Interdisciplinary Science and Technology, India
  30. CSIR-National Institute of Oceanography, India
  31. CSIR-National Institute of Science, Technology and Development Studies, India
  32. CSIR-National Physical Laboratory, India

Peer review process

This article was accepted for publication as part of eLife's original publishing model.

History

  1. Version of Record published
  2. Accepted Manuscript published
  3. Accepted
  4. Received

Decision letter

  1. Jameel Iqbal
    Reviewing Editor; James J Peters Veterans Affairs Medical Center, United States
  2. Mone Zaidi
    Senior Editor; Icahn School of Medicine at Mount Sinai, United States
  3. Madhuri Kanitkar
    Reviewer; Armed Force Medical College, India
  4. Manindra Agrawal
    Reviewer; Indian Institute of Technology Kanpur, India

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Acceptance summary:

This publication is the first large scale COVID-19 seroprevalence study from India, and demonstrates that more than a hundred million individuals were infected. While this rate is notably higher than officially reported statistics, interestingly 3 month and 5-6 month follow-up analyses demonstrated that neutralization antibody activity significantly declines in about a quarter of individuals, most of whom remain seropositive. Overall this study’s findings have implications for reinfection as well as shed light on the severity of the initial COVID-19 infection wave in India.

Decision letter after peer review:

Thank you for submitting your article "Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Mone Zaidi as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Madhuri Kanitkar (Reviewer #2); Manindra Agrawal (Reviewer #3).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

There was a marked debate amongst the reviewers regarding the validity of the findings and their usefulness. Overall, the reviewers felt that further expansion of the observational cohort make strengthen novel findings. There a numerous suggestions for improvement and narrowing focus on what can be concluded from the investigation.

1. Include three month follow-up data if available for the cohorts.

2. Narrow focus to limit conclusions on diet, smoking etc. as the reviewers felt that the study was not designed or powered to look at those differences.

Reviewer #1 (Recommendations for the authors):

My recommendation would be that the manuscript, while interesting, largely consists of a series of observations on a cohort that can hardly be said to be representative of the larger Indian population. It is this that I see to be the main defect of the manuscript. I tried hard to see if this study might at all be relevant to a broader understanding of COVID-19 in India but concluded that there were too many confounding variables – the selection of employees and contract workers in CSIR laboratories already speakers to a higher-than-average awareness of COVID-19. In addition, the bias towards metropolitan areas is a defect. The fact that the seroprevalence for the city of Pune provides results that are quite different from others for the same city is a cause for worry. As a last point, I thought that the writing could have been tighter and more targeted, especially in the introduction.

Reviewer #2 (Recommendations for the authors):

The authors of this well-designed cohort study for sero-positivity need to be complimented. A few suggestions for the study are as follows:

1. Table 1 – Title may specify Demographics of the Seropositive individuals.

2. The symptoms sought for in the history have not been clarified in the questionnaire and being recall minor symptoms are likely to be under reported. A table/figure may be added

3. It is not clear how some individuals have completed six months for repeat antibody titers when the study implies it was conducted in Aug Sept.

4. In case children of this close-knit cohort can be included the study can give an additional insight into the role children will play as schools open up.

Reviewer #3 (Recommendations for the authors):

No specific comments.

https://doi.org/10.7554/eLife.66537.sa1

Author response

Essential revisions:

There was a marked debate amongst the reviewers regarding the validity of the findings and their usefulness. Overall, the reviewers felt that further expansion of the observational cohort make strengthen novel findings. There a numerous suggestions for improvement and narrowing focus on what can be concluded from the investigation.

1. Include three month follow-up data if available for the cohorts.

Thank you for the suggestion, which has led to important insights. While full cohort follow-up is not yet available, we have now obtained 3 month follow-up of 607 people who were seropositive at baseline (see revised Figure 4A and 4B), and 5-6 month follow-up for 175 individuals (now added as Figure 4C and 4D) a. We note that amongst those who passed a neutralization antibody surrogate threshold at baseline, 20-30% fail to pass that mark by 6 months. (Figure 4 Source Data) Yet, only 5% lose seropositivity, suggesting declining immunity despite persisting seropositivity. This may be relevant to the current course of increasing outbreaks after the previous peak in October 2020, and the manuscript discussion has been modified accordingly.

2. Narrow focus to limit conclusions on diet, smoking etc. as the reviewers felt that the study was not designed or powered to look at those differences.

We agree that the observations in regard to diet and smoking are only hypothesis generating and need specifically designed studies to confirm the findings. We have also mentioned in the manuscript that associations found between sero-positivity and some of the parameters should be confirmed with studies specifically designed for this purpose. As suggested, we state that “The associations with diet and smoking are intriguing, but preliminary. It has been proposed that a fiber-rich diet may play an important role in COVID-19 through anti-inflammatory properties by modification of gut microbiota.25 A recent review has highlighted the role of trace elements, nutraceuticals and probiotics in COVID-19.26 The negative association with smoking has been reported elsewhere, but not shown to be causal.27-31 Further exploration is necessary before reaching any conclusions, especially since seropositivity is an imperfect marker of infection-risk and may equally well be explained by altered antibody response and dynamics”

Reviewer #1 (Recommendations for the authors):

My recommendation would be that the manuscript, while interesting, largely consists of a series of observations on a cohort that can hardly be said to be representative of the larger Indian population. It is this that I see to be the main defect of the manuscript. I tried hard to see if this study might at all be relevant to a broader understanding of COVID-19 in India but concluded that there were too many confounding variables – the selection of employees and contract workers in CSIR laboratories already speakers to a higher-than-average awareness of COVID-19. In addition, the bias towards metropolitan areas is a defect. The fact that the seroprevalence for the city of Pune provides results that are quite different from others for the same city is a cause for worry. As a last point, I thought that the writing could have been tighter and more targeted, especially in the introduction.

We agree with the reviewer that this is a very specific cohort, largely urban, and with higher levels of education than average. We further agree that the utility of this cohort is not in making general statements about the population, but rather in deriving specific insights for which the cohort is best suited. We enumerate some of them that are present in this manuscript.

a. It is as important to understand the relative degree of spread between Indian cities, where a combination of denser population and indoor lives has led to the greatest spread of disease. Since pandemics are typically self-limiting, regions with greater spread are further along the course and can expect declines faster. This provides useful insight for public health strategy. While our cohort does not necessarily represent the average population, it is similar between cities, something that is not true for any other survey. The ICMR national sero-survey is a random selection of districts and is heavily rural biased.1 While that is important, that is not where fast growing outbreaks are likely based on a very outdoor life and lower density. Other city-wise serosurveys are variable in target population as well as methodology and cannot be easily compared.2-5 Thus our data is the first that permits comparison between many important urban regions of India, showing which regions were more advanced along the course and where future outbreaks were still likely. We note here that some of the regions identified by this survey as high risk such as Kerala, interior Maharashtra, amongst others, are where the outbreaks continued until much later.

b. The CSIR cohort has the added advantage of greater baseline data and repeated access, we are able to determine antibody stability, as shown, and possible correlates

c. The cohort is well suited to understanding clinical associations of SARS CoV2 infections such as symptom rate and severity amongst its participants as well as associations of infection risks (using seropositivity as an imperfect surrogate).

d. The Pune city sero-surveillance which has been pointed out by the reviewer was a survey of Pune’s five most affected sub-wards and not the Pune population in general. 6 Despite all the limitations, which we accept in the prior comment, our overall crude positivity rate of 10% is very similar to that of the ICMR national serosurvey, and in general the patterns we see are along the lines of what is known about severity of outbreaks. Thus, there is no real evidence to the contrary that would establish inaccuracy of the trends seen by us, and we respectfully note that surprising findings may be the most valuable ones. In fact, seeing current trends of rising cases in Maharashtra, including in Pune, when compared to other cities, our survey values may have been more correct.

Reviewer #2 (Recommendations for the authors):

The authors of this well-designed cohort study for sero-positivity need to be complimented. A few suggestions for the study are as follows:

1. Table 1 – Title may specify Demographics of the Seropositive individuals.

Thank you for the correction. It has been addressed and the title now changed.

2. The symptoms sought for in the history have not been clarified in the questionnaire and being recall minor symptoms are likely to be under reported. A table/figure may be added

We regret the lack of clarity. Supplementary File 2 contains the frequency of symptoms reported as per the questionnaire. We agree that minor symptoms are usually underreported, but during these times of SARS-CoV-2 pandemic, people have become highly aware of their symptoms.

3. It is not clear how some individuals have completed six months for repeat antibody titers when the study implies it was conducted in Aug Sept.

For CSIR-IGIB, the study started in May-June and hence we were able to obtain minimal samples at 6 months completion. This is also the reason, CSIR-IGIB had been removed from figure 2B analysis as stated in the manuscript.

4. In case children of this close-knit cohort can be included the study can give an additional insight into the role children will play as schools open up.

We agree that children could provide specific insights into transmission dynamics specifically when schools open up but the current ethical approval didn’t permit us to have reporting for children and hence would be taken care of in future.

References:

1. Murhekar M, Bhatnagar T, Selvaraju S, et al. Prevalence of SARS-CoV-2 infection in India: Findings from the national serosurvey, May-June 2020. Indian Journal of Medical Research 2020;152(1):48-60. doi: 10.4103/ijmr.IJMR_3290_20

2. Ray A, Singh K, Chattopadhyay S, et al. Seroprevalence of anti-SARS-CoV-2 IgG antibodies in hospitalized patients at a tertiary referral center in North India. medRxiv 2020:2020.08.22.20179937. doi: 10.1101/2020.08.22.20179937

3. Satpati P, Sarangi SS, Gantait K, et al. Sero-surveillance (IgG) of SARS-CoV-2 among Asymptomatic General population of Paschim Medinipur District, West Bengal, India(Conducted during last week of July and 1st week of August 2020) – A Joint Venture of VRDL Lab (ICMR), Midnapore Medical College and amp; Hospital and amp; Department of Health and Family Welfare,Govt. of West Bengal, Paschim Medinipur. medRxiv 2020:2020.09.12.20193219. doi: 10.1101/2020.09.12.20193219

4. Babu GR, Sundaresan R, Athreya S, et al. The burden of active infection and anti-SARS-CoV-2 IgG antibodies in the general population: Results from a statewide survey in Karnataka, India. medRxiv 2020:2020.12.04.20243949. doi: 10.1101/2020.12.04.20243949

5. Sharma N, Sharma P, Basu S, et al. The seroprevalence and trends of SARS-CoV-2 in Delhi, India: A repeated population-based seroepidemiological study. medRxiv 2020:2020.12.13.20248123. doi: 10.1101/2020.12.13.20248123

6. Kulkarni P. “Pune’s first sero-survey shows 51.5% citizens have Covidantibodies”: The Times of India, 18 August 2020.; 2020 [Available from: https://timesofindia.indiatimes.com/city/pune/citys-first-sero-survey-shows-51-5-citizens-have-covid-antibodies/articleshow/77602008.cms].

7. Stadlbauer D, Tan J, Jiang K, et al. Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York City. Nature 2021;590(7844):146-50. doi: 10.1038/s41586-020-2912-6

8. Bauch CT. Estimating the COVID-19 R number: a bargain with the devil? The Lancet Infectious Diseases 2021;21(2):151-53. doi: 10.1016/S1473-3099(20)30840-9

9. Mandal M, Mandal S. COVID-19 pandemic scenario in India compared to China and rest of the world: a data driven and model analysis. medRxiv 2020:2020.04.20.20072744. doi: 10.1101/2020.04.20.20072744

10. 2014 [cited 2020]. [Available from: https://censusindia.gov.in/2011-Common/Sample_Registration_System.html].

11. Conte L, Toraldo DM. Targeting the gut–lung microbiota axis by means of a high-fibre diet and probiotics may have anti-inflammatory effects in COVID-19 infection. Therapeutic Advances in Respiratory Disease 2020;14:1753466620937170. doi: 10.1177/1753466620937170

12. Jayawardena R, Sooriyaarachchi P, Chourdakis M, et al. Enhancing immunity in viral infections, with special emphasis on COVID-19: A review. Diabetes and metabolic syndrome 2020;14(4):367-82. doi: 10.1016/j.dsx.2020.04.015 [published Online First: 2020/04/26]

13. Patidar GK, Dhiman Y. Distribution of ABO and Rh (D) Blood groups in India: A systematic review. ISBT Science Series;n/a(n/a) doi: https://doi.org/10.1111/voxs.12576

14. Golinelli D, Boetto E, Maietti E, et al. The association between ABO blood group and SARS-CoV-2 infection: A meta-analysis. PLOS ONE 2020;15(9):e0239508. doi: 10.1371/journal.pone.0239508

15. Zhao J, Yang Y, Huang H, et al. Relationship between the ABO Blood Group and the COVID-19 Susceptibility. medRxiv 2020:2020.03.11.20031096. doi: 10.1101/2020.03.11.20031096

16. Wu Y, Feng Z, Li P, et al. Relationship between ABO blood group distribution and clinical characteristics in patients with COVID-19. Clinica Chimica Acta 2020;509:220-23. doi: https://doi.org/10.1016/j.cca.2020.06.026

17. Latz CA, DeCarlo C, Boitano L, et al. Blood type and outcomes in patients with COVID-19. Ann Hematol 2020;99(9):2113-18. doi: 10.1007/s00277-020-04169-1 [published Online First: 07/12]

18. Göker H, Aladağ Karakulak E, Demiroğlu H, et al. The effects of blood group types on the risk of COVID-19 infection and its clinical outcome. Turk J Med Sci 2020;50(4):679-83. doi: 10.3906/sag-2005-395

19. Barnkob MB, Pottegård A, Støvring H, et al. Reduced prevalence of SARS-CoV-2 infection in ABO blood group O. Blood Adv 2020;4(20):4990-93. doi: 10.1182/bloodadvances.2020002657

https://doi.org/10.7554/eLife.66537.sa2

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  1. Salwa Naushin
  2. Viren Sardana
  3. Rajat Ujjainiya
  4. Nitin Bhatheja
  5. Rintu Kutum
  6. Akash Kumar Bhaskar
  7. Shalini Pradhan
  8. Satyartha Prakash
  9. Raju Khan
  10. Birendra Singh Rawat
  11. Karthik Bharadwaj Tallapaka
  12. Mahesh Anumalla
  13. Giriraj Ratan Chandak
  14. Amit Lahiri
  15. Susanta Kar
  16. Shrikant Ramesh Mulay
  17. Madhav Nilakanth Mugale
  18. Mrigank Srivastava
  19. Shaziya Khan
  20. Anjali Srivastava
  21. Bhawana Tomar
  22. Murugan Veerapandian
  23. Ganesh Venkatachalam
  24. Selvamani Raja Vijayakumar
  25. Ajay Agarwal
  26. Dinesh Gupta
  27. Prakash M Halami
  28. Muthukumar Serva Peddha
  29. Gopinath M Sundaram
  30. Ravindra P Veeranna
  31. Anirban Pal
  32. Vinay Kumar Agarwal
  33. Anil Ku Maurya
  34. Ranvijay Kumar Singh
  35. Ashok Kumar Raman
  36. Suresh Kumar Anandasadagopan
  37. Parimala Karuppanan
  38. Subramanian Venkatesan
  39. Harish Kumar Sardana
  40. Anamika Kothari
  41. Rishabh Jain
  42. Anupama Thakur
  43. Devendra Singh Parihar
  44. Anas Saifi
  45. Jasleen Kaur
  46. Virendra Kumar
  47. Avinash Mishra
  48. Iranna Gogeri
  49. Geethavani Rayasam
  50. Praveen Singh
  51. Rahul Chakraborty
  52. Gaura Chaturvedi
  53. Pinreddy Karunakar
  54. Rohit Yadav
  55. Sunanda Singhmar
  56. Dayanidhi Singh
  57. Sharmistha Sarkar
  58. Purbasha Bhattacharya
  59. Sundaram Acharya
  60. Vandana Singh
  61. Shweta Verma
  62. Drishti Soni
  63. Surabhi Seth
  64. Sakshi Vashisht
  65. Sarita Thakran
  66. Firdaus Fatima
  67. Akash Pratap Singh
  68. Akanksha Sharma
  69. Babita Sharma
  70. Manikandan Subramanian
  71. Yogendra S Padwad
  72. Vipin Hallan
  73. Vikram Patial
  74. Damanpreet Singh
  75. Narendra Vijay Tripude
  76. Partha Chakrabarti
  77. Sujay Krishna Maity
  78. Dipyaman Ganguly
  79. Jit Sarkar
  80. Sistla Ramakrishna
  81. Balthu Narender Kumar
  82. Kiran A Kumar
  83. Sumit G Gandhi
  84. Piyush Singh Jamwal
  85. Rekha Chouhan
  86. Vijay Lakshmi Jamwal
  87. Nitika Kapoor
  88. Debashish Ghosh
  89. Ghanshyam Thakkar
  90. Umakanta Subudhi
  91. Pradip Sen
  92. Saumya Ray Chaudhury
  93. Rashmi Kumar
  94. Pawan Gupta
  95. Amit Tuli
  96. Deepak Sharma
  97. Rajesh P Ringe
  98. Amarnarayan D
  99. Mahesh Kulkarni
  100. Dhansekaran Shanmugam
  101. Mahesh S Dharne
  102. Sayed G Dastager
  103. Rakesh Joshi
  104. Amita P Patil
  105. Sachin N Mahajan
  106. Abujunaid Habib Khan
  107. Vasudev Wagh
  108. Rakesh Kumar Yadav
  109. Ajinkya Khilari
  110. Mayuri Bhadange
  111. Arvindkumar H Chaurasiya
  112. Shabda E Kulsange
  113. Krishna Khairnar
  114. Shilpa Paranjape
  115. Jatin Kalita
  116. Narahari G Sastry
  117. Tridip Phukan
  118. Prasenjit Manna
  119. Wahengbam Romi
  120. Pankaj Bharali
  121. Dibyajyoti Ozah
  122. Ravi Kumar Sahu
  123. Elapavalooru VSSK Babu
  124. Rajeev Sukumaran
  125. Aiswarya R Nair
  126. Prajeesh Kooloth Valappil
  127. Anoop Puthiyamadam
  128. Adarsh Velayudhanpillai
  129. Kalpana Chodankar
  130. Samir Damare
  131. Yennapu Madhavi
  132. Ved Varun Aggarwal
  133. Sumit Dahiya
  134. Anurag Agrawal
  135. Debasis Dash
  136. Shantanu Sengupta
(2021)
Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2
eLife 10:e66537.
https://doi.org/10.7554/eLife.66537

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https://doi.org/10.7554/eLife.66537