Abstract
Background
Vaccines against the COVID-19 pandemic were introduced in late 2020. The present study has been conducted to study the serious Adverse Events Following Immunization (AEFIs) reported for COVID-19 vaccines from India.
Methods
Secondary data analysis of the causality assessment reports for the 1112 serious AEFIs published by the Ministry of Health & Family Welfare, Government of India, was conducted. For the current analysis, all the reports published till 29.03.2022 were included. The primary outcome variables analyzed were the consistent causal association and the thromboembolic events.
Results
The majority of the serious AEFIs assessed were either coincidental (578, 52%) or vaccine product related (218, 19.6%). All the serious AEFIs were reported among the Covishield (992, 89.2%) and COVAXIN (120, 10.8%) vaccines. Among these, 401 (36.1%) were deaths, and 711 (63.9%) were hospitalized and recovered. On adjusted analysis, females, the younger age group and non-fatal AEFIs showed a statistically significant consistent causal association with COVID-19 vaccination. Thromboembolic events were reported among 209 (18.8%) of the analyzed participants, with a significant association with higher age and case fatality rate.
Conclusion
Deaths reported under serious AEFIs were found to have a relatively lower consistent causal relationship with the COVID-19 vaccines than the recovered hospitalizations in India. No consistent causal association was found between the thromboembolic events and the type of COVID-19 vaccine administered in India.
Keywords: Adverse events following immunization, COVID-19 vaccine, Thromboembolic events, India, Deaths
1. Introduction
Vaccines against the COVID-19 pandemic were introduced in late 2020. Presently multiple vaccines with different dosing schedules are being administered across the world. Vaccines are also being prescribed for children aged 12 years and above. The safety profile of these vaccines is systematically and clinically studied under the trial settings before being approved by the regulatory bodies for marketing. After the approval, they are kept under post-marketing surveillance to identify any safety signals and serious adverse effects. Considering the short time in which we had to find an effective weapon to reign in the COVID-19 pandemic, the majority of these vaccines were approved under the Emergency use listing (EUL). Thus, the post-marketing surveillance of the COVID-19 vaccines becomes even more critical, as these real-world data can help us pick up the safety signals, for better or worse.1 Countries worldwide have their Adverse Events Following Immunization (AEFIs) surveillance systems to capture these safety signals.2 An analysis of the Vigibase reported 103,954 adverse events among 30,523 persons who took the COVID-19 vaccines from 15th December 2020 to 24th January 2021 worldwide.3
India started the COVID-19 vaccination with Covishield and Covaxin vaccines, later including the Sputnik V vaccine. Reports of thromboembolic events (TE) have been reported with AstraZeneca, Covishield's European counterpart. In such cases, the regulatory authorities reviewed the events and found no association with the vaccine.4 India has a specific, passive AEFI reporting system for COVID-19 vaccines, inbuilt within the COWIN application.5 COWIN was formulated to enable beneficiary registration for COVID-19 vaccination in India. India has reported more than 49,819 adverse events as of 30th November 2021. Within that, 1965 serious adverse events were reported.6 It is vital to do a causality assessment of the AEFIs reported, especially all the serious AEFIs. Appropriate AEFI committees should investigate them to identify any new safety signals, increase in the incidence of already known adverse events, and specific association of the AEFI with the vaccine and demography. It is essential to analyze the AEFI causality classification of such serious AEFIs to reveal the causal linkage between the COVID-19 vaccine and the AEFI. Kaur et al analyzed the cardiovascular adverse events reported from the Vigibase database to identify the association with COVID-19 vaccines and reported an association of serious events with age >75 years. However, the study reported the events till 24th January 2021 only, while the COVID-19 vaccine was introduced in India on 16th January 2021. Details on the causality assessment of these events were not available in the study.3 A literature review revealed that no analysis of the causality assessment of serious adverse events following COVID-19 vaccination could be found from India. Hence, we conducted the following analysis to study the serious AEFIs reported for COVID-19 vaccines from India.
2. Methods
Secondary data analysis of the causality assessment reports for the serious AEFIs published by the Ministry of Health & Family Welfare, Government of India, was conducted. Causality assessment of the AEFIs is supposed to be conducted at the varying levels of health administration by a panel of experts. India has constituted a National AEFI committee with independent experts to determine the causality of AEFIs, reported across the country. A National AEFI secretariat has been established to monitor the overall AEFI incidence and assessment of causality. Additionally, a National AEFI Technical Collaborating Centre has been established to facilitate the process. In light of the COVID-19 vaccination drive that started on 15th January 2021 in India, a special group was constituted to conduct a causality assessment of AEFIs following the COVID-19 vaccination.7 The special group comprises of medical specialists, cardiologists, neurologists, pulmonary medicine specialists, and obstetrician-gynaecologists. The results of the causality assessment done by this special group is discussed and approved in the national AEFI committee meeting.7 After removing the names and address, the final approved assessment report is disseminated in the public domain, as an anonymized line list of the National AEFI Committee's causality assessment. For the current analysis, all the reports published till 29.03.2022 were included. The data was entered into MS Excel, and the analysis was conducted using SPSS v20. Descriptive data were expressed in the frequencies and proportions. Chi-square test was applied to determine the statistical significance of association between the consistency of causal association, thromboembolic events, type of vaccine, socio-demographic and clinical characteristics. The primary outcome variables analyzed were the consistent causal association and the thromboembolic events. Adjusted analysis was done using logistic regression by including the variables that had a statistically significant association with the outcome variable in the univariate analysis. The sub-group of thromboembolic events,6,8 reported among the severe and serious AEFI, was also analyzed with the vaccine and vaccinee characteristics. Ethical permission to conduct the analysis was obtained from the Institute Ethics Committee, VMMC & Safdarjung Hospital, New Delhi.
3. Results
As of 29.03.2022, the causality assessment report for 1112 Serious AEFIs has been published in India for COVID-19 vaccination.
All these serious AEFIs were reported among the Covishield (992, 89.2%) and COVAXIN (120, 10.8%) vaccinees. Among these, 401 (36.1%) were deaths, and 711 (63.9%) were hospitalized and recovered. The majority of the AEFIs were reported among females (584, 52.5%) and 15–44 years of age (449, 40.4%). Thromboembolic events were reported among 209 (18.8%) of the cases analyzed. Proportionately, more females with serious AEFIs had taken the COVISHIELD vaccine than COVAXIN, while none of the other demographic features was different between the two vaccines (Table 1).
Table 1.
Demographic and clinical characteristics of the serious AEFI cases reported in India (N = 1112).
| COVISHIELD |
COVAXIN |
Total |
p value | ||||
|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | ||
| Sex | |||||||
| Male | 457 | 46.1 | 71 | 58.2 | 528 | 47.5 | 0.007 |
| Female | 535 | 53.9 | 49 | 40.8 | 584 | 52.5 | |
| Age | |||||||
| 15–44 years | 391 | 39.4 | 58 | 48.3 | 449 | 40.4 | 0.124 |
| 45–59 years | 257 | 25.9 | 30 | 25 | 287 | 25.8 | |
| ≥60 years | 344 | 34.7 | 32 | 26.7 | 376 | 33.8 | |
| Type of AEFI | |||||||
| Death | 367 | 37 | 34 | 28.3 | 401 | 36.1 | 0.062 |
| Severe/Hospitalised & Recovered | 625 | 63 | 86 | 71.7 | 711 | 63.9 | |
| AEFIs | |||||||
| COVID-19 disease | 95 | 9.6 | 10 | 8.3 | 105 | 9.4 | 0.660 |
| Anaphylaxis | 36 | 3.6 | 7 | 5.8 | 43 | 3.9 | 0.237 |
| Allergic Reaction | 46 | 4.6 | 6 | 5 | 52 | 4.7 | 0.859 |
| CVS disease | 285 | 28.7 | 31 | 25.8 | 316 | 28.4 | 0.506 |
| CVA | 71 | 7.2 | 6 | 5 | 77 | 6.9 | 0.379 |
| Thromboembolic events | 189 | 19.1 | 20 | 16.7 | 209 | 18.8 | 0.527 |
The majority of the serious AEFIs assessed were either Coincidental (578, 52%) or Vaccine Product Related (218, 19.6%), followed by Immunization Anxiety-related reactions (145, 13%). Four (0.4%) cases were classified as Immunization Error related reactions. 53 (4.7%) cases were reported as indeterminate or unclassifiable. Among the serious AEFIs reported, the decision on the consistency of causality was available for 945 (85%). Among these 945, a consistent causal association was reported among 367 (38.8%), while 578 (61.2%) were found to have an inconsistent causal association with the vaccine, i.e., coincidental (Table 2).
Table 2.
Proportion of AEFI causality assessment classification between COVISHIELD & COVAXIN(N = 1112).
| AEFI causality assessment classification | COVISHIELD |
COVAXINa |
Total |
|||
|---|---|---|---|---|---|---|
| n | % | n | % | n | % | |
| Vaccine Product Related | 202 | 20.4 | 16 | 13.3 | 218 | 19.6 |
| Immunization Error related reaction | 4 | 0.4 | 0 | 0 | 4 | 0.4 |
| Immunization Anxiety related reaction | 119 | 12 | 26 | 21.7 | 145 | 13 |
| Temporal relationship is consistent but there is insufficient definitive evidence for vaccine causing event | 92 | 9.3 | 10 | 8.3 | 102 | 9.2 |
| Reviewing factors result in conflicting trends of consistency and inconsistency with causal association to immunization | 11 | 1.1 | 0 | 0 | 11 | 1 |
| Coincidental | 517 | 52.1 | 61 | 50.8 | 578 | 52 |
| Unclassifiable | 40 | 4 | 6 | 5 | 46 | 4.1 |
| Indeterminate | 7 | 0.7 | 0 | 0 | 7 | 0.6 |
Vaccine Product Related & Coincidental (COVAXIN)- 1 (0.8%).
Among the serious AEFIs, for which conclusive evidence on causality was available, univariate analysis revealed that a significantly higher proportion of the females (p < 0.001), younger age group (p < 0.001), non-fatal AEFIs (p < 0.001) and the non-thromboembolic events (p < 0.001) showed consistent causal association with COVID-19 vaccination. However, on adjusted analysis, females, the younger age group and non-fatal AEFIs showed a statistically significant consistent causal association with COVID-19 vaccination (Table 3) No serious AEFIs were reported under clusters from the COVID-19 vaccinations.
Table 3.
Association between clinical characteristics and the causality of severe & serious AEFI of COVID-19 vaccination (N = 945).
| Variables | Consistent Causal Association (367) |
Inconsistent causal association (Coincidental) (578) |
p value | Adjusted p valuea | ||
|---|---|---|---|---|---|---|
| n | % | n | % | |||
| Sex | ||||||
| Male | 112 | 25.8 | 322 | 74.2 | <0.001 | 0.044 |
| Female | 255 | 49.9 | 256 | 50.1 | ||
| Age | ||||||
| 15–44 years | 254 | 67.7 | 121 | 32.3 | <0.001 | Ref |
| 45–59 years | 85 | 36.3 | 149 | 63.7 | <0.001 | |
| ≥60 years | 28 | 8.3 | 308 | 91.7 | <0.001 | |
| COVID-19 vaccine | ||||||
| Covishield | 325 | 38.6 | 517 | 61.4 | 0.669 | – |
| Covaxin | 42 | 40.8 | 61 | 59.2 | ||
| Type of AEFI | ||||||
| Death | 9 | 2.8 | 313 | 97.2 | <0.001 | <0.001 |
| Severe/Hospitalised & Recovered | 358 | 57.5 | 265 | 42.5 | ||
| Thrombo- embolic events | 0 | 0 | 180 | 100 | <0.001b | 0.994 |
Adjusted for sex, age groups, type of AEFI and the thromboembolic events.
Fishers exact test.
Thromboembolic events were reported among 209 (18.8%) of the analyzed participants. Among the ones with thromboembolic events, acute coronary syndrome (96,45.9%) followed by cerebrovascular accidents (CVA) (77, 36.8%) were reported to be the most common ones. These were followed by myocardial infarction (54, 25.8%) (Table 4).
Table 4.
Distribution of thromboembolic event among the serious AEFI cases of COVID-19 vaccination.
| TE Event | Frequency N = 209 |
Proportion (18.8%) |
|---|---|---|
| Acute coronary Syndrome | 96 | 45.9 |
| Myocardial Infarction | 54 | 25.8 |
| CVA | 77 | 36.8 |
Thromboembolic events were reported among 189 (19.1%) of the COVISHIELD beneficiaries, but it was not significantly different from the Covaxin beneficiaries, who reported 20 (16.7%) thromboembolic events (Table 1). The majority of the TE events were reported among males, which was found to be statistically significant in unadjusted (p < 0.001) as well as adjusted analysis (p < 0.001). Older age groups (45–59 years and ≥60 years) were having a significantly higher proportion of TE than the young ones (p < 0.05). The case fatality rate (CFR) was also higher among the vaccinees with TE events 132 (32.9) when compared with other diagnoses (p < 0.001). The statistical significance of the higher age (≥45 years) and the case fatality remained the same in the adjusted analysis (Table 5). Two cases of thrombocytopenia were reported among the COVISHIELD vaccinees, and one case was reported in COVAXIN vaccinees. However, none of them was found to have a causal link with the respective vaccines.
Table 5.
Association between the COVID-19 vaccinee characteristics and thromboembolic events.
| Variables |
Thromboembolic events |
p value |
Adjustedap value |
|||
|---|---|---|---|---|---|---|
|
Yes |
No |
|||||
| n | % | n | % | |||
| Sex | ||||||
| Male | 139 | 26.3 | 389 | 73.7 | <0.001 | 0.001 |
| Female | 70 | 12 | 514 | 88 | ||
| Age | ||||||
| 15–44 years | 24 | 5.3 | 425 | 94.7 | <0.001 | Ref |
| 45–59 years | 60 | 20.9 | 227 | 79.1 | <0.001 | |
| ≥60 years | 125 | 33.2 | 251 | 66.8 | 0.017 | |
| Type of AEFI | ||||||
| Death | 132 | 32.9 | 269 | 67.1 | <0.001 | <0.001 |
| Severe/Hospitalised & Recovered | 77 | 10.8 | 634 | 89.2 | ||
Adjusted for sex, age and type of AEFI.
4. Discussion
Reports indicate that 1.51 billion doses of COVID-19 vaccines were administered in India till 08.01.2022,9 the latest date for which the causality assessment report is available in the public domain from the country. As of 30th November 2021, 1.23 billion vaccine doses had been administered with AEFIs amounting to 4/100,000 doses. Among these AEFIs, 1965 cases were reported to be serious AEFIs, translating to 1.6/million doses administered.6 This is lower than the ones reported from the clinical trials of the vaccines administered in India,10 which might be due to differential surveillance followed in the trial mode (active surveillance) and post-marketing surveillance (passive surveillance). However, the COVID-19 vaccine AEFI rate in India was much lesser than the AEFI rates reported in other countries such as Canada (48/100000 doses) United Kingdom (300–700/100000 doses) and Brazil (777/100000 doses).11,12 The causality assessment of serious AEFIs has not been up to speed. Causality assessment report has been published for only 1112 out of 1965 serious AEFIs. The COVID-19 vaccine-related deaths reported in India were 94613 . The present analysis included 401 deaths. The recorded fatal events are low compared to the European Medical Agency which reported 938 fatal AEFIs from 58.4 million doses of AstraZeneca (European counterpart of COVISHIELD).14 VAERS from the USA reported 12,313 deaths among the COVID-19 vaccinees between 14th December 2020 and 19th July 2021.14 These findings signify the necessity and huge scope to improve the AEFI surveillance for COVID-19 vaccines in India. The duration taken for assessing the causality and approval of the report is also long, to the range of a maximum of 310 days among the cases analyzed in our study. Delays in despatching the medical records and post-mortem analysis by the states' relatively smaller size of the causality assessment committee in comparison to the load of vaccines administered may be some of the potential reasons for the delay.11 This longer duration in disseminating the causality assessment needs further study to identify the bottlenecks and chokepoints responsible for such a prolonged duration.
The present analysis reported 43 serious anaphylaxis reactions from India, while 461 serious and non-serious anaphylaxis or anaphylactoid reactions have been reported from the United Kingdom (UK).15 All 43 serious anaphylactic reactions were assessed to be vaccine product-related and found to have a consistent causal association with the vaccination.
Overall, COVID-19 vaccine AEFIs,14 including serious AEFIs,12 were reported to be more common in females than males, which is echoed in our analysis. A significantly higher proportion of the younger age group (15–44 years) was found to have a consistent causal association with vaccination than their counterparts. Fatalities reported were significantly lower among the consistent causal association group than the coincidental group, in line with the findings from other countries.14 Pre-existing diseases could have been the potential reason for their deaths.14
All the thromboembolic events analyzed in our study, for which consistency could be evaluated, were found to have an inconsistent causal association with the COVID-19 vaccine. In India, thromboembolic event incidence has been reported to be 0.61 cases/million doses,6 which is very low when compared with the rate of similar events reported in other countries. The UK reported a rate of 13.6 per million first or unknown doses and 1.3 per million-second doses administered16 while 10 cases per million doses were reported in Germany.6 Esba et al reported that 4 out of 5 (80%) serious AEFIs were thrombotic events post-vaccination in Saudi Arabia.17 The European Medical Association (EMA) reviewed 25 thromboembolic events among the Astrazeneca vaccine (Covishield), but found no causal linkage 18 . This is similar to our findings in the current analysis from India.
Proportionately, more males reported TE events than females in our analysis, whereas the review of the Eudravigilance database reported that most TE events happened among females.(8) Regarding age, relatively older vaccinees (≥45 years) were reported with TE events from India, with a median age of 63 years, while the median age was 47 years from Europe.(8) In their comparative incidence of TE events between the hormonal contraceptives and COVID-19 vaccinees, Esba et al reported 68 events among the younger, females vaccinees in the USA19 Our study reported that the most common TE event was acute coronary syndrome (43), followed by CVA (33). An analysis of the Vigibase database till 24th January 2021 from across the world reported 20 serious acute coronary syndrome events, including four myocardial infarctions.3 Vaccine-induced thrombotic thrombocytopenia syndrome (VITT) has been a concern and associated with the COVISHIELD administration.20 An analysis of the national cohort from England revealed an increased risk of thrombosis and thrombocytopenia in AstraZeneca vaccinees.21 The pathophysiology for such an event has been hypothesized to be similar to that of heparin-induced thrombocytopenia. Antigen mediated as well as constituents of vaccines like adjuvants have also been hypothesized as potential factors for the VITT from earlier studies.21 Though two cases of thrombocytopenia were reported in the current analysis, they were not found to have a consistent causal association with COVISHIELD. Gordon et al reported 17 cases of immune thrombocytopenia (ITP) following the AstraZeneca vaccine, which was higher than the expected rate, yet they did not assess the event's causality.22
A significantly higher proportion of deaths occurred among the vaccinees who had a thromboembolic event in our study compared to the severe/hospitalized & recovered cases. Nevertheless, no significant association was found with COVISHIELD administration and with the consistency of causal association. This is in line with the previous literature that found no causal linkage between the Astrazeneca vaccine and TE events.4 The incidence of cerebral venous thrombosis (CVT) and portal vein thrombosis (PVT) among the COVID-19 infected persons from the USA was reported to be significantly higher (42.8 per million doses) than the background rate and the ones reported among the mRNA vaccinees23 Eudravigilance data from Europe till 1st May 2021 reported 48 cerebral venous sinus thrombosis (CVST), 517 deep vein thrombosis and 866 pulmonary embolisms, with the COVISHIELD counterpart, yet the reported rates were not higher than the expected background rates.24 Autopsy plays an important role in establishing the association between the VITT in the COVID-19 vaccine program.20 The proportion of fatalities for which an autopsy was done could not be found in the data from India. Hence, it can be recommended to conduct autopsies for all the fatalities among the serious COVID-19 AEFIs in the furture.
Relating to the quality of immunization services, 0.4% of the serious AEFIs were classified as immunization error related. A study from Brazil attributed 1.11% of the AEFIs (non-serious) to immunization error related causes.12 Regarding the quality of the AEFI investigation, unclassifiable events among the serious AEFIs in the data analyzed in our study have been lower than those reported for the previously published non-COVID-19 vaccine analysis of causality assessment reports from India.25 However, there is a temporal as well as a methodological difference in the assessment between the two data.
The present study assessed the cause determination of the AEFIs in a correct perspective with the help of scientifically founded causality assessment reports to summarize the possible reasons for a severe adverse reaction. However, the findings must be cautiously interpreted. The present study is a record-based analysis of 1112 cases. The available demographic variables were limited, with no laboratory parameters. Underreporting the AEFIs is a significant issue in India, which is another limitation.
All the serious AEFIs reported among the COVID-19 vaccinees are investigated by the National AEFI committee in India. Deaths reported under serious AEFIs were found to have a relatively lower consistent causal relationship with the COVID-19 vaccines than the recovered hospitalizations in India. No consistent causal association was found between the TE events and the type of COVID-19 vaccine administered in India. TE events were associated with the age group 45–59 and ≥ 60 years among the AEFIs. The rate of overall AEFIs and serious/fatal AEFIs reporting is low, and the time taken for publishing the causality assessment is longer. The AEFI causality assessment for all the serious AEFIs must be completed at the earliest, and the causality assessment findings need to be published simultaneously. Timely dissemination of the causality assessment reports will help in building vaccine confidence among the public by alleviating the apprehensions and rumours regarding the COVID-19 vaccine. Further studies must be conducted by analyzing the laboratory parameters and clinical course of the serious AEFIs and autopsy findings of fatal AEFIs, to monitor the known AEs and identify the other, underlying safety signals.
Financial disclosure
Authors have no financial interests related to the material in the manuscript.
Funding
None.
Conflict of interest
None.
Author contributions
Aravind P. Gandhi conceptualized, curated data, analysed, interpreted data, drafted the manuscript and is guarantor. U Venkatesh conceptualized, curated data, interpreted data, critically reviewed the manuscript for important intellectual content and is guarantor. Naveen Murali conceptualized, curated data, interpreted data, critically reviewed the manuscript for important intellectual content and is guarantor.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributor Information
Aravind P. Gandhi, Email: aravindsocialdoc@gmail.com.
U. Venkatesh, Email: venkatesh2007mbbs@gmail.com.
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