Effectiveness of COVID-19 Vaccines against Delta Variant (B.1.617.2): A Meta-Analysis
Article
Mahumud, Rashidul Alam, Ali, Mohammad Afshar, Kundu, Satyajit, Rahman, Md Ashfikur, Kamara, Joseph Kihika and Renzaho, Andre M. N.. 2022. "Effectiveness of COVID-19 Vaccines against Delta Variant (B.1.617.2): A Meta-Analysis
." Vaccines. 10 (2), pp. 1-12. https://doi.org/10.3390/vaccines10020277
| Article Title | Effectiveness of COVID-19 Vaccines against Delta Variant (B.1.617.2): A Meta-Analysis |
|---|---|
| ERA Journal ID | 214428 |
| Article Category | Article |
| Authors | Mahumud, Rashidul Alam, Ali, Mohammad Afshar, Kundu, Satyajit, Rahman, Md Ashfikur, Kamara, Joseph Kihika and Renzaho, Andre M. N. |
| Journal Title | Vaccines |
| Journal Citation | 10 (2), pp. 1-12 |
| Article Number | 277 |
| Number of Pages | 12 |
| Year | 2022 |
| Publisher | MDPI AG |
| Place of Publication | Switzerland |
| ISSN | 2076-393X |
| Digital Object Identifier (DOI) | https://doi.org/10.3390/vaccines10020277 |
| Web Address (URL) | https://www.mdpi.com/2076-393X/10/2/277 |
| Abstract | Objectives: The highly transmissible COVID-19 Delta variant (DV) has contributed to a surge in cases and exacerbated the worldwide public health crisis. Several COVID-19 vaccines play a significant role in a high degree of protection against the DV. The primary purpose of this meta-analysis is to estimate the pooled effectiveness of the COVID-19 vaccines against the DV in terms of risk ratio (RR) among fully vaccinated, compared to unvaccinated populations. Methods: We carried out a systematic review, with meta-analysis of original studies focused on COVID-19 vaccines effectiveness against a DV clinical perspective among fully COVID-19 vaccinated populations, compared to placebo (unvaccinated populations), published between 1 May 2021 and 30 September 2021. Eleven studies containing the data of 17.2 million participants were identified and included in our study. Pooled estimates of COVID-19 vaccines effectiveness (i.e., risk ratio, RR) against the DV with 95% confidence intervals were assessed using random-effect models. Publication bias was assessed using Egger’s regression test and funnel plot to investigate potential sources of heterogeneity and identify any differences in study design. Results: A total population of 17.2 million (17,200,341 people) were screened for the COVID-19 vaccines’ effectiveness against the DV. We found that 61.13% of the study population were fully vaccinated with two doses of COVID-19 vaccines. The weighted pooled incidence of COVID-19 infection was more than double (20.07%) among the unvaccinated population, compared to the fully vaccinated population (8.16%). Overall, the effectiveness of the COVID-19 vaccine against the DV was 85% (RR = 0.15, 95% CI: 0.07– 0.31). The effectiveness of COVID-19 vaccines varied slidably by study designs, 87% (RR = 0.13, 95% CI: 0.06–0.30) and 84% (RR = 0.16, 95% CI: 0.02, 1.64) for cohort and case-control studies, respectively. Conclusion: The effectiveness of COVID-19 vaccines were noted to offer higher protection against the DV among populations who received two vaccine doses compared with the unvaccinated population. This finding would help efforts to maximise vaccine coverage (i.e., at least 60% to 70% of the population), with two doses among vulnerable populations, in order to have herd immunity to break the chain of transmission and gain greater overall population protection more rapidly. |
| Keywords | B.1.617.2; COVID-19 vaccines; Delta variant; Herd immunity; Meta-analysis; Vaccines effectiveness |
| ANZSRC Field of Research 2020 | 4299. Other health sciences |
| Byline Affiliations | University of Sydney |
| School of Business | |
| University of Rajshahi, Bangladesh | |
| University of South Australia | |
| Jagannath University, Bangladesh | |
| Patuakhali Science and Technology University, Bangladesh | |
| Southeast University, China | |
| Khulna University, Bangladesh | |
| World Vision East Africa Regional Office, Kenya | |
| Deakin University | |
| Western Sydney University | |
| Burnet Institute, Australia |
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