COVID-19 pandemic dynamics in India, the SARS-CoV-2 Delta variant and implications for vaccination

Author:

Yang Wan1ORCID,Shaman Jeffrey2

Affiliation:

1. Department of Epidemiology, Columbia University, New York, NY, USA

2. Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA

Abstract

The Delta variant is a major SARS-CoV-2 variant of concern first identified in India. To better understand COVID-19 pandemic dynamics and Delta, we use multiple datasets and model-inference to reconstruct COVID-19 pandemic dynamics in India during March 2020–June 2021. We further use the large discrepancy in one- and two-dose vaccination coverage in India (53% versus 23% by end of October 2021) to examine the impact of vaccination and whether prior non-Delta infection can boost vaccine effectiveness (VE). We estimate that Delta escaped immunity in 34.6% (95% CI: 0–64.2%) of individuals with prior wild-type infection and was 57.0% (95% CI: 37.9–75.6%) more infectious than wild-type SARS-CoV-2. Models assuming higher VE among non-Delta infection recoverees, particularly after the first dose, generated more accurate predictions than those assuming no such increases (best-performing VE setting: 90/95% versus 30/67% baseline for the first/second dose). Counterfactual modelling indicates that high vaccination coverage for first vaccine dose in India combined with the boosting of VE among recoverees averted around 60% of infections during July–mid-October 2021. These findings provide support to prioritizing first-dose vaccination in regions with high underlying infection rates, given continued vaccine shortages and new variant emergence.

Funder

National Science Foundation

Rapid Response Research Program

National Institute of Allergy and Infectious Diseases

Morris-Singer Foundation

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

Reference43 articles.

1. World Health Organization. 2021 Tracking SARS-CoV-2 variants. See https://www.who.int/en/activities/tracking-SARS-CoV-2-variants/.

2. Public Health England. 2021 SARS-CoV-2 variants of concern and variants under investigation in England. Technical briefing 14. See https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/991343/Variants_of_Concern_VOC_Technical_Briefing_14.pdf (accessed 16 June 2021).

3. National Collaborating Centre for Infectious Diseases. 2021 Updates on COVID-19 Variants of Concern. 26 April 2021. See https://nccid.ca/covid-19-variants/ (accessed 3 May 2021).

4. Centers for Disease Control and Prevention. 2021 SARS-CoV-2 Variant Classifications and Definitions. See https://www.cdc.gov/coronavirus/2019-ncov/variants/variant-info.html (accessed 17 June 2021).

5. Global Initiative on Sharing All Influenza Data (GISAID). 2021 Tracking of Variants.16 June 2021. See https://www.gisaid.org/hcov19-variants/ (accessed 16 June 2021).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3