Modelling the impact of vaccination on COVID-19 in African countries.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
PLoS Computational Biology Pub Date : 2024-10-23 eCollection Date: 2024-10-01 DOI:10.1371/journal.pcbi.1012456
Dephney Mathebula, Abigail Amankwah, Kossi Amouzouvi, Kétévi Adiklè Assamagan, Somiealo Azote, Jesutofunmi Ayo Fajemisin, Jean Baptiste Fankam Fankame, Aluwani Guga, Moses Kamwela, Mulape Mutule Kanduza, Toivo Samuel Mabote, Francisco Fenias Macucule, Azwinndini Muronga, Ann Njeri, Michael Olusegun Oluwole, Cláudio Moisés Paulo
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Abstract

The rapid development of vaccines to combat the spread of COVID-19, caused by the SARS-CoV-2 virus, is a great scientific achievement. Before the development of the COVID-19 vaccines, most studies capitalized on the available data that did not include pharmaceutical measures. Such studies focused on the impact of non-pharmaceutical measures such as social distancing, sanitation, use of face masks, and lockdowns to study the spread of COVID-19. In this study, we used the SIDARTHE-V model, an extension of the SIDARTHE model, which includes vaccination rollouts. We studied the impact of vaccination on the severity of the virus, specifically focusing on death rates, in African countries. The SIRDATHE-V model parameters were extracted by simultaneously fitting the COVID-19 cumulative data of deaths, recoveries, active cases, and full vaccinations reported by the governments of Ghana, Kenya, Mozambique, Nigeria, South Africa, Togo, and Zambia. Using South Africa as a case study, our analysis showed that the cumulative death rates declined drastically with the increased extent of vaccination drives. Whilst the infection rates sometimes increased with the arrival of new coronavirus variants, the death rates did not increase as they did before vaccination.

模拟非洲国家接种疫苗对 COVID-19 的影响。
迅速研制出疫苗来抗击由 SARS-CoV-2 病毒引起的 COVID-19 的传播是一项伟大的科学成就。在开发 COVID-19 疫苗之前,大多数研究利用的是不包括药物措施的现有数据。这些研究侧重于非药物措施的影响,如社会隔离、卫生、使用口罩和封锁,以研究 COVID-19 的传播。在本研究中,我们使用了 SIDARTHE-V 模型,它是 SIDARTHE 模型的扩展,其中包括疫苗接种的推广。我们研究了接种疫苗对非洲国家病毒严重程度的影响,特别是对死亡率的影响。SIRDATHE-V 模型参数是通过同时拟合加纳、肯尼亚、莫桑比克、尼日利亚、南非、多哥和赞比亚政府报告的 COVID-19 死亡、康复、活动病例和全面接种疫苗的累积数据提取的。以南非为例,我们的分析表明,随着疫苗接种范围的扩大,累计死亡率急剧下降。虽然感染率有时会随着冠状病毒新变种的出现而上升,但死亡率并没有像接种疫苗前那样上升。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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