西非年龄结构和疫苗重点对COVID-19的影响

IF 3 Q2 INFECTIOUS DISEASES
H. B. Taboe, M. Asare-Baah, Afsana Yesmin, C. Ngonghala
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引用次数: 7

摘要

自2019年出现以来,持续的COVID-19大流行一直是一项重大的全球卫生挑战。早期的预测认为,由于撒哈拉以南非洲地区易患其他传染病、医疗体系薄弱和社会经济条件恶劣,该地区将承担不成比例的COVID-19负担,但与此相反,与其他地区相比,此次大流行对该地区的影响非常轻微。有趣的是,尽管非药物干预措施(npi)实施松散,疫苗的可得性和管理也很低,但SSA的病例、住院和疾病导致的死亡人数仍然很低。造成这种低负担的可能原因包括流行病学差异、报告不足(由于检测有限)、气候因素、人口结构和政府政策举措。在这项研究中,我们制定了一个模型框架,包括一个基本模型(其中只有易感个体接种疫苗),一个疫苗结构模型和一个混合疫苗年龄结构模型,以评估西非(WA)的COVID-19动态。的框架是训练有素的部分确认日常COVID-19例16个西非国家的数据,验证了剩下的部分数据,并用于(i)评估年龄结构的影响在佤邦COVID-19的发病率,(ii)评价疫苗和疫苗优先级的影响基于年龄方括号在次区域COVID-19的负担,和(3)探索合理的理由COVID-19低负担的佤邦与世界其他地方相比。模型参数的校准和全球敏感性分析表明,无症状青年是西澳大流行的主要驱动因素。此外,混合疫苗年龄结构模型的基本繁殖数和对照繁殖数均小于其他两种模型,表明未考虑年龄结构的模型高估了疾病负担。这一结果也通过疫苗衍生的群体免疫阈值得到证实。特别是,对基本(疫苗结构)模型的综合分析表明,如果84%(73%)的西非民众充分接种了批准在西澳大利亚州使用的疫苗,就可以实现疫苗衍生的群体免疫。混合模型的群体免疫阈值较低(68%)。此外,如果优先考虑效力较高的疫苗(如辉瑞或Moderna疫苗),则所有三个阈值都较低(基本模型为60%,疫苗结构模型为51%,混合模型为48%),如果优先考虑效力较低的疫苗,则所有三个阈值都较高。模型模拟表明,在西澳控制COVID-19大流行(通过减少传播)需要采取积极主动的方法,包括优先为更多的年轻人接种疫苗或同时为更多的年轻人和老年人接种疫苗。此外,与疫苗接种相辅相成的是更高水平的口罩遵守情况,这将改善遏制大流行的前景。此外,该模型的模拟预测,到2022年7月中旬,将出现另一波COVID-19波(与欧米克隆波相比,峰值大小更小)。此外,出现传染性更强的变体或放松有效减少传播的现有措施,将在未来导致更具破坏性的COVID-19浪潮。综上所述,考虑年龄结构对于理解为什么西澳州的COVID-19负担较低和维持目前的疫苗接种水平非常重要,并辅之以世卫组织推荐的npii,这对于遏制该疾病在西澳州的传播至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of age structure and vaccine prioritization on COVID-19 in West Africa
The ongoing COVID-19 pandemic has been a major global health challenge since its emergence in 2019. Contrary to early predictions that sub-Saharan Africa (SSA) would bear a disproportionate share of the burden of COVID-19 due to the region's vulnerability to other infectious diseases, weak healthcare systems, and socioeconomic conditions, the pandemic's effects in SSA have been very mild in comparison to other regions. Interestingly, the number of cases, hospitalizations, and disease-induced deaths in SSA remain low, despite the loose implementation of non-pharmaceutical interventions (NPIs) and the low availability and administration of vaccines. Possible explanations for this low burden include epidemiological disparities, under-reporting (due to limited testing), climatic factors, population structure, and government policy initiatives. In this study, we formulate a model framework consisting of a basic model (in which only susceptible individuals are vaccinated), a vaccine-structured model, and a hybrid vaccine-age-structured model to assess the dynamics of COVID-19 in West Africa (WA). The framework is trained with a portion of the confirmed daily COVID-19 case data for 16 West African countries, validated with the remaining portion of the data, and used to (i) assess the effect of age structure on the incidence of COVID-19 in WA, (ii) evaluate the impact of vaccination and vaccine prioritization based on age brackets on the burden of COVID-19 in the sub-region, and (iii) explore plausible reasons for the low burden of COVID-19 in WA compared to other parts of the world. Calibration of the model parameters and global sensitivity analysis show that asymptomatic youths are the primary drivers of the pandemic in WA. Also, the basic and control reproduction numbers of the hybrid vaccine-age-structured model are smaller than those of the other two models indicating that the disease burden is overestimated in the models which do not account for age-structure. This result is also confirmed through the vaccine-derived herd immunity thresholds. In particular, a comprehensive analysis of the basic (vaccine-structured) model reveals that if 84%(73%) of the West African populace is fully immunized with the vaccines authorized for use in WA, vaccine-derived herd immunity can be achieved. This herd immunity threshold is lower (68%) for the hybrid model. Also, all three thresholds are lower (60% for the basic model, 51% for the vaccine-structured model, and 48% for the hybrid model) if vaccines of higher efficacies (e.g., the Pfizer or Moderna vaccine) are prioritized, and higher if vaccines of lower efficacy are prioritized. Simulations of the models show that controlling the COVID-19 pandemic in WA (by reducing transmission) requires a proactive approach, including prioritizing vaccination of more youths or vaccination of more youths and elderly simultaneously. Moreover, complementing vaccination with a higher level of mask compliance will improve the prospects of containing the pandemic. Additionally, simulations of the model predict another COVID-19 wave (with a smaller peak size compared to the Omicron wave) by mid-July 2022. Furthermore, the emergence of a more transmissible variant or easing the existing measures that are effective in reducing transmission will result in more devastating COVID-19 waves in the future. To conclude, accounting for age-structure is important in understanding why the burden of COVID-19 has been low in WA and sustaining the current vaccination level, complemented with the WHO recommended NPIs is critical in curbing the spread of the disease in WA.
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