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波哥大针对新冠病毒疫苗有效性的预测建模:涉及不同变体和计算优化效率的方法创新

Predictive modelling of the effectiveness of vaccines against COVID-19 in Bogotá: Methodological innovation involving different variants and computational optimisation efficiency.

作者信息

Espinosa Oscar, White Lisa, Bejarano Valeria, Aguas Ricardo, Rincón Duván, Mora Laura, Ramos Antonio, Sanabria Cristian, Rodríguez Jhonathan, Barrera Nicolás, Álvarez-Moreno Carlos, Cortés Jorge, Saavedra Carlos, Robayo Adriana, Gao Bo, Franco Oscar

机构信息

Economic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.

Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, D.C., Colombia.

出版信息

Heliyon. 2024 Oct 23;10(21):e39725. doi: 10.1016/j.heliyon.2024.e39725. eCollection 2024 Nov 15.

Abstract

The uncertainty associated with the future of viruses such as SARS-CoV-2 poses a challenge to public health officials because of its implications for welfare, economics and population health. In this document, we develop an age-stratified epidemiological-mathematical model to predict various health outcomes, considering the effectiveness of COVID-19 vaccines. The analytical model proposed and developed for this research is based on the approach constructed by the COVID-19 International Modelling Consortium. Following this approach, this paper innovates at the frontier of knowledge by including the various variants of SARS-CoV-2 in the Consortium model. Furthermore, for the first time in international literature, a complete compilation of the formal mathematical development of this entire quantitative model is presented. Our model accurately fits the observed historical data of new infections, cumulative mortality, symptomatic infections, hospitalisations, and Intensive Care Units admissions, capturing the waves of contagion that have occurred in Bogotá, Colombia. In turn, the prognosis obtained indicates a considerable decrease in the incidence and lethality caused by SARS-CoV-2 under current conditions, thus evidencing the effectiveness of vaccines against infection, hospitalisation, and death. This model enables the evaluation of different scenarios in response to changes in the dynamics of this infectious disease, providing information to policymakers for real-world evidence-based decision-making.

摘要

像严重急性呼吸综合征冠状病毒2(SARS-CoV-2)这样的病毒,其未来存在不确定性,这给公共卫生官员带来了挑战,因为它会对福利、经济和人口健康产生影响。在本文件中,我们构建了一个按年龄分层的流行病学数学模型,以预测各种健康结果,同时考虑了新冠病毒疾病(COVID-19)疫苗的有效性。本研究提出并开发的分析模型基于COVID-19国际建模联盟构建的方法。遵循这一方法,本文通过在联盟模型中纳入SARS-CoV-2的各种变体,在知识前沿进行了创新。此外,本文首次在国际文献中完整呈现了整个定量模型的形式化数学推导过程。我们的模型准确拟合了新感染病例、累积死亡率、有症状感染病例、住院病例以及重症监护病房收治病例的观察历史数据,捕捉到了哥伦比亚波哥大发生的疫情传播浪潮。相应地,所得到的预测结果表明,在当前条件下,SARS-CoV-2导致的发病率和致死率大幅下降,从而证明了疫苗在预防感染、住院和死亡方面的有效性。该模型能够评估针对这种传染病动态变化的不同情景,为政策制定者提供基于实际证据的决策信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edf7/11570482/74dee6c260b6/gr1.jpg

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