揭示大流行模式:对哥伦比亚波哥大四波COVID-19传播和严重程度参数的详细分析。

David Santiago Quevedo, Nicolás T Domínguez, Diego Fernando Perez, Maria Alejandra Cabrera Polanía, Juan David Serrano Medina, Felipe Segundo Abril-Bermúdez, Diane Moyano Romero, Diana Sofia Rios Oliveros, Manuel Alfredo González Mayorga, Charles Whittaker, Zulma M Cucunubá
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引用次数: 0

摘要

背景:尽管来自高收入国家的数据丰富,但关于在拉丁美洲不同人口稠密地区观察到的独特流行病学模式的信息有限。本报告回顾性分析了在哥伦比亚波哥大爆发的四波COVID-19疫情,详细评估了177万例病例。方法:采用综合的统计方法。通过估计瞬时繁殖数R (t)来评估传播动态,而使用多项逻辑回归模型来估计变异特异性传播优势。通过一系列指标评估疾病严重程度:住院病例比(HCR)、重症监护病房病例比(ICU- cr)、病死率(CFR)、住院病死率(HFR)和ICU病死率(ICU- fr)。此外,我们分析了住院、ICU入院和死亡率按年龄组和波浪的分布。我们采用贝叶斯分层模型来捕获流行病学延迟,如发病至死亡、住院和ICU入院时间,以估计住院和ICU住院时间。结果:我们的发现揭示了R (t)的实质性变化,在祖先波和欧米克隆波期间峰值超过2.5。在大流行期间,我们观察到CFR降低了78%,这强调了临床严重程度的变化。与Mu变异相关的第三次浪潮记录了最高的病例数和死亡数,同时CFR下降,HFR升高,受影响最严重的年龄组向年轻人群转移。相比之下,由欧米克隆变体驱动的第四波表现出最高的繁殖数量和最低的总体严重性。这一浪潮的特点是儿科住院人数显著增加。研究显示,住院和ICU的平均时间在四波中持续下降,住院时间从10.84天减少到7.85天,ICU时间从16.2天下降到12.4天。结论:本研究揭示了波哥大四波COVID-19期间不同年龄组的传播和严重程度指标(包括死亡率、住院率、ICU率和住院时间)发生的重大变化。这些见解强调了回顾性分析对于了解大流行的各种影响并为不同城市环境中的公共卫生战略提供信息的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unveiling pandemic patterns: a detailed analysis of transmission and severity parameters across four COVID-19 waves in Bogotá, Colombia.

Background: Despite a wealth of data from high-income countries, there is limited information on the distinct epidemiological patterns observed in diverse, densely populated regions within Latin America. This retrospective analysis of COVID-19's four major waves in Bogotá, Colombia, evaluates 1.77 million cases in detail.

Methods: A comprehensive suite of statistical methods was employed. Transmission dynamics were assessed by estimating the instantaneous reproduction number R ( t ) , while variant-specific transmission advantages were estimated using multinomial logistic regression models. Disease severity was assessed through a suite of indicators: Hospitalisation Case Ratio (HCR), intensive care unit case ratio (ICU-CR), case fatality ratio (CFR), hospitalisation fatality ratio (HFR), and ICU fatality ratio (ICU-FR). Additionally, we analysed the distribution of hospitalisations, ICU admissions, and fatalities by age group and wave. We employed a Bayesian hierarchical model to capture epidemiological delays-such as onset-to-death, hospitalisation, and ICU admission durations to estimate hospital and ICU stay durations.

Results: Our findings reveal substantial variation in R ( t ) , with peaks exceeding 2.5 during the ancestral and Omicron waves. Over the course of the pandemic, we observed a 78% reduction in CFR, underscoring shifts in clinical severity. The third wave, associated with the Mu variant, recorded the highest case and death counts, alongside a decreased CFR, an elevated HFR, and a shift in the most affected age group towards younger populations. In contrast, the fourth wave, driven by the Omicron variant, exhibited the highest reproduction number and the lowest overall severity. This wave was characterised by a significant increase in pediatric hospitalisations. The study reveals a continued decline in the mean durations of hospital and ICU stays across the four waves, with hospital stays decreasing from 10.84 to 7.85 days and ICU stays dropping from 16.2 to 12.4 days.

Conclusions: This study reveals significant shifts in transmission and severity metrics-including mortality, hospitalisation, and ICU rates and stays-across age groups during Bogotá's four COVID-19 waves. These insights underscore the value of retrospective analyses to understand the pandemic's varied impact and inform public health strategies in diverse urban settings.

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