Regional clustering and waves patterns due to COVID-19 by the index virus and the lambda/gamma, and delta/omicron SARS-CoV-2 variants in Peru.

Gates Open Research Pub Date : 2023-11-20 eCollection Date: 2022-01-01 DOI:10.12688/gatesopenres.13644.2
Melissa Toyama, Lucía Vargas, Sofía Ticliahuanca, Antonio M Quispe
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引用次数: 0

Abstract

Background: Coronavirus disease 2019 (COVID-19) impact varies substantially due to various factors, so it is critical to characterize its main differences to inform decision-makers about where to focus their interventions and differentiate mitigation strategies. Up to this date, little is known about the patterns and regional clustering of COVID-19 waves worldwide.

Methods: We assessed the patterns and regional clustering of COVID-19 waves in Peru by using the weekly mortality rates for each of the 25 regions as an outcome of interest. We obtained the death counts from the National Informatics System of Deaths and population estimates from the National Registry of Identification and Civil Status. In addition, we characterized each wave according to its duration, peak, and mortality rates by age group and gender. Additionally, we used polynomial regression models to compare them graphically and performed a cluster analysis to identify regional patterns.

Results: We estimated the average mortality rate at the first, second, and third waves at 13.01, 14.12, and 9.82 per 100,000 inhabitants, respectively, with higher mortality rates among elders and men. The patterns of each wave varied substantially in terms of duration, peak, impact, and wave shapes. Based on our clustering analysis, during the first wave caused by the index virus, the 25 regions of Peru presented six different wave patterns. However, the regions were clustered in two different wave patterns during the second and third, caused by alpha/lambda/delta and omicron.

Conclusions: The propagation of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) variants behaved in Peru with varying wave patterns and regional clustering. During the COVID-19 pandemic, the weekly mortality rates followed different spatiotemporal patterns with solid clustering, which might help project the impact of future waves of COVID-19.

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秘鲁由指数病毒以及SARS-CoV-2的λ / γ和δ /omicron变体引起的COVID-19的区域聚集和波动模式。
背景:2019冠状病毒病(COVID-19)的影响因各种因素而有很大差异,因此,确定其主要差异,以便告知决策者应将干预措施的重点放在何处,并区分缓解战略,这一点至关重要。迄今为止,对全球COVID-19波的模式和区域聚集性知之甚少。方法:我们使用25个地区的每周死亡率作为研究结果,评估了秘鲁COVID-19波的模式和区域聚集性。我们从国家死亡信息系统获得死亡人数,从国家身份和公民身份登记处获得人口估计。此外,我们根据其持续时间、峰值和按年龄组和性别划分的死亡率来描述每个波的特征。此外,我们使用多项式回归模型对它们进行图形比较,并进行聚类分析以确定区域模式。结果:我们估计第一波、第二波和第三波的平均死亡率分别为13.01、14.12和9.82 / 10万居民,老年人和男性的死亡率更高。每种波浪的模式在持续时间、峰值、冲击和波浪形状方面有很大的不同。根据我们的聚类分析,在由指数病毒引起的第一波期间,秘鲁25个地区出现了六种不同的波型。然而,在第二波和第三波中,这些区域聚集在两种不同的波模式中,这是由α / λ / δ和omicron引起的。结论:严重急性呼吸综合征冠状病毒2型(SARS-COV-2)变异在秘鲁的传播表现出不同的波型和区域聚集性。在新冠肺炎大流行期间,周死亡率具有不同的时空模式,具有坚实的聚类性,这可能有助于预测未来新冠肺炎疫情的影响。
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来源期刊
Gates Open Research
Gates Open Research Immunology and Microbiology-Immunology and Microbiology (miscellaneous)
CiteScore
3.60
自引率
0.00%
发文量
90
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