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Global dynamic spatiotemporal pattern of seasonal influenza since 2009 influenza pandemic.

2009 年流感大流行以来季节性流感的全球动态时空格局。

  • 影响因子:3.0670
  • DOI:10.1186/s40249-019-0618-5
  • 作者列表:"Xu ZW","Li ZJ","Hu WB
  • 发表时间:2020-01-03
Abstract

BACKGROUND:Understanding the global spatiotemporal pattern of seasonal influenza is essential for influenza control and prevention. Available data on the updated global spatiotemporal pattern of seasonal influenza are scarce. This study aimed to assess the spatiotemporal pattern of seasonal influenza after the 2009 influenza pandemic. METHODS:Weekly influenza surveillance data in 86 countries from 2010 to 2017 were obtained from FluNet. First, the proportion of influenza A in total influenza viruses (PA) was calculated. Second, weekly numbers of influenza positive virus (A and B) were divided by the total number of samples processed to get weekly positive rates of influenza A (RWA) and influenza B (RWB). Third, the average positive rates of influenza A (RA) and influenza B (RB) for each country were calculated by averaging RWA, and RWB of 52 weeks. A Kruskal-Wallis test was conducted to examine if the year-to-year change in PA in all countries were significant, and a universal kriging method with linear semivariogram model was used to extrapolate RA and RB in all countries. RESULTS:PA ranged from 0.43 in Zambia to 0.98 in Belarus, and PA in countries with higher income was greater than those countries with lower income. The spatial patterns of high RB were the highest in sub-Saharan Africa, Asia-Pacific region and South America. RWA peaked in early weeks in temperate countries, and the peak of RWB occurred a bit later. There were some temperate countries with non-distinct influenza seasonality (e.g., Mauritius and Maldives) and some tropical/subtropical countries with distinct influenza seasonality (e.g., Chile and South Africa). CONCLUSIONS:Influenza seasonality is not predictable in some temperate countries, and it is distinct in Chile, Argentina and South Africa, implying that the optimal timing for influenza vaccination needs to be chosen with caution in these unpredictable countries.

摘要

背景: 了解季节性流感的全球时空格局对流感的控制和预防至关重要。关于季节性流感全球时空格局更新的现有数据很少。本研究旨在评估 2009 流感大流行后季节性流感的时空模式。 方法: 从fluenet获得了 2010 年至 2017 年 86 个国家的每周流感监测数据。首先,计算甲型流感在流感病毒总量 (PA) 中的比例。第二,每周流感阳性病毒 (A和B) 的数量除以处理的样本总数,以获得甲型流感 (RWA) 和乙型流感 (RWB) 的每周阳性率。第三,通过平均RWA和 52 周RWB计算每个国家的平均甲型流感 (RA) 和乙型流感 (RB) 阳性率。进行Kruskal-Wallis test,以检验所有国家PA的逐年变化是否显著,并采用线性半变异函数模型的通用kriging方法外推各国RA和RB。 结果: PA在赞比亚为 0.43,白俄罗斯为 0.98,收入较高的国家PA大于收入较低的国家。高RB的空间模式在撒哈拉以南非洲、亚太地区和南美洲最高。RWA在温带国家的早期几周内达到峰值,RWB的峰值发生较晚一点。有一些温带国家具有非明显的流感季节性 (e。g.,毛里求斯和马尔代夫) 和一些具有明显流感季节性的热带/亚热带国家 (e.g.,智利和南非)。 结论: 流感季节性在一些温带国家是不可预测的,在智利、阿根廷和南非是不同的,这意味着在这些不可预测的国家需要谨慎选择流感疫苗接种的最佳时机。

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呼吸道感染方向

呼吸道感染分为上呼吸道感染与下呼吸道感染。上呼吸道感染是指自鼻腔至喉部之间的急性炎症的总称,是最常见的感染性疾病。下呼吸道感染是最常见的感染性疾患,治疗时必须明确引起感染的病原体以选择有效的抗生素。

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