...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Influenza and other respiratory viruses. >Applying the moving epidemic method to determine influenza epidemic and intensity thresholds using influenza‐like illness surveillance data 2009‐2018 in Tunisia
【24h】

Applying the moving epidemic method to determine influenza epidemic and intensity thresholds using influenza‐like illness surveillance data 2009‐2018 in Tunisia

机译：应用移动流行方法测定使用突尼斯植物流感样疾病监测数据的流感流行病和强度阈值

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Background Defining the start and assessing the intensity of influenza seasons are essential to ensure timely preventive and control measures and to contribute to the pandemic preparedness. The present study aimed to determine the epidemic and intensity thresholds of influenza season in Tunisia using the moving epidemic method. Methods We applied the moving epidemic method (MEM) using the R Language implementation (package “mem”). We have calculated the epidemic and the different intensity thresholds from historical data of the past nine influenza seasons (2009‐2010 to 2017‐2018) and assessed the impact of the 2009‐2010 pandemic year. Data used were the weekly influenza‐like illness (ILI) proportions compared with all outpatient acute consultations. The goodness of the model was assessed using a cross validation procedure. Results The average duration of influenza epidemic during a typical season was 20?weeks and ranged from 11?weeks (2009‐2010 season) to 23?weeks (2015‐2016 season). The epidemic threshold with the exclusion of the pandemic season was 6.25%. It had a very high sensitivity of 85% and a high specificity of 69%. The different levels of intensity were established as follows: low, if ILI proportion is below 9.74%, medium below 12.05%; high below 13.27%; and very high above this last rate. Conclusions This is the first mathematically based study of seasonal threshold of influenza in Tunisia. As in other studies in different countries, the model has shown both good specificity and sensitivity, which allows timely and accurate detection of the start of influenza seasons. The findings will contribute to the development of more efficient measures for influenza prevention and control.
机译：背景技术定义开始和评估流感季节的强度对于确保及时预防和控制措施并为大流行准备提供贡献。本研究旨在利用移动流行方法确定突尼斯流感季节的流行病和强度阈值。方法使用R语言实现（包“MEM”）应用移动流行病方法（MEM）。我们已经计算了过去九个流感季节的历史数据（2009-2010至2017-2018）的疫情和不同的强度阈值，并评估了2009 - 2010年大流行年度的影响。与所有门诊急性咨询相比，使用的数据是每周流感样疾病（ILI）比例。使用交叉验证程序评估模型的良好。结果典型季节流感流行病的平均持续时间为20？周，从11个星期（2009-2010季）到23个？周（2015-2016季）。排除大流行季节的疫情阈值为6.25％。它具有85％的敏感性85％，特异性为69％。建立不同程度的强度如下：低，如果Ili比例低于9.74％，培养基低于12.05％;高于13.27％;并且高于这个最后一次速度。结论这是突尼斯季节性流感季节性阈值的第一个基于数学上的研究。与其他国家的其他研究一样，该模型表明了良好的特异性和敏感性，这既允许及时准确地检测流感季节的开始。调查结果将有助于开发更有效的流感预防和控制措施。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号