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Effects and interaction of meteorological factors on influenza: Based on the surveillance data in Shaoyang, China

机译:气象因素对流感的影响和相互作用:基于邵阳市的监测数据

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摘要

Background: Previous studies have demonstrated that meteorological factors influence the incidence of influenza. However, little is known regarding the interactions of meteorological factors on the risk of influenza in China.Objective: The study aimed to evaluate the associations between meteorological factors and influenza in Shaoyang of southern China, and explore the interaction of temperature with humidity and rainfall.Methods: Weekly meteorological data and disease surveillance data of influenza in Shaoyang were collected from 2009 to 2012. According to the incubation period and infectious period of influenza virus, the maximum lag period was set as 3 weeks. A generalized additive model was conducted to evaluate the effect of meteorological factors on the weekly number of influenza cases and a stratification model was applied to investigate the interaction.Results: During the study period, the total number of influenza cases that were notified in the study area was 2506, with peak times occurring from December to March. After controlling for the confounders, each 5 degrees C decrease in minimum temperature was related to 8% (95%CI: 1-15%) increase in the number of influenza cases at a 1-week lag. There was an interaction between minimum temperature and relative humidity and the risk of influenza was higher in cold and less humid conditions than other conditions. The interaction between minimum temperature and rainfall was not statistically significant in our study.Conclusions: The study suggests that minimum temperature is inversely associated with influenza in the study area of China, and the effect can be modified by relative humidity. Meteorological variables could be integrated in current public health surveillance system to better prepare for the risks of influenza.
机译:背景:以前的研究表明,气象因素会影响流感的发病率。然而,关于中国气象因素与流感风险之间相互作用的研究鲜为人知。目的:本研究旨在评估中国南方邵阳市气象因素与流感之间的关系,并探讨温度与湿度和降雨之间的相互作用。方法:收集2009年至2012年邵阳市流感的每周气象数据和疾病监测数据。根据流感病毒的潜伏期和传染期,将最大滞后期定为3周。运用广义加性模型评估气象因素对每周流感病例数的影响,并采用分层模型调查相互作用。结果:在研究期间,研究中通知的流感病例总数地区为2506,高峰时间为12月至3月。在控制混杂因素之后,最低温度每降低5摄氏度,与1周时滞后的流感病例数增加8%(95%CI:1-15%)有关。最低温度和相对湿度之间存在相互作用,寒冷和潮湿条件下的流感风险高于其他条件。结论:最低温度与中国研究地区的流感呈负相关,且相对湿度可以改变这一影响。可以将气象变量整合到当前的公共卫生监视系统中,以更好地应对流感风险。

著录项

  • 来源
    《Environmental research》 |2019年第5期|326-332|共7页
  • 作者单位

    Shandong Univ, Sch Publ Hlth, Dept Epidemiol, 44 Wenhuaxi Rd, Jinan 250012, Shandong, Peoples R China;

    Shandong Univ, Sch Publ Hlth, Dept Epidemiol, 44 Wenhuaxi Rd, Jinan 250012, Shandong, Peoples R China;

    Univ Sydney, China Studies Ctr, Sch Publ Hlth, Sydney, NSW, Australia;

    Shandong Univ, Sch Publ Hlth, Dept Epidemiol, 44 Wenhuaxi Rd, Jinan 250012, Shandong, Peoples R China;

    Shandong Univ, Sch Publ Hlth, Dept Epidemiol, 44 Wenhuaxi Rd, Jinan 250012, Shandong, Peoples R China;

    Shandong Univ, Hosp 2, Dept Med Adm, 247 BeiYuan Rd, Jinan 250033, Shandong, Peoples R China;

    Shandong Univ, Sch Publ Hlth, Dept Epidemiol, 44 Wenhuaxi Rd, Jinan 250012, Shandong, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Influenza; Meteorological factors; Interaction; Generalized additive model; Stratification model;

    机译:流行性感冒;气象因素;相互作用;广义加性模型;分层模型;

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