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Relationship of meteorological factors and human brucellosis in Hebei province, China

机译:中国河北省气象因素与人体布鲁氏的关系

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摘要

Background: Brucellosis has always been one of the major public health problems in China. Investigating the influencing factors of brucellosis is conducive to its prevention and control. The incidence trend of brucellosis shows an obvious seasonality, suggesting that there may be a correlation between brucellosis and meteorological factors, but related studies were few. We aimed to use the autoregressive integrated moving average (ARIMA) model to analyze the relationship between meteorological factors and brucellosis. Methods: The data of monthly incidence of brucellosis and meteorological factors in Hebei province from January 2004 to December 2015 were collected from the Chinese Public Health Science Data Center and Chinese meteorological data website. An ARIMA model incorporated with covariables was conducted to estimate the effects of meteorological variables on brucellosis. Results: There was a highest peak from May to July every year and an upward trend during the study period. Atmospheric pressure, wind speed, mean temperature, and relative humidity had significant effects on brucellosis. The ARIMA(1,0,0)(1,1,0)_(12) model with the covariates of atmospheric pressure, wind speed and mean temperature was the optimal model. The results showed that the atmospheric pressure with a 2-month lag (β = -0.004, p = 0.037), the wind speed with a 1-month lag (β = 0.030, p = 0.035), and the mean temperature with a 2-month lag (β = —0.003, p = 0.034) were significant predictors. Our study suggests that atmospheric pressure, wind speed, mean temperature, and relative humidity have a significant impact on brucellosis. Further understanding of its mechanism would help facilitate the monitoring and early warning of brucellosis.
机译:背景:布鲁克病一直是中国的主要公共卫生问题之一。调查水骨菌的影响因素有利于预防和控制。布鲁克病的发病趋势表明了明显的季节性,表明布鲁氏菌病和气象因素之间可能存在相关性,但相关的研究很少。我们旨在使用自回归综合移动平均(ARIMA)模型来分析气象因素和布鲁氏菌病之间的关系。方法:从2004年1月到2015年1月到2015年1月,从2004年1月到2015年12月,从2004年1月到2015年12月,从中国公共卫生科学数据中心和中国气象数据网站收集了河北省的月度发病率。进行了加入协变者的Arima模型,以估计气象变量对布鲁氏菌病的影响。结果:每年5月至7月,研究期间的趋势最高。大气压,风速,平均温度和相对湿度对布鲁氏菌病具有显着影响。 ARIMA(1,0,0)(1,1,0)_(12)模型具有大气压的协变量,风速和平均温度是最佳模型。结果表明,具有2个月滞后的大气压(β= -0.004,p = 0.037),风速,1个月滞后(β= 0.030,p = 0.035),平均温度为2 -MONTH滞后(β= -0.003,P = 0.034)是显着的预测因子。我们的研究表明,大气压,风速,平均温度和相对湿度对布鲁氏菌病产生重大影响。进一步了解其机制将有助于促进布鲁克枯的监测和预警。

著录项

  • 来源
    《The Science of the Total Environment》 |2020年第1期|135491.1-135491.8|共8页
  • 作者单位

    Department of Epidemiology and Biostatistics School of Public Health Anhui Medical University Hefei Anhui 230036 China;

    Department of Epidemiology and Biostatistics School of Public Health Anhui Medical University Hefei Anhui 230036 China;

    Department of Epidemiology and Biostatistics School of Public Health Anhui Medical University Hefei Anhui 230036 China;

    Department of Epidemiology and Biostatistics School of Public Health Anhui Medical University Hefei Anhui 230036 China;

    Division of Life Sciences and Medicine The First Affiliated Hospital of University of Science and Technology of China Hefei Anhui 230036 China;

    Department of Epidemiology and Biostatistics School of Public Health Anhui Medical University Hefei Anhui 230036 China;

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

    Brucellosis; ARIMA model; Meteorology factors; Time series analysis;

    机译:布鲁氏菌病;Arima模型;气象因素;时间序列分析;

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