京津冀气象条件对学龄前儿童流感的影响及预报方法研究

基于2014—2016年京津冀地区学龄前儿童流感发病人数和气象观测数据，研究了学龄前儿童流感发病与单个气象要素以及综合气象条件的关系，结果表明:该地区学龄前儿童流感发病人数与一周以内的气温、相对湿度、气压和综合气象条件指标—大气环境人体感知度（BPWI）存在显著线性相关。大气环境人体感知度与学龄前儿童流感具有更稳定的暴露-反应关系:当BPWI≤?11或0≤BPWI<10 时，随着BPWI减小，流感发病风险增大。气压是另一个显著影响流感发病的气象要素:当本站气压>905 hPa，随着气压的升高，流感发病人数增多；当本站气压达到1007 hPa时，流感发病风险达到峰值。在厘清暴露-反应关系的基础上，采用机器学习方法进行预报建模，发现超前3天的BPWI对流感发病人数贡献最大。通过历史回报检验，得到了较好的学龄前儿童流感发病回报效果，为流感的分类人群干预提供了预报依据和科学参考。 

The influence of meteorological conditions on influenza among preschool children over Beijing-Tianjin-Hebei area and prediction methods

Based on the number of influenza cases amongst preschool children and meteorological observations over Beijing-Tianjin-Hebei area from 2014 to 2016, the relationships between the incidence of preschool children influenza and individual meteorological factor as well as their combined conditions are investigated. The results indicate significant linear correlations between the number of influenza infection amongst preschool children and temperature, relative humidity, atmospheric pressure and a defined comprehensive indicator Body Perception Weather Index (BPWI). The exposure-consequence relationship based on the BPWI is more stable, i.e., while the BPWI values equal or smaller than ?11 or within the range of 0—10 correspond to higher risk of influenza. Local atmospheric pressure is another key factor. When the station pressure is higher than 905 hPa, higher pressure causes more infection, and the infection peak corresponds to 1007 hPa. On the basis of these understanding, a machine learning method is used to perform prediction experiment, and it is found that the BPWI with a 3 d lead time contributes the most to influenza incidence. The hindcast evaluation reports a fairly good performance of the prediction model, and this provides valuable evidences and scientific clues for pre-intervention.