du Prel Jean-Baptist, Puppe Wolfram, Gröndahl Britta, Knuf Markus, Weigl Josef A I, Schaaff Franziska, Schmitt Heinz-Josef
Kinderklinik, Paediatrische Infektiologie & Zentrum Praeventive Paediatrie, Universitaetsmedizin, Johannes-Gutenberg-Universitaet, Mainz, Germany.
Clin Infect Dis. 2009 Sep 15;49(6):861-8. doi: 10.1086/605435.
Information on the onset of epidemics of acute respiratory tract infections (ARIs) is useful in timing preventive strategies (eg, the passive immunization of high-risk infants against respiratory syncytial virus [RSV]). Aiming at better predictions of the seasonal activity of ARI pathogens, we investigated the influence of climate on hospitalizations for ARIs.
Samples obtained from 3044 children hospitalized with ARIs in Mainz, Germany, were tested for pathogens with a multiplex reverse-transcriptase polymerase chain reaction enzyme-linked immunosorbent assay from 2001 through 2006. Hospitalizations for ARIs were correlated with meteorological parameters recorded at the University of Mainz. The frequency of hospitalization for RSV infection was predicted on the basis of multiple time series analysis.
Influenza A, RSV, and adenovirus were correlated with temperature and rhinovirus to relative humidity. In a time series model that included seasonal and climatic conditions, RSV-associated hospitalizations were predictable.
Seasonality of certain ARI pathogens can be explained by meteorological influences. The model presented herein is a first step toward predicting annual RSV epidemics using weather forecast data.
急性呼吸道感染(ARI)疫情的发病信息有助于确定预防策略的时机(例如,对高危婴儿进行呼吸道合胞病毒[RSV]被动免疫)。为了更好地预测ARI病原体的季节性活动,我们研究了气候对ARI住院情况的影响。
对2001年至2006年期间在德国美因茨因ARI住院的3044名儿童的样本,采用多重逆转录酶聚合酶链反应酶联免疫吸附试验检测病原体。ARI住院情况与美因茨大学记录的气象参数相关。基于多重时间序列分析预测RSV感染的住院频率。
甲型流感病毒、RSV和腺病毒与温度相关,鼻病毒与相对湿度相关。在一个包括季节和气候条件的时间序列模型中,RSV相关的住院情况是可预测的。
某些ARI病原体的季节性可由气象影响来解释。本文提出的模型是利用天气预报数据预测年度RSV疫情的第一步。