Exploration of the association between meteorological factors and positive rate of norovirus infectious diarrhea based on the distributed lag non-linear model in Shanghai
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摘要:
目的 探讨上海市腹泻患者中诺如病毒感染与气象因素的关联,为诺如病毒感染性腹泻的防控提供科学依据。 方法 收集上海市2012―2019年腹泻病例与上海市各气象监测点逐日气象资料,利用分布滞后非线性模型(distributed lag non-linear model, DLNM)分析诺如病毒感染性腹泻的发病与气象因素的关联。 结果 在21 148名腹泻入院的就诊患者中,诺如病毒检出率为18.75%。其中45~<60岁人群的检出率最高(22.72%)。DLNM结果显示,相对于日平均气温18 ℃(P50),当日平均气温为-6 ℃时对诺如病毒感染的影响最大(RR=3.06, 95% CI: 1.49~6.30);日平均气温在滞后2 d时对诺如病毒感染产生最大影响(RR=1.15, 95% CI: 1.02~1.29)。相对于日降水量0 mm(P50),当日降水量195 mm时出现最大负效应(RR=0.31, 95% CI: 0.06~1.66)。 结论 上海市腹泻入院就诊患者的诺如病毒感染率较高,低温增加诺如病毒感染性腹泻发病风险,应根据诺如病毒流行特征针对性地开展防控工作。 Abstract:Objective To explore the association between norovirus among diarrheal patients and meteorological factors in Shanghai, and to provide a scientific basis for the prevention and control of norovirus infectious diarrhea. Methods We collected the data of diarrhea in Shanghai from 2012 to 2019 and the daily meteorological data of all meteorological monitoring points in Shanghai. A distributed lag non-linear model (DLNM) was constructed to analyze the relationship between norovirus infections diarrhea and meteorological factors. Results 18.75% of the 21 148 diarrheal patients were found norovirus. Age group of 45~ < 60 years old patients were found with the highest positive percentage (22.72%). Compared with the daily average temperature of 18 ℃ (P50), the daily average temperature of -6 ℃ had the greatest impact on norovirus infection (RR=3.06, 95% CI: 1.49-6.30); the average daily temperature lagging by 2 days has a maximum impact on norovirus infection (RR=1.15, 95% CI: 1.02-1.29). Compared with the daily precipitation of 0mm (P50), the highest negative effect was associated with daily precipitation of 195 mm (RR=0.31, 95% CI: 0.06-1.66). Conclusions The rate of norovirus infection in patients in Shanghai is high, and low temperature increases the risk of norovirus infectious diarrhea. Targeted prevention and control work should be carried out according to the characteristics of norovirus epidemic. -
Key words:
- Norovirus /
- Sentinel surveillance /
- Distributed lag non-linear model /
- Diarrhea
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图 2 (A) RR随日平均气温与滞后时间的变化趋势3D图(B)特定日平均气温不同滞后天数对诺如病毒感染的效应(C)诺如病毒感染与日平均气温的总体累积效应图
Figure 2. (A) 3D plot for variation trend of RR with average daily temperature and lag time (B) Lag-response association at specific daily average temperature of norovirus infection (C) Overall cumulative exposure-response association between norovirus infection and daily average temperature
图 3 (A) RR随日降水量与滞后时间的变化趋势3D图(B)特定日降水量不同滞后天数对诺如病毒感染的效应(C)诺如病毒感染与日降水量的总体累积效应图
Figure 3. (A) 3D plot for variation trend of relative risk with daily precipitation and lag time (B) Lag-response association at specific daily precipitation of norovirus infection (C) Overall cumulative exposure-response association between norovirus infection and daily precipitation
表 1 2012―2019年上海市诺如病毒感染性腹泻基本特征[n(%)]
Table 1. Characteristics of norovirus infectious diarrhea in Shanghai from 2012 to 2019 [n(%)]
病例数 诺如病毒检出率 P值 GI组检出率 P值 GII组检出率 P值 总计(例) 21 148(100.00) 3 966(18.75) 335(1.58) 3 500(16.55) 性别 0.03 0.14 0.11 男 11 211(53.01) 2 165(19.31) 191(1.70) 1 898(16.93) 女 9 937(46.99) 1 801(18.12) 144(1.45) 1 602(16.12) 年龄组(岁) <0.01 <0.01 <0.01 <1 2 049(9.69) 208(10.15) 5(0.24) 201(9.81) 1~<5 3 046(14.40) 480(15.76) 11(0.36) 464(15.23) 5~<18 1 240(5.86) 174(14.03) 12(0.97) 155(12.50) 18~<45 7 377(34.88) 1 591(21.57) 183(2.48) 1 332(18.06) 45~<60 3 424(16.19) 778(22.72) 62(1.81) 693(20.24) ≥60 4 012(18.97) 735(18.32) 62(1.55) 655(16.33) 季节 <0.01 <0.01 <0.01 春季 4 849(22.93) 1 061(21.88) 141(2.91) 846(17.45) 夏季 5 992(28.33) 507(8.46) 56(0.93) 440(7.34) 秋季 5 523(26.12) 1 282(23.21) 46(0.83) 1 227(22.22) 冬季 4 784(22.62) 1 116(23.33) 92(1.92) 987(20.63) -
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