HUANG Yue,YANG Yang,MA Pan,et al.Relationship between Influenza Outbreak Epidemic and Atmospheric Particle Concentration in the Cold Season of Shenzhen[J].Journal of Chengdu University of Information Technology,2025,40(02):232-237.[doi:10.16836/j.cnki.jcuit.2025.02.015]
深圳市冷季流感暴发与大气颗粒物浓度关系探究
- Title:
- Relationship between Influenza Outbreak Epidemic and Atmospheric Particle Concentration in the Cold Season of Shenzhen
- 文章编号:
- 2096-1618(2025)02-0232-06
- Keywords:
- influenza outbreak epidemic; atmospheric particulate matter; exposure-response relationship; time-series model; cold season
- 分类号:
- P49
- 文献标志码:
- A
- 摘要:
- 为探究亚热带气候区冷季流感暴发风险与大气颗粒物浓度的关系,为相关疾病的防治提供科学依据,进一步丰富气象健康与交叉领域的研究,收集深圳市2013年5月至2015年12月流感暴发的疫情逐日监测数据,及同时段的常规气象观测数据与大气颗粒物浓度数据。在区分流感病毒亚型(甲流、乙流)的基础上,采用分布-滞后非线性模型DLNM,分析冷季流感暴发与两种粒径颗粒物PM10、PM2.5的关联性。结果显示:两种亚型的暴发均在冷季呈现高峰,与颗粒物在冷季的高浓度峰值基本对应; 但甲流、乙流疫情暴发的时间段不完全重合,并存在年际差异。DLNM 揭示,对于甲流而言,高浓度PM2.5存在较强的滞后性影响,滞后11 d时74.28 μg/m3(P90)的PM2.5浓度关联的相对危险度RR可达1.85(95%CI:1.01～3.36); 而PM10的即时效应更强,暴发当天高浓度(90.50 μg/m3,P75)关联的RR高达1.68(95%CI:1.04～2.71)。此外,大气颗粒物对乙流暴发仅存在一定的滞后效应(5～8 d),例如,滞后5 d浓度为56.58 μg/m3(P75)的PM2.5危险度为1.22(95%CI:0.90～1.64),而90.50 μg/m3(P75)的PM10危险度高达3.17(95%CI:1.73～5.78)。综上,大气颗粒物对流感暴发疫情的影响显著,提升空气质量可一定程度降低流感传播风险。
- Abstract:
- The current study explored the relationship between influenza outbreak risk and concentration of airborne particulate matter in the cold season of Shenzhen, a sub-tropical city in China, which could enrich the study in the interdisciplinary field of meteorology and health, and improve the efficiency of the influenza prevention. Our study collected the daily surveillance data of influenza outbreak in Shenzhen from May 2013 to December 2015, as well as the daily meteorological observation data and daily concentration of atmospheric particulates(PM10 and PM2.5). Based on differentiating two subtypes of influenza virus(influenza-A and influenza-B), we analyzed the association between influenza outbreaks and the two kinds of particulate matter in the cold season of Shenzhen. The Distributed-Lag Nonlinear Model(DLNM)was adopted. The results showed that, the peaks of influenza subtypes generally occurred simultaneously with the high concentrations of particulate matter in the cold season. However, the outbreaks of influenza-A and influenza-B epidemics did not coincide completely, some inter-annual differences existed as well. The DLNM revealed that high PM2.5 concentration had significant effects on influenza-A, e.g., the relative risk(RR)corresponding to a 74.28 μg/m3 of PM2.5(the 90th percentile)on lag 11 d was 1.85(95%CI:1.01-3.36). In contrast, the immediate effect of PM10 on influenza-A was stronger, with an RR of 1.68(95%CI:1.04-2.71)associated with a high concentration(90.50 μg/m3)on the day of the influenza outbreak. However, the immediate effect of particulate matters on influenza B was not significant, they only presented some short-term lag effects on lag 5-8 d. A more prominent impact of PM10 than PM2.5 was revealed. For example, concerning PM2.5, the RR was 1.22(95%CI:0.90-1.64)for a concentration of 56.58 μg/m3(the 75th percentile)on lag 5 d, whereas for PM10 the RR was up to 3.17(95%CI:1.73-5.78)(90.50 μg/m3,the 75th percentile). In summary, the ambient influence of atmospheric particulate matter on the influenza outbreak was significant in Shenzhen, China. Improving air quality could reduce influenza transmission risk to some extent.
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备注/Memo
收稿日期:2023-09-07
基金项目:国家自然科学基金资助项目(42205185); 中国气象局青年创新团队资助项目(CMA2024QN15)
通信作者:马盼.mapan@cuit.edu.cn