Analysis of the effects of different temperature levels in Changsha on human adenovirus infection

LUO Piaoyi; KUANG Wentao; NI Han; FU Liuyi; LYU Yuan; ZHA Wenting; YI Shanghui; ZHANG Siyu

doi:10.16462/j.cnki.zhjbkz.2024.02.005

Volume 28 Issue 2

Feb. 2024

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Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2024 > 28(2): 152-160

LUO Piaoyi, KUANG Wentao, NI Han, FU Liuyi, LYU Yuan, ZHA Wenting, YI Shanghui, ZHANG Siyu. Analysis of the effects of different temperature levels in Changsha on human adenovirus infection[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(2): 152-160. doi: 10.16462/j.cnki.zhjbkz.2024.02.005

Citation:

LUO Piaoyi, KUANG Wentao, NI Han, FU Liuyi, LYU Yuan, ZHA Wenting, YI Shanghui, ZHANG Siyu. Analysis of the effects of different temperature levels in Changsha on human adenovirus infection[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(2): 152-160. doi: 10.16462/j.cnki.zhjbkz.2024.02.005

Citation:

LUO Piaoyi, KUANG Wentao, NI Han, FU Liuyi, LYU Yuan, ZHA Wenting, YI Shanghui, ZHANG Siyu. Analysis of the effects of different temperature levels in Changsha on human adenovirus infection[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(2): 152-160. doi: 10.16462/j.cnki.zhjbkz.2024.02.005

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Analysis of the effects of different temperature levels in Changsha on human adenovirus infection

doi: 10.16462/j.cnki.zhjbkz.2024.02.005

1.
Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha 410013, China
2.
Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China

Funds:

Major Project of Science and Technology Innovation of Hunan Province 2020SK1010

Natural Science Foundation of Hunan Province 2020JJ8007

Key Projects of Hunan Provincial Department of Education 21A0023

Changsha Natural Science Foundation kq2202254

More Information

Corresponding author: YI Shanghui, E-mail: 653489246@qq.com; ZHANG Siyu, E-mail: 359766279@qq.com
Received Date: 2023-04-26
Rev Recd Date: 2023-09-03

Available Online: 2024-03-30

Publish Date: 2024-02-10

Abstract

Abstract

Objective The objective of this study was to examine the impact and lag effects of varying temperature levels on human adenovirus (HAdV) infection. Methods We collected information on HAdV infection in 2020 and meteorological data for the same period from three sentinel hospitals in Changsha. Spearman rank correlation was employed to analyze the relationship between meteorological factors and the number of HAdV infection cases. Different temperature levels, including daily average, daily maximum, and daily minimum, were categorized using thresholds below P_2.5 and above P_97.5 to define extremely low and high temperatures. The distributed lag nonlinear model (DLNM) was utilized to investigate the impact and lag effect of different temperature levels on HAdV infection. Results In 2020, a total of 41 624 specimens were examined in Changsha, with 1 693 yielding positive results for HAdV, resulting in a prevalence rate of 4.07%. Of these cases, infants and children aged 0-4 years comprised 67.04%. Spearman rank correlation analysis indicated that weak associations (all P < 0.05) between HAdV infection and daily average temperature (r_s=-0.121), daily maximum temperature (r_s=-0.110), and daily minimum temperature (r_s=-0.119). The distributed lag nonlinear model (DLNM) showed that both three-dimensional plot (3-D plot) and contour plots revealed a noticeable short-term effect of high temperature on the risk of HAdV infection. Specifically, under extremely high temperature conditions, both daily average and daily minimum temperatures were found to exhibit a lagged impact on the risk of HAdV infection for a single day. Moreover, the cumulative effects of daily average and daily maximum temperatures displayed a gradual increase with longer lag periods. At a lag of 21 days, the relative risks rose to 15.79 (95% CI: 2.69-92.79) and 11.81 (95% CI: 2.26-61.68), respectively. Additionally, the cumulative effect of daily minimum temperature reached its peak at a lag of 4 days (RR=6.78, 95%CI: 1.05-43.83). Conclusions Infants and young children are particularly vulnerable to HAdV infection. The study findings reveal significant correlations between different temperature levels and the occurrence of HAdV infection. Moreover, the study highlights the significant immediate and cumulative lag effects of extreme temperatures on HAdV infection risk in Changsha.
- Temperature,
- Human adenovirus,
- Sentinel surveillance,
- Distribution lag nonlinear model

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References(27)

References

[1]	Li JY, Sun RH, Chen LD. Identifying sensitive population associated with summer extreme heat in Beijing [J]. Sustain Cities Soc, 2022, 83: 103925. DOI: 10.1016/j.scs.2022.103925.
[2]	Ding T, Li X, Gao H. An unprecedented high temperature event in Southern China in autumn 2021 and the essential role of the mid-latitude trough [J]. Adv Clim Change Res, 2022, 13(6): 772-777. DOI: 10.1016/j.accre.2022.11.002.
[3]	Ingole V, Sheridan SC, Juvekar S, et al. Mortality risk attributable to high and low ambient temperature in Pune city, India: a time series analysis from 2004 to 2012 [J]. Environ Res, 2022, 204: 112304. DOI: 10.1016/j.envres.2021.112304.
[4]	Li ZJ, Li YL, Wang XN, et al. Extreme temperature exposure and urolithiasis: a time series analysis in Ganzhou, China [J]. Front Public Health, 2022, 10: 1075428. DOI: 10.3389/fpubh.2022.1075428.
[5]	Shao M, Yu L, Xiao C, et al. Short-term effects of ambient temperature and pollutants on the mortality of respiratory diseases: a time-series analysis in Hefei, China [J]. Ecotoxicol Environ Saf, 2021, 215: 112160. DOI: 10.1016/j.ecoenv.2021.112160.
[6]	Liu Y, Guo Y, Wang CB, et al. Association between temperature change and outpatient visits for respiratory tract infections among children in Guangzhou, China [J]. Int J Environ Res Public Health, 2015, 12(1): 439-454. DOI: 10.3390/ijerph120100439.
[7]	周建丁, 马玉霞, 杨丝絮, 等. 最高气温对呼吸系统疾病急诊人次的影响研究[J]. 中国环境科学, 2019, 39(1): 372-378. DOI: 10.3969/j.issn.1000-6923.2019.01.044. Zhou JD, Ma YX, Yang SX, et al. A study on the impact of daily maximum temperature on the hospital emergency room visits due to respiratory diseases [J]. China Environ Sci, 2019, 39(1): 372-378. DOI: 10.3969/j.issn.1000-6923.2019.01.044.
[8]	Ko JH, Woo HT, Oh HS, et al. Ongoing outbreak of human adenovirus-associated acute respiratory illness in the Republic of Korea military, 2013 to 2018 [J]. Korean J Intern Med, 2021, 36(1): 205-213. DOI: 10.3904/kjim.2019.092.
[9]	饶华祥, 马永成, 姜双应, 等. 青海省急性呼吸道感染病原学分析[J]. 中国病原生物学杂志, 2014, 9(5): 430-433. DOI: 10.13350/j.cjpb.140511. Rao HX, Ma YC, Jiang SY, et al. Etiological analysis of acute respiratory tract infection in Qinghai Province [J]. J Pathog Biol, 2014, 9(5): 430-433. DOI: 10.13350/j.cjpb.140511.
[10]	路凤, 李亚伟, 李成橙, 等. 时间序列分析在空气污染与健康领域的应用及其R软件实现[J]. 中国卫生统计, 2018, 35(4): 622-625. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGWT201804041.htm Lu F, Li YW, Li CC, et al. Application of time series analysis in the field of air pollution and health and its R software implementation [J]. China Health Statistics, 2018, 35(4): 622-625. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGWT201804041.htm
[11]	Zhang C, Fu X, Zhang YY, et al. Epidemiological and time series analysis of haemorrhagic fever with renal syndrome from 2004 to 2017 in Shandong Province, China [J]. Sci Rep, 2019, 9: 14644. DOI: 10.1038/s41598-019-50878-7.
[12]	Gasparrini A, Armstrong B, Kenward MG. Distributed lag non-linear models [J]. Stat Med, 2010, 29(21): 2224-2234. DOI: 10.1002/sim.3940.
[13]	Zhu HS, Chen S, Wang MZ, et al. Analysis on association between incidence of hand foot and mouth disease and meteorological factors in Xiamen, 2013-2017 [J]. Chin J Epidemiol, 2019, 40(5): 531-536. DOI: 10.3760/cma.j.issn.0254-6450.2019.05.008.
[14]	中国疾病预防控制中心. 人腺病毒呼吸道感染预防控制技术指南(2019年版)(2019-12-13)[2023-02-01]. https://www.chinapneumonia.cn/uploadfile/images/edit/0830171753614.pdf.
[15]	沈秀莲, 郑尔达, 黄甜, 等. 基于分布滞后非线性模型探讨日均气温对曲靖市手足口病发病的影响[J]. 中华疾病控制杂志, 2020, 24(11): 1275-1281. DOI: 10.16462/j.cnki.zhjbkz.2020.11.007. Shen XL, Zheng ED, Huang T, et al. Effect of temperature on hand, foot and mouth disease incidence in Qujing: a distributed lag non-linear model analysis [J]. Chin J Dis Control Prev, 2020, 24(11): 1275-1281. DOI: 10.16462/j.cnki.zhjbkz.2020.11.007.
[16]	Barnadas C, Schmidt DJ, Fischer TK, et al. Molecular epidemiology of human adenovirus infections in Denmark, 2011-2016 [J]. J Clin Virol, 2018, 104: 16-22. DOI: 10.1016/j.jcv.2018.04.012.
[17]	Kurskaya O, Ryabichenko T, Leonova N, et al. Viral etiology of acute respiratory infections in hospitalized children in Novosibirsk City, Russia (2013-2017) [J]. PLoS One, 2018, 13(9): e0200117. DOI: 10.1371/journal.pone.0200117.
[18]	吴本权, 唐英春, 朱家馨, 等. 广州市区两幼儿园2~6岁健康儿童肺炎链球菌携带状况调查[J]. 中国当代儿科杂志, 2001(5): 529-531. DOI: 10.3969/j.issn.1008-8830.2001.05.013. Wu BQ, Tang YC, Zhu JX, et al. Carrier rate of Streptococcus pneumoniae in healthy children aged 2-6 in two kindergartens in Guangzhou city [J]. Chin J Contemp Pediatr, 2001, 3(5): 529-531. DOI: 10.3969/j.issn.1008-8830.2001.05.013.
[19]	Mäkinen TM, Juvonen R, Jokelainen J, et al. Cold temperature and low humidity are associated with increased occurrence of respiratory tract infections [J]. Respir Med, 2009, 103(3): 456-462. DOI: 10.1016/j.rmed.2008.09.011.
[20]	Pscheidt VM, Gregianini TS, Martins LG, et al. Epidemiology of human adenovirus associated with respiratory infection in southern Brazil [J]. Rev Med Virol, 2021, 31(4): e2189. DOI: 10.1002/rmv.2189.
[21]	骆善彩, 汪庆庆, 杨娟, 等. 基于分布滞后非线性模型评估气温对淮安市儿科呼吸系统疾病门诊量的影响[J]. 江苏预防医学, 2022, 33(1): 3-7. DOI: 10.13668/j.issn.1006-9070.2022.01.002. Luo SC, Wang QQ, Yang J, et al. A study of the average daily temperature and children′s hospital respiratory disease outpatient volume based on distributed lag no-linear model in Huai′an City [J]. Jiangsu J Prev Med, 2022, 33(1): 3-7. DOI: 10.13668/j.issn.1006-9070.2022.01.002.
[22]	李娟, 张志薇, 于庚康, 等. 气象要素对南京市呼吸系统疾病的影响研究[J]. 气象科学, 2017, 37(3): 409-415. DOI: 10.3969/2016jms.0050. Li J, Zhang ZW, Yu GK, et al. Impact of meteorological factors on respiratory diseases in Nanjing [J]. J Meteorol Sci, 2017, 37(3): 409-415. DOI: 10.3969/2016jms.0050.
[23]	马辛悦. 2005-2018年沈阳市区居民呼吸系统疾病死亡趋势及极端温度对死亡风险的时空规律分析[D]. 沈阳: 中国医科大学, 2022. Ma XY. Analysis on the death trend of respiratory diseases and the temporal and spatial law of extreme temperature on death risk in Shenyang urban residents from 2005 to 2018 [D]. Shenyang: China Medical University, 2022.
[24]	Lei C, Lou CT, Io K, et al. Viral etiology among children hospitalized for acute respiratory tract infections and its association with meteorological factors and air pollutants: a time-series study (2014-2017) in Macao [J]. BMC Infect Dis, 2022, 22(1): 588. DOI: 10.1186/s12879-022-07585-y.
[25]	Liu WQ, Liu WL, Zhuang GY, et al. The change in the relationship between temperature and respiratory diseases among children in Guangzhou, China [J]. Environ Sci Pollut Res, 2023, 30(19): 55816-55825. DOI: 10.1007/s11356-023-26374-x.
[26]	Ban J, Xu D, He MZ, et al. The effect of high temperature on cause-specific mortality: a multi-County analysis in China [J]. Environ Int, 2017, 106: 19-26. DOI: 10.1016/j.envint.2017.05.019.
[27]	Dastoorpoor M, Khodadadi N, Masoumi K, et al. Physiological equivalent temperature (PET) and non-accidental, cardiovascular and respiratory disease mortality in Ahvaz, Iran [J]. Environ Geochem Health, 2022, 44(8): 2767-2782. DOI: 10.1007/s10653-021-01063-1.