Risk effects of meteorological factors on human brucellosis in Jilin province, China, 2005-2019

Shanjun Huang; Hao Wang; Zhuo Li; Zhaohan Wang; Tian Ma; Ruifang Song; Menghan Lu; Xin Han; Yiting Zhang; Yingtong Wang; Qing Zhen; Tiejun Shui

doi:10.1016/j.heliyon.2024.e29611

Risk effects of meteorological factors on human brucellosis in Jilin province, China, 2005-2019

Heliyon. 2024 Apr 15;10(8):e29611. doi: 10.1016/j.heliyon.2024.e29611. eCollection 2024 Apr 30.

Authors

Shanjun Huang^{1

2}, Hao Wang¹, Zhuo Li¹, Zhaohan Wang¹, Tian Ma¹, Ruifang Song¹, Menghan Lu¹, Xin Han¹, Yiting Zhang¹, Yingtong Wang¹, Qing Zhen^{1

2}, Tiejun Shui³

Affiliations

¹ Department of Epidemiology and Biostatistics, Key Laboratory of Zoonosis, Ministry of Education, School of Public Health, Jilin University, Changchun, Jilin, PR China.
² State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Changchun, PR China.
³ Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, PR China.

Abstract

Background: The impact of climate on zoonotic infectious diseases (or can be referred to as climate-sensitive zoonotic diseases) is confirmed. Yet, research on the association between brucellosis and climate is limited. We aim to understand the impact of meteorological factors on the risk of brucellosis, especially in northeastern China.

Methods: Monthly incidence data for brucellosis from 2005 to 2019 in Jilin province was obtained from the China Information System for Disease Control and Prevention (CDC). Monthly meteorological data (average temperature (°C), wind velocity (m/s), relative humidity (%), sunshine hours (h), air pressure (hPa), and rainfall (mm)) in Jilin province, China, from 2005 to 2019 were collected from the China Meteorological Information Center (http://data.cma.cn/). The Spearman's correlation was used to choose among the several meteorological variables. A distributed lag non-linear model (DLNM) was used to estimate the lag and non-linearity effect of meteorological factors on the risk of brucellosis.

Results: A total of 24,921 cases of human brucellosis were reported in Jilin province from 2005 to 2019, with the peak epidemic period from April to June. Low temperature and low sunshine hours were protective factors for the brucellosis, where the minimum RR values were 0.50 (95 % CI = 0.31-0.82) for -13.7 °C with 1 month lag and 0.61 (95 % CI = 0.41-0.91) for 110.5h with 2 months lag, respectively. High temperature, high sunshine hours, and low wind velocity were risk factors for brucellosis. The maximum RR values were 2.91 (95 % CI = 1.43-5.92, lag = 1, 25.7 °C), 1.85 (95 % CI = 1.23-2.80, lag = 2, 332.6h), and 1.68 (95 % CI = 1.25-2.26, lag = 2, 1.4 m/s). The trends in the impact of extreme temperature and extreme sunshine hours on the transmission of brucellosis were generally consistent.

Conclusion: High temperature, high sunshine hours, and low wind velocity are more conducive to the transmission of brucellosis with an obvious lag effect. The results will deepen the understanding of the relationship between climate and brucellosis and provide a reference for formulating relevant public health policies.

Keywords: DLNM; Human brucellosis; Meteorological factor; Sunshine hours; Temperature; Wind velocity.