Non-linear relationships and interactions of meteorological factors on mumps in Jinan, China
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ORIGINAL PAPER
Non-linear relationships and interactions of meteorological factors on mumps in Jinan, China Shaoqian Lin 1 & Shiman Ruan 1 & Xingyi Geng 1 & Kaijun Song 1 & Liangliang Cui 1 & Xiaoxue Liu 1 & Yingjian Zhang 1 & Meng Cao 1 & Ying Zhang 2 Received: 22 February 2020 / Revised: 2 October 2020 / Accepted: 3 November 2020 # ISB 2020
Abstract Although vaccination is available, mumps remains a public health concern in many countries including China. Previous studies have indicated the impact of meteorological factors and mumps, but findings vary across different regions with limited evidence to inform local public health responses. We aim to examine the impacts of meteorological variables on mumps in Jinan, a temperate city of China, and explore the interactions of temperature with humidity or wind speed. Weekly meteorological data and notified cases of mumps in Jinan were collected for 2014–2018. Regression analyses using the generalized additive model were performed with considerations of multicollinearity, lag effects, school holidays, long-term trend, and seasonality. A stratification model was applied to investigate the interaction. We found a non-linear relationship between weekly mean temperature and the number of cases. Between 1.2 and 24.5 °C, the excess risk (ER) of mumps for a 1 °C increase in weekly mean temperature was 3.08% (95% CI 1.32 to 4.87%) at 0-week lag. The lagged effects could last for 3 weeks. There were interactions between mean temperature and relative humidity or wind speed. The effect of mean temperature was enhanced in days with low relative humidity or high wind speed. This study suggests that temperature is positively associated with mumps cases with thresholds in the temperate city of China, and the effect can be modified by relative humidity and wind speed and is independent of vaccine coverage. Findings could be integrated into current early warning systems of mumps in order to protect people’s health from the risk of changing climate. Keywords Meteorological factors . Mumps . Generalized additive model . Time series analysis
Introduction Mumps is an acute respiratory infectious disease caused by mumps virus belonging to the Paramyxovirus family, which is characterized by unilateral or bilateral swollen and painful parotid gland with precursory fever (Tyor and Harrison 2014). It is generally a mild and self-limiting disease, most often affecting children between 5 and 9 years old. However, the disease can cause serious complications, such as orchitis, oophoritis, meningitis, encephalitis, pancreatitis, and deafness (Yung et al. 2011). The epidemiological evidence reveals that
* Ying Zhang [email protected] 1
Jinan Municipal Center for Disease Control and Prevention, 2 Weiliu Road, Huaiyin District, Jinan 250021, China
2
School of Public Health, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2006, Australia
mumps is still an important public health problem in many countries (Deeks et al. 2011; Fiebelkorn et al. 2013). There were a total
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