| BackgroundMumps, categorized as a notifiable infectious disease in China, is an acute respiratory infectious disease with painful swelling of the parotid caused by mumps virus popular on a global scale. Guangzhou has a typical subtropical climate with a distinct 4 seasons, in which summers are long, hot, and humid, winters are short, mild, and dry. Typhoon frequently influences Guangzhou. Appropriate climate, frequent tourism and trade all around the world, a large amount of floating population and lack awareness of vaccination cause the high incidence of mumps in Guangzhou. There have been resurgences and large-scale outbreaks of mumps in the world over the past decade. The scale and seasonality of mumps have regional differences. Moreover, the climate change caused by global warming might be influence the mumps incidence. Therefore, it is urgent and important to explore the relationship between the epidemiology of mumps and meteorological factors.Little literature with inconsistent conclusions was found on the relationship between meteorological factors and mumps. Most models used in the literature are not flexible enough, and the prediction accuracies are not high. In addition, few meteorological variables were used in the models and few research studied on the subtropical area. Meteorological factors have delayed effects. However, most studies used traditional and single models to explore the effects, such as generalized linear model (GLM) and generalized additive model (GAM), which only took into account the effect of meteorological factors at a specific time, without considering the distribution of lag. As a result, the bias of results could not be ignored. Therefore, it is necessary to explore the relationship between the epidemiology of mumps and meteorological factors systematically and comprehensively, and to provide scientific basis for the prevention and control of mumps.MethodsData collectionReports of mumps cases were derived from the National Information System for Disease Control and Prevention from 1 January 2005 to 31 December 2014. The daily meteorological data from 2005 to 2013, including the maximum, mean, minimum temperature, and relative humidity, atmospheric pressure, wind velocity, and sunshine hours, were obtained from the China Meteorological Administration.Data analysisDescriptive epidemiological analysis was conducted. Spearman’s correlation was used to examine the relevance between the daily weather conditions and the mumps incidence. Meteorological factors related to mumps incidence were included in the model. After controlling the seasonality and long-time trend, and the effects of week and holiday, a Poisson regression with quasi-Poisson function to combine a DLNM was constructed. We used the Akaike information criterion for quasi-Poisson(Q-AIC) to choose the best model and calculated the overall effects (the estimated effects of meteorological factors used their median value as the corresponding reference value after the whole lag days), extreme effects (the estimated effects of meteorological factors comparing the 1st to their own median and the 99th to their own median at different lag day) and cumulative extreme effects (the estimated effects of meteorological factors comparing the 1st to their own median and the 99th to their own median after the whole lag days). We evaluated the effects of mean temperature on the incidence of mumps (hot effect:the relative risk (RR) of the incidence of mumps by comparing the 99th to the 90th percentile of mean temperature; cold effect:the RR of the incidence of mumps by comparing the 1st to the 10th percentile of mean temperature) for the subpopulations of different sex and age groups (0-4 y, 5-9 y,10-14 y,15-29 y and 30-64 y). We calculated the excess cases and RRs of the mumps incidence during the case periods (extend 3 subsequent days following the tropical cyclone periods) vs. the reference periods (as a bidirectional near-term summer period of the dentical duration and with the dentical distribution of the days of the week) in 2005-2013.ResultsThe epidemiology of mumps There were 55,639 mumps cases reported in Guangzhou during 2005-2014 with the annual average incidence of 47.87/lakh. Obvious seasonality was observed, and the incidence peak happened in the periods of May to July (21773 cases, account for 39.13%). The mumps cases occurred in all 12 districts (county-level cities), especially Panyu district, with the incidence of 78.43/lakh (11,162 cases, account for 20.06%). The mumps cases reported in Nansha district were the least, with the incidence of 18.15/lakh (1,103 cases, account for 1.98%). There were 30,570 cases (56.99%) reported in the urban areas, with the incidence of 46.05/lakh, and 25,069 cases (43.01%) reported in the rural areas, with the incidence of 51.57/lakh, and the differences had statistical significance (X2=17798.24, P<0.01). Among 55,639 reported cases,35,431 were male and 20,208 were female, with the ratio of male to female of 1.75:1. The sex differences of incidence had statistical significance (x2=12637.31,P<0.01). The maximum, minimum, and median ages were 91 y,29 d,7 y, respectively. Up to 81.59% of the cases occurred in children aged 0-14 y, and the peak incidence occurred in children aged 3-9 y (32,538 cases, account for 58.48%).44.93% (25,000 cases) occurred in students,23.33% (12,982 cases) in preschool children, and 16.47% (9,162 case) in scattered children.The relationship between mumps cases and meteorological factorsGeneral situation The median of daily mumps cases was 14 in Guangzhou during 2005-2013. The median of daily maximum, mean and minimum temperature were 28.3℃,24.2℃, and 21.3℃, respectively. The median of the daily weather conditions were as follows:relative humidity,75%; sunshine hours,3.8 h; wind velocity,1.4 m/s; and atmospheric pressure,1007.5 hPa.Correlation analysis Based on Spearman’s correlation analysis, except for daily sunshine hours, the maximum temperature, mean temperature, minimum temperature, relative humidity, wind velocity, and atmospheric pressure were associated with the incidence of mumps (P<0.01).General relationship and the maximum RRs of meteorological factors The three-dimensional plots showed all the relationship curves between the meteorological variables and the incidence of mumps with various lag days were nonlinear, whereas the different variables had different characteristics. The risk was the highest when daily mean temperature was 34.2℃ at lag 10 d and the RR was 1.05 (95%CI,1.03-1.06); when relative humidity was 99% at lag 24 d, the RR was the highest as 1.04 (95%CI,1.02-1.07); when wind velocity was 9.1 m/s at lag 10 d, the RR was the highest as 1.06 (95%CI,1.00-1.12); and when atmospheric pressure was 1027.2 hPa at lag 7 d, the RR was the highest as 1.04 (95%CI,0.96-1.13).The overall effects When mean temperature was 34.2℃ after lag 30 d, the RR was the highest as 3.03 (95%CI,2.05-4.48); when relative humidity was 99% after lag 24 d, the RR was the highest as 1.26 (95%CI,0.95-1.67); the risk was the highest when wind velocity was 9.1 m/s after lag 21 d and the RR was 2.55 (95%CI, 1.01-6.44); the risk was the highest when atmospheric pressure was 987.4 hPa after lag 7 d and the RR was 1.01 (95%CI,0.86-1.18).The extreme effects The changes of the extreme effects of mean temperature and relative humidity along with lag days were more obvious than the changes of the extreme effects of wind velocity and atmospheric pressure. The RR (cold effect) increased with the increased lag days when mean temperature decreased from 13.1℃ to 7.4℃. The RR (hot effect) increased with the increased lag days when mean temperature increased from 29.9℃ to 31.9℃, with the maximum RR as 1.02 at lag 10 d. The RR (dry effect) was highest at lag 5 d when relative humidity decreased from 55% to 34%. The RR (wet effect) decreased before lag 12 d, and then increased, with the maximum RR as 1.02 at lag 24 d when relative humidity increased from 89% to 96%.The cumulative extreme effects For mean temperature, the cumulative extreme effects were 1.47 and 0.51 when mean temperature was 31.9℃ after lag 30 d and 7.4℃ after lag 30 d, respectively. For relative humidity, the cumulative extreme effect was 1.12 (no statistically significance) when relative humidity was 96% after lag 24 d. For wind velocity, the cumulative extreme effect was 0.76 when wind velocity was 0.5 m/s after lag 21 d. For atmospheric pressure, the cumulative extreme effect was 0.84 when atmospheric pressure was 1023.0 hPa after lag 7 d.The effects of mean temperature on mumps cases for the subpopulations The hot effect and cold effect were larger in females than in males, and the differences had statistical significance [RR 1.61> 1.40,0.53>0.49, and 1 was not included in RR(95%CI)]. In general, hot effects increased with age, whereas cold effects did not have the similar trend.The effects of typhoon on mumps cases There were excess cases between 2 periods of each year during 2005-2013. The highest number of excess cases was 129 in 2010, and the least was 5 in 2007. The RRs were higher than 1, and the RRs and statistical significance of the RR 95% CIs were 1.30 (1.08,1.62),1.47 (1.22,1.89), 1.63 (1.46,1.94),1.27 (1.09,1.52), and 1.23 (1.02,1.52) in 2006,2008,2010,2011, and 2012, respectively. In general, typhoons caused an increase in mumps cases.ConclusionsIn Guangzhou, the incidence peak of mumps happened in summer (the periods of May to July). The mumps incidence in rural areas was higher than urban areas. The mumps incidence was higher in male than in female. Students aged< 14 y was the high-risk groups of mumps. High temperature, high relative humidity, high wind velocity and low atmospheric pressure increased the mumps risk. Female was the susceptible of hot and cold effects. Hot effects increased with age. Typhoons might cause an higher increase in mumps cases. |
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