Spatiotemporal characters and influence factors of hand, foot and mouth epidemic in Xinjiang, China

Abstract

Hand, foot and mouth (HFM) disease is a common childhood illness. The paper aims to capture the spatiotemporal characters, and investigate the influence factors of the HFM epidemic in 15 regions of Xinjiang province from 2008 to 2017, China. Descriptive statistical analysis shows that the children aged 0-5 years have a higher HFM incidence, mostly boys. The male-female ratio is 1.5:1. Through the scanning method, we obtain the first cluster high-risk areas. The cluster time is usually from May to August every year. A spatiotemporal model is proposed to analyze the impact of meteorological factors on HFM disease. Comparing with the spatial model, the model is more effective in terms of R2, AIC, deviation, and mean-square error. Among meteorological factors, the number of HFM cases generally increases with the intensity of rainfall. As the temperature increases, there are more HFM patients. Some regions are mostly influenced by wind speed. Further, another spatiotemporal model is introduced to investigate the relationship between HFM disease and socioeconomic factors. The results show that socioeconomic factors have significant influence on the disease. In most areas, the risk of HFM disease tends to rise with the increase of the gross domestic product, the ratios of urban population and tertiary industry. The incidence is closely related to the number of beds and population density in some regions. The higher the ratio of primary school, the lower the number of HFM cases. Based on the above analysis, it is the key measure to prevent and control the spread of the HFM epidemic in high-risk areas, and influence factors should not be ignored.

Epidemiological characteristics and spatiotemporal clustering analysis of hand-foot-and-mouth disease in Dali between 2013 and 2021

“…The onset season seen in 2020-2021 was different from that of previous years, consistent with the Japanese experience of HFMD [26]. HFMD incidence was concentrated in autumn and winter, perhaps due to COVID-19, and was related to population mobility, social economy and policy factors [27]. Therefore, limiting assembly of susceptible populations and implementing prevention and control policy measures may regulate the seasonal distribution of HFMD and reduce morbidity.…”

Analysis of A SARIMA-XGBoost Model for Hand, Foot and Mouth Disease in Xinjiang, China

“…• Based on the AIC and BIC criteria, we conduct multiple order combinations to determine the optimal parameters. To capture the nonlinear characteristics embedded in the residuals of the SARIMA(p, d, q) × (P, D, Q) s model in Table 3, the meteorological variables corresponding to each region are used as input variables for the XGBoost algorithm ( 8)- (10). In the training of the XGBoost algorithm, the parameters have a significant impact on the effectiveness of the training.…”

“…According to the transmission mechanism of infectious diseases, meteorological conditions may influence the incidence, the transmission range, and the susceptibility of the population to diseases [5][6][7] . Various studies have shown that meteorological factors such as temperature, rainfall, humidity, air pressure, light, and wind speed are tightly associated with HFMD [8][9][10][11] .…”

Spatiotemporal patterns and risk mapping of provincial hand, foot, and mouth disease in mainland China, 2014–2017

“…There have been numerous prior studies on the spatiotemporal pattern of HFMD (6)(7)(8)(9)(10)(11). Nevertheless, the majority of the related researches have been carried out in just one province or local region with a small spatial size, such as Shaanxi Province (12), Xinjian (6), Henan Province (13), or the Ili River Valley Region (14).…”

“…There have been numerous prior studies on the spatiotemporal pattern of HFMD (6)(7)(8)(9)(10)(11). Nevertheless, the majority of the related researches have been carried out in just one province or local region with a small spatial size, such as Shaanxi Province (12), Xinjian (6), Henan Province (13), or the Ili River Valley Region (14). Analysis of the spatial distribution and temporal trend of HFMD incidence nationwide helps to determine high-risk provinces and periods, thus identifying provinces where prevention and control efforts are most needed and maximizing and rationalizing the utilization of limited public health resources.…”