Spatio-Temporal Pattern and Risk Factor Analysis of Hand, Foot and Mouth Disease Associated with Under-Five Morbidity in the Beijing–Tianjin–Hebei Region of China

Abstract

Hand, foot and mouth disease (HFMD) in children under the age of five is a major public health issue in China. Beijing–Tianjin–Hebei is the largest urban agglomeration in northern China. The present study aimed to analyze the epidemiological features of HFMD, reveal spatial clusters, and detect risk factors in this region. Reports of HFMD cases in Beijing–Tianjin–Hebei from 1 January 2013 to 31 December 2013 were collected from 211 counties or municipal districts. First, the epidemiological features were explored, and then SaTScan analysis was carried out to detect spatial clusters of HFMD. Finally, GeoDetector and spatial paneled model were used to identify potential risk factors among the socioeconomic and meteorological variables. There were a total of 90,527 HFMD cases in the year 2013. The highest rate was in individuals aged one year, with an incidence of 24.76/103. Boys (55,168) outnumbered girls (35,359). Temporally, the incidence rose rapidly from April, peaking in June (4.08/103). Temperature, relative humidity and wind speed were positively associated with the incidence rate, while precipitation and sunshine hours had a negative association. The explanatory powers of these factors were 57%, 13%, 2%, 21% and 12%, respectively. Spatially, the highest-risk regions were located in Beijing and neighboring areas, with a relative risk (RR) value of 3.04. The proportion of primary industry was negatively associated with HFMD transmission, with an explanatory power of 32%. Gross domestic product (GDP) per capita, proportion of tertiary industry, and population density were positively associated with disease incidence, with explanatory powers of 22%, 17% and 15%, respectively. These findings may be helpful in the risk assessment of HFMD transmission and for implementing effective interventions to reduce the burden of this disease.

Spatiotemporal risk mapping of hand, foot and mouth disease and its association with meteorological variables in children under 5 years

“…The results revealed that high-risk area were mainly in large cities, such as Beijing, Tianjin, Shijiazhuang and their neighbouring areas. This finding was consistent with that reported in previous studies [3,19,35]. Deng et al found that cluster centres of HFMD were almost the same in the capital of Guangdong province in China as in neighbouring areas [19].…”

“…Liu found that a cluster centre in Shandong province in China varied in different years [35]. Xu found that high-risk areas were mainly located in regions with a high level of economic development and population density [3].…”

“…Research also reported that relative humidity had a significant influence on HFMD transmission, showing that high relative humidity resulted in a greater risk of HFMD infection [13,[15][16][17][18][19][20]. In addition to air temperature and relative humidity, other meteorological factors, such as air pressure, wind speed and sunshine hours, also appeared to influence HFMD transmission [3,17]. Although the previous studies detected a link between the risk of HFMD and meteorological factors, the association between these factors differed, depending on the region.…”

Spatio-Temporal Variations of Satellite-Based PM2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China

“…According to the literature, GDM can not only quantitatively determine the relative importance of each driving factor both in spatial and temporal variation, but also address the joint effects of these factors on the spatio-temporal variation of PM 2.5 concentrations. Therefore, GDM has attracted wide attention of the application from various fields with proven advantages [24][25][26].…”

Transmission center and driving factors of hand, foot, and mouth disease in China: A combined analysis

“…However, it is difficult to interpret the transmission pattern of HFMD owing to the presence of nonstationarity and nonlinearity in incidence data. Several factors, including climatic and socio-economic factors, are found to influence the pattern of HFMD, which reflects complex interactions among these factors [13][14][15][16][17]. As a result, incidence data of HFMD show strong seasonality, oscillations, and changes in period over time.…”