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

Xu, Chengdong

doi:10.3390/ijerph14040416

Cited by 34 publications

(45 citation statements)

References 34 publications

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“…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].…”

Section: Discussionsupporting

confidence: 92%

“…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].…”

Section: Discussionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Xiao

2017

Epidemiol. Infect.

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Hand, foot and mouth disease (HFMD) risk has become an increasing concern in the Beijing-Tianjin-Hebei region, which is the biggest urban agglomeration in north-eastern Asia. In the study, spatiotemporal epidemiological features of HFMD were analysed, and a Bayesian space-time hierarchy model was used to detect local spatial relative risk (RR) and to assess the effect of meteorological factors. From 2009 to 2013, there was an obvious seasonal pattern of HFMD risk. The highest risk period was in the summer, with an average monthly incidence of 4·17/103, whereas the index in wintertime was 0·16/103. Meteorological variables influenced temporal changes in HFMD. A 1 °C rise in air temperature was associated with an 11·5% increase in HFMD (corresponding RR 1·122). A 1% rise in relative humidity was related to a 9·51% increase in the number of HFMD cases (corresponding RR 1·100). A 1 hPa increment in air pressure was related to a 0·11% decrease in HFMD (corresponding RR 0·999). A 1 h increase in sunshine was associated with a 0·28% rise in HFMD cases (corresponding RR 1·003). A 1 m/s rise in wind speed was related to a 6·2% increase in HFMD (corresponding RR 1·064). High-risk areas were mainly large cities, such as Beijing, Tianjin, Shijiazhuang and their neighbouring areas. These findings can contribute to risk control and implementation of disease-prevention policies.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Xiao

2017

Epidemiol. Infect.

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“…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].…”

Section: Introductionmentioning

confidence: 99%

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

Wang

Samat

Abuduwaili

et al. 2020

IJERPH

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With the aggravation of air pollution in recent years, a great deal of research on haze episodes is mainly concentrated on the east-central China. However, fine particulate matter (PM2.5) pollution in northwest China has rarely been discussed. To fill this gap, based on the standard deviational ellipse analysis and spatial autocorrelation statistics method, we explored the spatio-temporal variation and aggregation characteristics of PM2.5 concentrations in Xinjiang from 2001 to 2016. The result showed that annual average PM2.5 concentration was high both in the north slope of Tianshan Mountain and the western Tarim Basin. Furthermore, PM2.5 concentrations on the northern slope of the Tianshan Mountain increased significantly, while showing an obviously decrease in the western Tarim Basin during the period of 2001–2016. Based on the result of the geographical detector method (GDM), population density was the most dominant factor of the spatial distribution of PM2.5 concentrations (q = 0.550), followed by road network density (q = 0.423) and GDP density (q = 0.413). During the study period (2001–2016), the driving force of population density on the distribution of PM2.5 concentrations showed a gradual downward trend. However, other determinants, like DEM (Digital elevation model), NSL (Nighttime stable light), LCT (Land cover type), and NDVI (Normalized Difference Vegetation Index), show significant increased trends. Therefore, further effort is required to reveal the role of landform and vegetation in the spatio-temporal variations of PM2.5 concentrations. Moreover, the local government should take effective measures to control urban sprawl while accelerating economic development.

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“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Xu²,

Pān

et al. 2020

PLoS Negl Trop Dis

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Hand, foot, and mouth disease (HFMD) has become a major public health issue in China. The disease incidence varies substantially over time and across space. To understand the heterogeneity of HFMD transmission, we compare the spatiotemporal dynamics of HFMD in Qinghai and Shanghai by conducting combined analysis of epidemiological, wavelet time series, and mathematical methods to county-level data from 2009 to 2016. We observe hierarchical epidemic waves in Qinghai, emanating from Huangzhong and in Shanghai from Fengxian. Besides population, we also find that the traveling waves are significantly associated with socioeconomic and geographical factors. The population mobility also varies between the two regions: long-distance movement in Qinghai and between-neighbor commuting in Shanghai. Our findings provide important evidence for characterizing the heterogeneity of HFMD transmission and for the design and implementation of interventions, such as deploying optimal vaccine and changing local driving factors in the transmission center, to prevent or limit disease spread in these areas.

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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

Cited by 34 publications

References 34 publications

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

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

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

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

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