Short-term effects of meteorological factors on hand, foot and mouth disease among children in Shenzhen, China: Non-linearity, threshold and interaction

Zhang, Zhen; Xie, Xin; Chen, Xiliang; Li, Yuan; Lu, Yan; Mei, Shujiang; Liao, Yunjun; Lin, Hualiang

doi:10.1016/j.scitotenv.2015.09.027

Cited by 76 publications

(46 citation statements)

References 33 publications

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“…A similar association between relative humidity and the HFMD was observed in two other studies (Chen et al 2014;Li et al 2014). Additionally, the association between ecological factors and HFMD has a non-linear relationship, which was not analyzed in this study (Li et al 2015;Zhang et al 2016). In our data analysis, the association generally appeared to be linear.…”

Section: Discussionsupporting

confidence: 76%

Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China

et al. 2016

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The influence of socio-ecological factors on hand, foot and mouth disease (HFMD) were explored in this study using Bayesian spatial modeling and spatial patterns identified in dry regions of Gansu, China. Notified HFMD cases and socio-ecological data were obtained from the China Information System for Disease Control and Prevention, Gansu Yearbook and Gansu Meteorological Bureau. A Bayesian spatial conditional autoregressive model was used to quantify the effects of socio-ecological factors on the HFMD and explore spatial patterns, with the consideration of its socio-ecological effects. Our non-spatial model suggests temperature (relative risk (RR) 1.15, 95 % CI 1.01-1.31), GDP per capita (RR 1.19, 95 % CI 1.01-1.39) and population density (RR 1.98, 95 % CI 1.19-3.17) to have a significant effect on HFMD transmission. However, after controlling for spatial random effects, only temperature (RR 1.25, 95 % CI 1.04-1.53) showed significant association with HFMD. The spatial model demonstrates temperature to play a major role in the transmission of HFMD in dry regions. Estimated residual variation after taking into account the socio-ecological variables indicated that high incidences of HFMD were mainly clustered in the northwest of Gansu. And, spatial structure showed a unique distribution after taking account of socio-ecological effects.

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Section: Discussionsupporting

confidence: 76%

Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China

et al. 2016

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“…There have been many studies focused on the influence of various factors on HFMD [2,7,11,12,13,16,17,18,19,20,21,22,23,24], and a number of potential risk factors were analyzed in this study. Risk factors relating to socioeconomic variables were collected, including population density, gross domestic product (GDP) per capita of each county, and the proportion of primary/tertiary industry in the study area (Figure 2, Table S1).…”

Section: Methodsmentioning

confidence: 99%

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

2017

IJERPH

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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.

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“…The result indicated temperature rise led to the increase in the number of HFMD cases (Wei et al 2015). A mixed generalized additive model (Xu et al 2016), the distributed lag non-linear model (Zhang et al 2016), was employed to estimate the effects of meteorological factors on pediatric HFMD and the estimation results indicated that relative humidity and daily average temperature had non-linear delayed effects (Xiao et al 2017) on pediatric HFMD, but the effects were different between different regions.…”

Section: Introductionmentioning

confidence: 99%

Spatial-temporal mapping of hand, foot and mouth disease in relation to climate factors in Xinjiang, China from 2008 to 2016

Xie

Huang

Wang

et al. 2019

Preprint

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[Objectives]: The study mainly aims to depict the epidemiological characteristics of hand, foot and mouth disease (HFMD) in Xinjiang, China and evaluate the effects of meteorological factors (temperature & precipitation) on its dynamics through spatiotemporal analysis. This study provides substantial evidences for disease HFMD control and prevention. [Methods]: With the data from the national surveillance data of HFMD and meteorological parameters in the study area from 2008 to 2016, the correlation between meteorological factors and HFMD incidence was explored through kernel density analysis. Furthermore, the spatial autocorrelation of HFMD in each year was analyzed by the Spatial Autocorrelation (Global Moran's I) tool. [Results]: The relationship between monthly mean temperature (T) and HFMD cases fit best in the following logarithmic equation: y=4.8176ln(T)-19.773, (R2 = 0.5194). The relationship between monthly mean precipitation (P) and HFMD fit best in the following quadratic equation, y=-1E-06×P2+0.0108×P+5.9867, (R2 = 0.5319). HFMD was mainly distributed in northern Xinjiang. Global spatial autocorrelation analysis indicated the spatial dependency on the incidence of HFMD in 2008, 2010, 2012, 2014 and 2015. The spatial dependency is the negative spatial autocorrelation in 2009. The incidence of HFMD in Xinjiang presented a random distribution pattern in 2011 and 2016. [Conclusion]: Our findings show that meteorological (air temperature & precipitation) variables had important effects on HFMD occurrence and transmission. This study provides a basis for the early warning of HFMD.

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Short-term effects of meteorological factors on hand, foot and mouth disease among children in Shenzhen, China: Non-linearity, threshold and interaction

Cited by 76 publications

References 33 publications

Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China

Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China

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

Spatial-temporal mapping of hand, foot and mouth disease in relation to climate factors in Xinjiang, China from 2008 to 2016

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