scholarly journals The Association between Ambient Temperature and Childhood Hand, Foot and Mouth Disease in Chengdu, China: A Distributed Lag Non-linear Analysis

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Fei Yin ◽  
Tao Zhang ◽  
Lei Liu ◽  
Qiang Lv ◽  
Xiaosong Li
Keyword(s):  
Ambient Temperature ◽  
Foot And Mouth Disease ◽  
Linear Analysis ◽  
Mouth Disease ◽  
Distributed Lag ◽  
Non Linear ◽  
Foot And Mouth

scholarly journals Non-Linear Association between Exposure to Ambient Temperature and Children’s Hand-Foot-and-Mouth Disease in Beijing, China

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0126171 ◽  
Author(s):  
Meimei Xu ◽  
Weiwei Yu ◽  
Shilu Tong ◽  
Lei Jia ◽  
Fengchao Liang ◽  
...  
Keyword(s):  
Ambient Temperature ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Linear Association ◽  
Non Linear ◽  
Foot And Mouth ◽  
Beijing China

scholarly journals The association between diurnal temperature range and childhood hand, foot, and mouth disease: a distributed lag non-linear analysis

2017 ◽  
Vol 145 (15) ◽  
pp. 3264-3273 ◽  
Author(s):  
FEI YIN ◽  
YUE MA ◽  
XING ZHAO ◽  
QIANG LV ◽  
YAQIONG LIU ◽  
...  
Keyword(s):  
Diurnal Temperature Range ◽  
Foot And Mouth Disease ◽  
Sichuan Province ◽  
Mouth Disease ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Distributed Lag ◽  
Risk Estimates ◽  
Non Linear ◽  
Foot And Mouth

SUMMARYIn recent years, hand, foot, and mouth disease (HFMD) has been increasingly recognized as a critical challenge to disease control and prevention in China. Previous studies have found that meteorological factors such as mean temperature and relative humidity were associated with HFMD. However, little is known about whether the diurnal temperature range (DTR) has any impact on HFMD. This study aimed to quantify the impact of DTR on childhood HFMD in 18 cities in Sichuan Province. A distributed lag non-linear model was adopted to explore the temporal lagged association of daily temperature with age-, gender- and pathogen-specific HFMD. A total of 290 123 HFMD cases aged 0–14 years were reported in the 18 cities in Sichuan Province. The DTR–HFMD relationships were non-linear in all subgroups. Children aged 6–14 years and male children were more vulnerable to the temperature changes. Large DTR had the higher risk estimates of HFMD incidence in cases of EV71 infection, while small DTR had the higher risk estimates of HFMD incidence in cases of CV-A16 infection. Our study suggested that DTR played an important role in the transmission of HFMD with non-linear and delayed effects.

scholarly journals Influence of temperature and humidity on hand, foot, and mouth disease in Guangzhou, 2013–2017

2020 ◽  
Vol 48 (6) ◽  
pp. 030006052092989
Author(s):  
Chun Chen ◽  
Qinqin Jiang ◽  
Zhuangzhi Song ◽  
Yilan Li ◽  
Hui Wang ◽  
...  
Keyword(s):  
Seasonal Pattern ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Distributed Lag ◽  
Foot And Mouth ◽  
Temperature And Humidity ◽  
Low Humidity ◽  
Long Term Trends ◽  
Public Health Strategies

Objective To explore associations between temperature, humidity and hand, foot and mouth disease (HFMD) incidence in Guangzhou, China from 2013 to 2017. Methods A distributed lag non-linear model was applied to estimate the effects of daily temperature and humidity on HFMD incidence after adjusting for long-term trends, seasonal trends, and day of the week. Results In total, 353,431 confirmed HFMD cases were reported in Guangzhou over the study period. A bimodal seasonal pattern was observed. High temperatures had acute short-term effects on HFMD incidence that declined quickly over time. The effects of low humidity declined over lag periods, but increased when the humidity surpassed 60.5%. Temperature and humidity were both inversely associated with HFMD incidence during lag days 0 to 3 and with lag periods Conclusions Temperature and humidity play important roles in HFMD incidence. These data are important for developing public health strategies.

scholarly journals The effect of temperature on childhood hand, foot and mouth disease in Guangdong Province, China, 2010-2013: A multicity study

2019 ◽  
Author(s):  
Zece Xu ◽  
Wenqi Hu ◽  
Kedi Jiao ◽  
Ci Ren ◽  
Baofa Jiang ◽  
...  
Keyword(s):  
Local Governments ◽  
Meta Analysis ◽  
Foot And Mouth Disease ◽  
Public Health Problem ◽  
Guangdong Province ◽  
Mouth Disease ◽  
Effect Of Temperature ◽  
Non Linear ◽  
Foot And Mouth ◽  
The Relationship

Abstract Background Hand, foot and mouth disease (HFMD) is a serious infectious disease, which has become a public health problem. Previous studies have shown that temperature may influence the incidence of HFMD, but most only focus on single city and the results are highly heterogeneous. Therefore, a multicity study was conducted to explore the association between temperature and HFMD in different cities and search for modifiers that influence the heterogeneity. Methods We collected daily cases of childhood HFMD (aged 0-5 years) and meteorological factors of 21 cities in Guangdong Province in the period of 2010-2013. Distributed lag non-linear model (DLNM) with quasi-Poisson was adopted to quantify the effects of temperature on HFMD in 21 cities. Then the effects of each city were pooled by multivariate meta-analysis to obtain the heterogeneity among 21 cities. Potential city-level factors were included in meta-regression to explore effect modifiers. Results A total of 1,048,574 childhood cases were included in this study. There was a great correlation between daily childhood HFMD cases and temperature in each city, which was non-linear and lagged. High heterogeneity was showed in the associations between temperature and HFMD in 21 cities. The pooled temperature-HFMD association was peaking at the 79th percentile of temperature with relative risk (RR) of 2.474(95%CI: 2.065-2.965) as compared to the median temperature. Latitude was the main modifier for reducing the heterogeneity to 69.28% revealed by meta-analysis. Conclusions There was a strong non-linear and lagged correlation between temperature and HFMD. Latitude was strongly associated with the relationship between temperature and HFMD. Meanwhile, it had an effect on modifying the relationship. These findings can conducive to local governments developing corresponding preventive measures.

scholarly journals Associations between ambient air pollution and daily incidence of pediatric hand, foot and mouth disease in Ningbo, 2014–2016: a distributed lag nonlinear model

2020 ◽  
Vol 148 ◽  
Author(s):  
Shaohua Gu ◽  
Decheng Li ◽  
Beibei Lu ◽  
Ruixue Huang ◽  
Guozhang Xu
Keyword(s):  
Air Pollution ◽  
Nonlinear Models ◽  
Critical Role ◽  
Foot And Mouth Disease ◽  
Ambient Air ◽  
Mouth Disease ◽  
Ambient Air Pollution ◽  
Targeted Prevention ◽  
Distributed Lag ◽  
Foot And Mouth

Abstract Hand, foot and mouth disease (HFMD) has high prevalence around the world, with serious consequences for children. Due to the long survival period of HFMD virus in ambient air, air pollutants may play a critical role in HFMD epidemics. We collected data on daily cases of HFMD among children aged 0–14 years in Ningbo City between 2014 and 2016. Distributed lag nonlinear models were used to assess the effects of particulate matter (PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3) on the daily incidence of HFMD among children, with analyses stratified by gender and age. Compared with moderate levels of air pollution, high SO2 levels had a relative risk (RR) of 2.32 (95% CI 1.42–3.79) and high NO2 levels had a RR of 2.01 (95% CI 1.22–3.31). The RR of O3 was 2.12 (95% CI 1.47–3.05) and that of PM2.5 was 0.77 (95% CI 0.64–0.92) at moderate levels of air pollution. Specifically, high levels of SO2 and NO2 had RRs of 2.39 (95% CI 1.44–3.96) and 2.02 (95% CI 1.21–3.39), respectively, among 0–4-year-old children, while high O3 had an RR of 2.31 (95% CI 1.09–4.89) among 5–14-year-old children. Our findings suggest significant associations of high SO2 and NO2 levels and moderate O3 levels in HFMD epidemics, and also indicate that air pollution causes lagged effects on HFMD epidemics. Our study provides practical and useful data for targeted prevention and control of HMFD based on environmental evidence.

scholarly journals Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China

BMJ Open ◽  
2017 ◽  
Vol 7 (10) ◽  
pp. e016263 ◽  
Author(s):  
Zhicheng Du ◽  
Lin Xu ◽  
Wangjian Zhang ◽  
Dingmei Zhang ◽  
Shicheng Yu ◽  
...  
Keyword(s):  
Search Engine ◽  
Surveillance System ◽  
Goodness Of Fit ◽  
Ecological Study ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Surveillance Data ◽  
Linear Effect ◽  
Non Linear ◽  
Foot And Mouth

ObjectivesHand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD.DesignEcological study.Setting and participantsInformation on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011–2014. Analyses were conducted at aggregate level and no confidential information was involved.Outcome measuresA seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI.ResultsA high correlation between HFMD incidence and BDI (r=0.794, p<0.001) or temperature (r=0.657, p<0.001) was observed using both time series plot and correlation matrix. A linear effect of BDI (without lag) and non-linear effect of temperature (1 week lag) on HFMD incidence were found in a distributed lag non-linear model. Compared with the model based on surveillance data only, the ARIMAX model including BDI reached the best goodness-of-fit with an Akaike information criterion (AIC) value of −345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%.ConclusionsAn ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings.

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