The threshold effects of meteorological factors on Hand, foot, and mouth disease (HFMD) in China, 2011

Spatial homogeneity pursuit of regression coefficients for hand, foot and mouth disease in Xinjiang Uygur Autonomous Region in 2018

To explore the complex spatial pattern between the incidence of hand, foot, and mouth disease (HFMD) and meteorological factors [average temperature (AT), average relative humidity (ARH), average air pressure (AP), average wind speed (AW)], this paper constructed a Spatial Clustering coefficient (SCC) regression model to detect spatial clustering patterns of each regression coefficients in different seasons. The results revealed that compared with geographically weighted regression (GWR), the coefficients estimated by SCC method were more smooth with clearly identified spatial and improved edge effects. Therefore, interesting spatial patterns were easy to identify in the SCC estimated coefficients. And then, the SCC method had better estimation accuracy in estimating the relationship between potential meteorological factors and HFMD cases. Meteorological factors had different significance in their effect on HFMD incidence depending on the season. Specifically, the influence of AT on HFMD was negatively correlated in summer and winter, especially in the Altay region, Bayingoleng Mongolian Autonomous Prefecture, Turpan region and Hami region. Second, AW had positive effects with HFMD in summer, but the AW played a negative role in the whole Xinjiang in winter. In Tianshan district, Shayibake district, Shuimogou district, etc. in summer, ARH showed a strong negative correlation, but in Alar city it had a high positive correlation, however, in winter ARH showed a high negative correlation in Altay regions, Aksu region and other places had negative effects, and it showed a strong positive correlation in Shayibak district. Finally, AP had a strong positive correlation with HFMD in summer in Shaybak district, but in winter, AP showed a strong negative correlation in Altay district and Buxel Mongolia Autonomous county. In summary, Xinjiang should adapt measures to local conditions, and formulate appropriate HFMD prevention strategies according to the characteristics of different regions, time, and meteorological factors.

Assessing the impact of ambient temperature on the risk of hand, foot, and mouth disease in Guangdong, China: New insight from the disease severity and burden

Background

The association between the incidence of hand, foot, and mouth disease (HFMD) and ambient temperature has been well documented. Although the severity of symptoms is an important indicator of disease burden and varies significantly across cases, it usually was ignored in previous studies, potentially leading to biased estimates of the health impact of temperature.

Methods

We estimated the disability-adjusted life year (DALY) by considering the severity of symptoms for each HFMD case reported during 2010–2012 in Guangdong and used distributed lag-nonlinear models to estimate the association between the daily average temperature and daily DALY of HFMD cases at the city-level. We investigated the potential effect modifiers on the pathway between temperature and DALY and pooled city-specific estimates to a provincial association using a meta-regression. The overall impact of temperature was further evaluated by estimates of DALYs that could be attributed to HFMD.

Results

The overall cumulative effect of daily mean temperature on the DALY of HFMD showed an inverse-U shape, with the maximum effect estimated to be β = 0.0331 (95%CI: 0.0199–0.0463) DALY at 23.8°C. Overall, a total of 6.432 (95%CI: 3.942–8.885) DALYs (attributable fraction = 2.721%, 95%CI: 1.660–3.759%) could be attributed to temperature exposure. All the demographic subgroups had a similar trend as the main analysis, while the magnitude of the peak of the temperature impact tended to be higher among the males, those aged ≥3yrs or from the Pear-River Delta region. Additionally, the impact of temperature on DALY elevated significantly with the increasing population density, per capita GDP, and per capita green space in parks.

Conclusions

Temperature exposure was associated with increased burden of HFMD nonlinearly, with certain groups such as boys and those from areas with greater population density being more vulnerable.

Hand, foot, and mouth disease (HFMD) is a contagious viral infection common in young children. Although the association between ambient temperature and the risk of HFMD has been well documented, existing studies were solely based on the reported number of cases, failing to differentiate cases of different severity. This study improves the estimation of disease burden by additionally accounting for the severity of symptoms. Our major findings included that (1) we identified an inverse-U shaped association between the ambient temperature and the daily DALY (i.e. an established indicator for disease burden) associated with HFMD, with 2.7% DALY could be attributed to the temperature exposure; (2) the peak impact of temperature on DALY was estimated to be β = 0.0331 (95%CI: 0.0199–0.0463) DALY and identified at 23.8°C; (3) the trends were generally consistent across different demographic and geographic subgroups, with the peak effect identified to be greater among the males, those aged ≥3yrs or from the Pear-River Delta region; (4) the impact of temperature on DALY elevated more apparently in areas with a greater population density, per capita GDP, or per capita green space in parks.

Effects of temperature and PM2.5 on the incidence of hand, foot, and mouth in a heavily polluted area, Shijiazhuang, China

The influence of weather and air pollution factors on hand, foot, and mouth disease (HFMD) has received widespread attention. However, most of the existing studies came from lightly polluted areas and the results were inconsistent. There was a lack of relevant evidence of heavily polluted areas. This study aims to quantify the relationship between weather factors and air pollution with HFMD in heavily polluted areas. We collected the daily number of hand, foot, and mouth disease in Shijiazhuang, China from 2014 to 2018, as well as meteorological and air pollutant data over the same period. The generalized linear model combined with the distributed lag model was used to study the effect of meteorological factors and air pollutants on the daily cases of HFMD and its hysteresis effect. We found that the dose-response relationship between temperature, PM_2.5, and the risk of hand-foot-mouth disease was non-linear. Both low temperature and high temperature increased the risk of hand-foot-mouth disease. The cumulative effect of high temperature reached the maximum at 0-10 lag days, and the cumulative effect of low temperature reached the maximum at 0-3 lag days. The concentration of PM_2.5 between 76 and 200 μg/m³ has a certain risk of the onset of hand, foot, and mouth disease, but the extreme PM_2.5 concentration has a certain protective effect. In addition, low humidity, low wind speed, and low-O₃ can increase the risk of HFMD. Risks of humidity and low concentration of O₃ increased as lag days extended. In conclusion, our study found that climate factors and air pollutants exert varying degrees of impact on HFMD. Our research provided the scientific basis for establishing an early warning system so that medical staff and parents can take corresponding measures to prevent HFMD.

Effect of climate factors on the incidence of hand, foot, and mouth disease in Malaysia: A generalized additive mixed model

Climate change is one of the critical determinants affecting life cycles and transmission of most infectious agents, including malaria, cholera, dengue fever, hand, foot, and mouth disease (HFMD), and the recent Corona-virus pandemic. HFMD has been associated with a growing number of outbreaks resulting in fatal complications since the late 1990s. The outbreaks may result from a combination of rapid population growth, climate change, socioeconomic changes, and other lifestyle changes. However, the modeling of climate variability and HFMD remains unclear, particularly in statistical theory development. The statistical relationship between HFMD and climate factors has been widely studied using generalized linear and additive modeling. When dealing with time-series data with clustered variables such as HFMD with clustered states, the independence principle of both modeling approaches may be violated. Thus, a Generalized Additive Mixed Model (GAMM) is used to investigate the relationship between HFMD and climate factors in Malaysia. The model is improved by using a first-order autoregressive term and treating all Malaysian states as a random effect. This method is preferred as it allows states to be modeled as random effects and accounts for time series data autocorrelation. The findings indicate that climate variables such as rainfall and wind speed affect HFMD cases in Malaysia. The risk of HFMD increased in the subsequent two weeks with rainfall below 60 mm and decreased with rainfall exceeding 60 mm. Besides, a two-week lag in wind speeds between 2 and 5 m/s reduced HFMD's chances. The results also show that HFMD cases rose in Malaysia during the inter-monsoon and southwest monsoon seasons but fell during the northeast monsoon. The study's outcomes can be used by public health officials and the general public to raise awareness, and thus, implement effective preventive measures.

Spatial-temporal heterogeneity and meteorological factors of hand-foot-and-mouth disease in Xinjiang, China from 2008 to 2016

The study aims to depict the temporal and spatial distributions of hand-foot-and-mouth disease (HFMD) in Xinjiang, China and reveal the relationships between the incidence of HFMD and meteorological factors in Xinjiang. With the national surveillance data of HFMD in Xinjiang and meteorological parameters in the study area from 2008 to 2016, in GeoDetector Model, we examined the effects of meteorological factors on the incidence of HFMD in Xinjiang, China, tested the spatial-temporal heterogeneity of HFMD risk, and explored the temporal-spatial patterns of HFMD through the spatial autocorrelation analysis. From 2008 to 2016, the HFMD distribution showed a distinct seasonal pattern and HFMD cases typically occurred from May to July and peaked in June in Xinjiang. Relative humidity, precipitation, barometric pressure and temperature had the more significant influences on the incidence of HFMD than other meteorological factors with the explanatory power of 0.30, 0.29, 0.29 and 0.21 (P<0.000). The interaction between any two meteorological factors had a nonlinear enhancement effect on the risk of HFMD. The relative risk in Northern Xinjiang was higher than that in Southern Xinjiang. Global spatial autocorrelation analysis results indicated a fluctuating trend over these years: the positive spatial dependency on the incidence of HFMD in 2008, 2010, 2012, 2014 and 2015, the negative spatial autocorrelation in 2009 and a random distribution pattern in 2011, 2013 and 2016. Our findings revealed the correlation between meteorological factors and the incidence of HFMD in Xinjiang. The correlation showed obvious spatiotemporal heterogeneity. The study provides the basis for the government to control HFMD based on meteorological information. The risk of HFMD can be predicted with appropriate meteorological factors for HFMD prevention and control.

Spatiotemporal characteristics and meteorological determinants of hand, foot and mouth disease in Shaanxi Province, China: a county-level analysis

BACKGROUND

Hand, foot and mouth disease (HFMD) is one of the common intestinal infectious diseases worldwide and has caused huge economic and disease burdens in many countries. The average annual incidence rate of HFMD was 11.66% in Shaanxi during the time span from 2009 to 2018. There are distinct differences within Shaanxi, as it is a special region that crosses three temperature zones. Hence, in this study, a spatiotemporal analysis of Shaanxi was performed to reveal the characteristics of the distribution of HFMD and to explore the meteorological determinants of HFMD.

METHODS

The county-level and municipal data from Shaanxi Province from 2009 to 2018 were applied to research the spatiotemporal characteristics of HFMD and its meteorological determinants. Time series and spatial autocorrelation analyses were applied to assess the spatiotemporal characteristics of HFMD. This study used spatial econometric panel models to explore the relationship between HFMD and meteorological factors based on the data of 107 counties and 10 municipalities.

RESULTS

The incidence rate of HFMD displayed no variable trend throughout the whole research period. A high incidence rate of HFMD was observed from June to September, corresponding to a time when the climate is characterized by heavy rain, high temperature, and high humidity. The high-incidence areas were mainly located in the central region in Shaanxi, whereas the low-incidence spots were mainly found in Northern Shaanxi. Regarding the meteorological factors analysed in this study, in general, the incidence rate of HFMD in specific regions was positively associated with the rainfall, temperature and humidity.

CONCLUSION

These results could be applied by the government and the general public to take effective measures to prevent disease. Region-targeted policies could be enacted and implemented in the future according to specific situations in different areas and the relevant meteorological determinants. Additionally, meteorological conditions normally extend to a wide-ranging region; thus, cooperation among surrounding regions is necessary.

Assessment of Temperature-Hand, Foot, and Mouth Disease Association and Its Variability across Urban and Rural Populations in Wuxi, China: A Distributed Lag Nonlinear Analysis

Hand, foot, and mouth disease (HFMD) has brought millions of attacks and a substantial burden in the Asia-Pacific region. Previous studies assessed disease risks around the world, which demonstrated great heterogeneity, and few determined the modification effect of social factors on temperature-disease relationship. We conducted a time-series study to evaluate the temperature-associated HFMD morbidity risk using daily data (from 2011 to 2017) and to identify potential modifiers relating to urban-rural status and aggregation mode of children. By applying a distributed lag nonlinear model (DLNM) and controlling for time-varying factors and other meteorological factors, we found that the relationship between daily mean temperature and the cumulative risk of HFMD was an approximately M-shaped curve. The effects of higher temperature appeared to be greater and more persistent than those of lower temperature. With the reference of -6°C, the cumulative relative risk (RR) values of high temperature (95 percentile) and low temperature (5 percentile) were 3.74 (95% CI: 2.50-5.61) and 1.72 (95% CI: 1.24-2.37) at lag 4-7, respectively. Temperature-associated HFMD morbidity risks were more pronounced among rural children and those attending kindergartens or schools at specific lags and temperatures. Relative risk values for temperature-disease association was highest among the 3- to 6-year group, whereas no gender difference was observed. Studying effect estimates and their modifications using the DLNM on a daily scale helps to identify susceptible groups and guide policy-making and resource allocation according to specific local conditions.

Using deep learning to predict the hand-foot-and-mouth disease of enterovirus A71 subtype in Beijing from 2011 to 2018

Hand-foot-and-month disease (HFMD), especially the enterovirus A71 (EV-A71) subtype, is a major health problem in Beijing, China. Previous studies mainly used regressive models to forecast the prevalence of HFMD, ignoring its intrinsic age groups. This study aims to predict HFMD of EV-A71 subtype in three age groups (0–3, 3–6 and > 6 years old) from 2011 to 2018 using residual-convolutional-recurrent neural network (CNNRNN-Res), convolutional-recurrent neural network (CNNRNN) and recurrent neural network (RNN). They were compared with auto-regressio, global auto-regression and vector auto-regression on both short-term and long-term prediction. Results showed that CNNRNN-Res and RNN had higher accuracies on point forecast tasks, as well as robust performances in long-term prediction. Three deep learning models also had better skills in peak intensity forecast, and CNNRNN-Res achieved the best results in the peak month forecast. We also found that three age groups had consistent outbreak trends and similar patterns of prediction errors. These results highlight the superior performance of deep learning models in HFMD prediction and can assist the decision-makers to refine the HFMD control measures according to age groups.

Impact of Ambient Temperature and Relative Humidity on the Incidence of Hand-Foot-Mouth Disease in Wuhan, China

Background: Few studies have previously explored the relationship between hand, foot, and mouth disease (HFMD) and meteorological factors with the effect modification of air pollution, and these studies had inconsistent findings. We therefore applied a time-series analysis assessing the effects of temperature and humidity on the incidence of HFMD in Wuhan, China to deepen our understanding of the relationship between meteorological factors and the risk of HFMD. Methods: Daily HFMD cases were retrieved from Hubei Provincial Center for Disease Control and Prevention from 1 February 2013 to 31 January 2017. Daily meteorological data including 24 h average temperature, relative humidity, wind velocity, and atmospheric pressure were obtained from Hubei Meteorological Bureau. Data on Air pollution was collected from 10 national air-monitoring stations in Wuhan city. We adopted a distributed lag non-linear model (DLNM) combined with Poisson regression and time-series analysis to estimate the effects of temperature and relative humidity on the incidence HFMD. Results: We found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "M" shape with two peaks occurring at 2.3 °C (RR = 1.760, 95% CI: 1.218-2.542) and 27.9 °C (RR = 1.945, 95% CI: 1.570-2.408), respectively. We observed an inverted "V" shape between relative humidity and HFMD. The risk of HFMD reached a maximum value at a relative humidity of 89.2% (RR = 1.553, 95% CI: 1.322-1.824). The largest delayed cumulative effects occurred at lag 6 for temperature and lag 13 for relative humidity. Conclusions: The non-linear relationship between meteorological factors and the incidence of HFMD on different lag days could be used in the early targeted warning system of infectious diseases, reducing the possible outbreaks and burdens of HFMD among sensitive populations.

Impact of Ambient Temperature and Relative Humidity on the Incidence of Hand-Foot-Mouth Disease in Wuhan, China

Background: Few studies have previously explored the relationship between hand, foot, and mouth disease (HFMD) and meteorological factors with the effect modification of air pollution, and these studies had inconsistent findings. We therefore applied a time-series analysis assessing the effects of temperature and humidity on the incidence of HFMD in Wuhan, China to deepen our understanding of the relationship between meteorological factors and the risk of HFMD. Methods: Daily HFMD cases were retrieved from Hubei Provincial Center for Disease Control and Prevention from 1 February 2013 to 31 January 2017. Daily meteorological data including 24 h average temperature, relative humidity, wind velocity, and atmospheric pressure were obtained from Hubei Meteorological Bureau. Data on Air pollution was collected from 10 national air-monitoring stations in Wuhan city. We adopted a distributed lag non-linear model (DLNM) combined with Poisson regression and time-series analysis to estimate the effects of temperature and relative humidity on the incidence HFMD. Results: We found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "M" shape with two peaks occurring at 2.3 °C (RR = 1.760, 95% CI: 1.218-2.542) and 27.9 °C (RR = 1.945, 95% CI: 1.570-2.408), respectively. We observed an inverted "V" shape between relative humidity and HFMD. The risk of HFMD reached a maximum value at a relative humidity of 89.2% (RR = 1.553, 95% CI: 1.322-1.824). The largest delayed cumulative effects occurred at lag 6 for temperature and lag 13 for relative humidity. Conclusions: The non-linear relationship between meteorological factors and the incidence of HFMD on different lag days could be used in the early targeted warning system of infectious diseases, reducing the possible outbreaks and burdens of HFMD among sensitive populations.

Weather effects on hand, foot, and mouth disease at individual level: a case-crossover study

BACKGROUND

Hand, foot, and mouth disease (HFMD) raises an urgent public health issue in the Asia-Pacific region, especially in China. The associations between weather factors and HFMD have been widely studied but with inconsistent results. Moreover, previous studies utilizing ecological design could not rule out the bias of exposure misclassification and unobserved confounders.

METHODS

We used case-crossover analysis to assess the associations of weather factors on HFMD. Individual HFMD cases from 2009 to 2012 in Guangdong were collected and cases located within 10 km of the meteorological monitoring sites were included. Lag effects were examined through the previous 7 days. In addition, we explored the variability by changing the distance within 20 km and 30 km.

RESULTS

We observed associations between HFMD and weather factors, including temperature and relative humidity. An approximately U-shaped relationship was observed for the associations of temperature on HFMD across the same day and the previous 7 days, while an approximately exponential-shaped was seen for relative humidity. Statistically significant increases in rates of HFMD were associated with each 10-unit increases in temperature [Excess rate (ER): 7.7%; 95% Confidence Interval (CI): 3.9, 11.7%] and relative humidity (ER: 1.9%; 95% CI: 0.7, 3.0%) on lag days 0-6, when assessing within 10 km of the monitoring sites. Potential thresholds for temperature (30.0 °C) and relative humidity (70.3%) detected showed associations with HFMD. The associations remained robust for 20 km and 30 km.

CONCLUSIONS

Our study found that temperature and relative humidity are significantly associated with the increased rates of HFMD. Thresholds and lag effects were observed between weather factors and HFMD. Our findings are useful for planning on targeted prevention and control of HFMD.

Spatial-temporal heterogeneity of hand, foot and mouth disease and impact of meteorological factors in arid/ semi-arid regions: a case study in Ningxia, China

Background

The incidence of hand, foot and mouth disease (HFMD) varies over space and time and this variability is related to climate and social-economic factors. Majority of studies on HFMD were carried out in humid regions while few have focused on the disease in arid/semi-arid regions, more research in such climates would potentially make the mechanism of HFMD transmission clearer under different climate conditions.

Methods

In this paper, we explore spatial-temporal distribution of HFMD in Ningxia province, which has an arid/semi-arid climate in northwest China. We first employed a Bayesian space-time hierarchy model (BSTHM) to assess the spatial-temporal heterogeneity of the HFMD cases and its relationship with meteorological factors in Ningxia from 2009 to 2013, then used a novel spatial statistical software package GeoDetector to test the spatial-temporal heterogeneity of HFMD risk.

Results

The results showed that the spatial relative risks in northern part of Ningxia were higher than those in the south. The highest temporal risk of HFMD incidence was in fall season, with a secondary peak in spring. Meteorological factors, such as average temperature, relative humidity, and wind speed played significant roles in the spatial-temporal distribution of HFMD risk.

Conclusions

The study provide valuable information on HFMD distribution in arid/semi-arid areas in northwest China and facilitate understanding of the concentration of HFMD.

Environmental persistence of foot-and-mouth disease virus applied to endemic regions

The consequences of foot-and-mouth disease impact regional economies and food security through animal mortality and morbidity, trade restrictions and burdens to veterinary infrastructure. Despite efforts to control the disease, some regions, mostly in warmer climates, persistently report disease outbreaks. Consequently, it is necessary to understand how environmental factors influence transmission, of this economically devastating disease. Extensive research covers basic aetiology and transmission potential of livestock and livestock products for foot-and-mouth disease virus (FMDV), with a subset evaluating environmental survival. However, this subset, completed in the early to mid-20th century in Northern Europe and the United States, is not easily generalized to today's endemic locations. This review uncovered 20 studies, to assess current knowledge and analyse the effects of environmental variables on FMDV survival, using a Cox proportional hazards (Coxph) model. However, the dataset is limited, for example pH was included in three studies and only five studies reported both relative humidity (RH) and temperature. After dropping pH from the analysis, our results suggest that temperature alone does not describe FMDV survival; instead, interactions between RH and temperature have broader impacts across various conditions. For instance, FMDV is expected to survive longer during the wet season (survival at day 50 is ~90% at 16°C and 86% RH) versus the dry season (survival at day 50 approaches 0% at 16°C and 37.5% RH) or comparatively in the UK versus the Southwestern United States. Additionally, survival on vegetation topped 70% on day 75 when conditions exceeded 20°C with high RH (86%), drastically higher than the survival on inanimate surfaces at the same temperature and RH (~0%). This is important in tropical regions, where high temperatures can persist throughout the year, but RH varies. Therefore, parameter estimates, for disease modelling and control in endemic areas, require environmental survival data from a wider range of conditions.

Impact of PM10 and meteorological factors on the incidence of hand, foot, and mouth disease in female children in Ningbo, China: a spatiotemporal and time-series study

Hand, foot, and mouth disease (HFMD) is a viral illness that is considered a critical public health challenge worldwide. Previous studies have demonstrated that meteorological parameters are significantly related to the incidence of HFMD in children; however, few studies have focused only on female children. This study quantified the associations of HFMD incidence with meteorological parameters and PM₁₀ (particulate matter with an aerodynamic diameter of 10 μm) among female children. Data were collected on daily HFMD cases, meteorological variables, and PM₁₀ levels in Ningbo, China, from January 2012 to December 2016. Data were assessed using a distributed lag nonlinear model (DLNM) with Poisson distribution. A total of 59,809 female children aged 0-15 years with HFMD were enrolled. The results showed that highest relative risk (RR) of HFMD for temperature was 3 °C and the lag effect was 3 days. The highest RR for PM₁₀ was 80 mg/m³ and the lag effect was 5 days. Spatial analysis showed that female HFMD incidence was mainly concentrated in the suburban of Ningbo city indicating that female children in this area should be more paid attention on avoiding this disease outbreak. Our findings suggest that HFMD prevention strategies should focus more attention on local meteorological parameters.

Interactions between climate factors and air pollution on daily HFMD cases: A time series study in Guangdong, China

BACKGROUND

Prior studies have shown that climate factors and air pollution are associated with hand, foot, and mouth disease (HFMD) epidemics. However, the interaction between air pollution and climate factors remains unknown.

METHODS

Daily HFMD counts from 2009 through 2012 in Guangdong were collected. We used distributed lag non-linear models to assess the associations of climate factors and air pollution on HFMD cases. The effects of climate factors were stratified by air pollution stratum to examine the interaction effect of air quality index (AQI) and temperature, as well as relative humidity. In addition, we explored the variability across gender groups.

RESULTS

We observed associations between HFMD cases and environmental factors, including temperature, relative humidity, and AQI. The highest relative risks (RR) were observed at the middle level of temperature and AQI, and high level of relative humidity. The effects for the interaction between AQI and climate factors on HFMD cases were also statistically observed. Compared with low level temperatures (≤23.5 °C), high level temperatures (>23.5 °C) had a RR of 1.486 (95%CI: 1.469,1.503) on days with "good" air quality (AQI ≤ 46), and RR of 1.013 (95%CI: 1.003,1.023) on days with "moderate" air quality (AQI > 46). For relative humidity, the high level (>77%) had a RR of 1.082 (95%CI: 1.076,1.089) on days with "good" air quality, and RR of 1.039 (95%CI: 1.033,1.046) on days with "moderate" air quality. The associations and the interactions remained robust for males and females.

CONCLUSIONS

Our findings indicate that climate factors and air pollution imposed lagged and non-linear effects on HFMD epidemics. The effects of climate factors on health potentially vary by AQI. Our study is practical and useful for targeted prevention and control, and provides environmental-based evidence.

Effect of ambient temperature and its effect modifiers on bacillary dysentery in Jinan, China

BACKGROUND

Studies about the modified effect among various meteorological factors on bacillary dysentery (BD) are limited. This study aimed to investigate the effect of ambient temperature and its effect modifiers on BD in Jinan.

METHODS

Daily data of BD cases and meteorological factors from 2005 to 2013 were collected. A generalized additive model (GAM) was conducted to explore the relationship between meteorological factors and BD. Then a distributed lag non-linear model (DLNM) was developed to assess the lag and cumulative effect. Finally, the modified effect between temperature and other meteorological factors on BD was explored by the GAM and a weather-stratified model.

RESULTS

A total of 11,738 cases of BD were notified over the study period. The exposure-response relationship between temperature and BD was liner with a single threshold value of 0 °C. Results of DLNM showed that after temperature exceeds the threshold, each 5 °C rise in temperature caused a 19% (RR = 1.19, 95% CI: 1.14-1.24) increase in the number of cases of BD at lag 0. The analysis of cumulative effects showed that each 5 °C rise in temperature can increase the number of cases by 61% (RR = 1.61, 95% CI: 1.58-1.63) at lag 0-lag 7 days. The effect modification of the association between temperature and BD by humidity was observed in our study, while the modification by precipitation and wind speed were not statistically significant. The risk of BD was highest when temperature and humidity were both high.

CONCLUSIONS

Our study indicates that temperature is significantly associated with the risk of BD in the study area, and the effect can be modified by humidity. Public health professionals and medical service providers should pay more attention BD prevention and control when the weather condition of both high temperature and high humidity would occur.

Exploring spatiotemporal nonstationary effects of climate factors on hand, foot, and mouth disease using Bayesian Spatiotemporally Varying Coefficients (STVC) model in Sichuan, China

BACKGROUND

Pediatric hand, foot, and mouth disease (HFMD) has generally been found to be associated with climate. However, knowledge about how this association varies spatiotemporally is very limited, especially when considering the influence of local socioeconomic conditions. This study aims to identify multi-sourced HFMD environmental factors and further quantify the spatiotemporal nonstationary effects of various climate factors on HFMD occurrence.

METHODS

We propose an innovative method, named spatiotemporally varying coefficients (STVC) model, under the Bayesian hierarchical modeling framework, for exploring both spatial and temporal nonstationary effects in climate covariates, after controlling for socioeconomic effects. We use data of monthly county-level HFMD occurrence and data of related climate and socioeconomic variables in Sichuan, China from 2009 to 2011 for our experiments.

RESULTS

Cross-validation experiments showed that the STVC model achieved the best average prediction accuracy (81.98%), compared with ordinary (68.27%), temporal (72.34%), spatial (75.99%) and spatiotemporal (77.60%) ecological models. The STVC model also outperformed these models in the Bayesian model evaluation. In this study, the STVC model was able to spatialize the risk indicator odds ratio (OR) into local ORs to represent spatial and temporal varying disease-climate relationships. We detected local temporal nonlinear seasonal trends and spatial hot spots for both disease occurrence and disease-climate associations over 36 months in Sichuan, China. Among the six representative climate variables, temperature (OR = 2.59), relative humidity (OR = 1.35), and wind speed (OR = 0.65) were not only overall related to the increase of HFMD occurrence, but also demonstrated spatiotemporal variations in their local associations with HFMD.

CONCLUSION

Our findings show that county-level HFMD interventions may need to consider varying local-scale spatial and temporal disease-climate relationships. Our proposed Bayesian STVC model can capture spatiotemporal nonstationary exposure-response relationships for detailed exposure assessments and advanced risk mapping, and offers new insights to broader environmental science and spatial statistics.

Meteorological factors and its association with hand, foot and mouth disease in Southeast and East Asia areas: a meta-analysis

Since the late 1990s, hand, foot and mouth disease (HFMD) has become a common health problem that mostly affects children and infants in Southeast and East Asia. Global climate change is considered to be one of the major risk factors for HFMD. This study aimed to assess the correlation between meteorological factors and HFMD in the Asia-Pacific region. PubMed, Web of Science, Embase, China National Knowledge Infrastructure, Wanfang Data and Weipu Database were searched to identify relevant articles published before May 2018. Data were collected and analysed using R software. We searched 2397 articles and identified 51 eligible papers in this study. The present study included eight meteorological factors; mean temperature, mean highest temperature, mean lowest temperature, rainfall, relative humidity and hours of sunshine were positively correlated with HFMD, with correlation coefficients (CORs) of 0.52 (95% confidence interval (CI) 0.42–0.60), 0.43 (95% CI 0.23–0.59), 0.43 (95% CI 0.23–0.60), 0.27 (95% CI 0.19–0.35), 0.19 (95% CI 0.02–0.35) and 0.19 (95% CI 0.11–0.27), respectively. There were sufficient data to support a negative correlation between mean pressure and HFMD (COR = −0.51, 95% CI −0.63 to −0.36). There was no notable correlation with wind speed (COR = 0.10, 95% CI −0.03 to 0.23). Our findings suggest that meteorological factors affect the incidence of HFMD to a certain extent.

Bayesian spatiotemporal analysis for association of environmental factors with hand, foot, and mouth disease in Guangdong, China

Hand, foot, and mouth disease (HFMD) remains a significant public health and economic burden in parts of China, particularly Guangdong Province. Although the association between meteorological factors and HFMD has been well documented, significant gaps remain in our understanding of the potential impact of environmental factors. Using county-level monthly HFMD data from China CDC and environmental data from multiple sources, we used spatiotemporal Bayesian models to evaluate the association between HFMD and environmental factors including vegetation index, proportion of artificial surface, road capacity, temperature and humidity, and assessed the spatial and temporal dynamic of the association. Statistically significant correlation coefficients from -0.056 to 0.36 (all P < 0.05) were found between HFMD incidence and all environmental factors. The contributions of these factors for HFMD incidence were estimated to be 16.32%, 12.31%, 14.61%, 13.53%, and 2.63%. All environmental factors including vegetation index (Relative Risk: 0.889; Credible Interval: 0.883-0.895), artificial surface (1.028; 1.022-1.034), road capacity (1.033; 1.028-1.038), temperature (1.039; 1.028-1.05), and relative humidity (1.015; 1.01-1.021) were statistically retained in the final spatiotemporal model. More comprehensive environmental factors were identified as associating with HFMD incidence. Taking these environmental factors into consideration for prevention and control strategy might be of great practical significance.

Temperature and humidity affect the incidence of hand, foot, and mouth disease: a systematic review of the literature - a report from the International Society of Dermatology Climate Change Committee

Hand, foot, and mouth disease (HFMD) is an enterovirus-mediated condition that predominantly affects children under 5 years of age. The tendency for outbreaks to peak in warmer summer months suggests a relationship between HFMD and weather patterns. We reviewed the English-language literature for articles describing a relationship between meteorological variables and HFMD. Seventy-two studies meeting criteria were identified. A positive, statistically significant relationship was identified between HFMD cases and both temperature (61 of 67 studies, or 91.0%, reported a positive relationship) [CI 81.8-95.8%, P = 0.0001] and relative humidity (41 of 54 studies, or 75.9%) [CI 63.1-85.4%, P = 0.0001]. No significant relationship was identified between HFMD and precipitation, wind speed, and/or sunshine. Most countries reported a single peak of disease each year (most commonly early Summer), but subtropical and tropical climate zones were significantly more likely to experience a bimodal distribution of cases throughout the year (two peaks a year; most commonly late spring/early summer, with a smaller peak in autumn). The rising global incidence of HFMD, particularly in Pacific Asia, may be related to climate change. Weather forecasting might be used effectively in the future to indicate the risk of HFMD outbreaks and the need for targeted public health interventions.

Effects of relative humidity on childhood hand, foot, and mouth disease reinfection in Hefei, China

BACKGROUND

In recent years, hand, foot, and mouth disease (HFMD) has become a major public health issue in China, and its reinfection rate has been high. Numerous studies have examined the effects of meteorological factors involved in HFMD infection. However, no study has investigated the effects on HFMD reinfection. The present study analyzed the relationship between relative humidity and HFMD reinfection.

METHODS

We employed a distributed lag nonlinear model to evaluate the relationship between relative humidity and childhood HFMD reinfection in Hefei, China during 2011-2016. This model controlled confounding factors, including seasonality, long-term trend, day of the week, precipitation, and mean temperature.

RESULTS

Childhood HFMD reinfection cases occurred mainly from April to July, and the second peak occurred from October to December. A statistically significant association was observed between relative humidity and HFMD reinfection with delayed effects. The adverse effect of high relative humidity (>75%) appeared later than those of low relative humidity (<75%). Moreover, the highest relative risk (RR 1.08, 95% CI 1.04-1.13) occurred when the relative humidity was 100% and had an 8-day lag. Given the differences between gender and age groups, the effects of extremely high relative humidity on females and those aged ≥4years were higher than those of other groups and caused the highest cumulative relative risks at lag 0-9 or 0-10days (Female: RR 2.00, 95% CI 1.23-3.26; Male: RR 1.55, 95% CI 1.04-2.30; Aged ≥4years: RR 2.31, 95% CI 1.27-4.18; Aged <4years: RR 1.51, 95% CI 1.04-2.20).

CONCLUSION

High and low relative humidity were found to cause the elevated risks of HFMD reinfection, and the highest risk was observed at extremely high relative humidity. Early warning systems should be built for the protection of susceptible populations, particularly females and children aged ≥4years.

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

OBJECTIVES

Hand, 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.

DESIGN

Ecological study.

SETTING AND PARTICIPANTS

Information 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 MEASURES

A 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.

RESULTS

A 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%.

CONCLUSIONS

An 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.

Estimating the basic reproduction rate of HFMD using the time series SIR model in Guangdong, China

Hand, foot, and mouth disease (HFMD) has caused a substantial burden of disease in China, especially in Guangdong Province. Based on notifiable cases, we use the time series Susceptible-Infected-Recovered model to estimate the basic reproduction rate (R0) and the herd immunity threshold, understanding the transmission and persistence of HFMD more completely for efficient intervention in this province. The standardized difference between the reported and fitted time series of HFMD was 0.009 (<0.2). The median basic reproduction rate of total, enterovirus 71, and coxsackievirus 16 cases in Guangdong were 4.621 (IQR: 3.907–5.823), 3.023 (IQR: 2.289–4.292) and 7.767 (IQR: 6.903–10.353), respectively. The heatmap of R0 showed semiannual peaks of activity, including a major peak in spring and early summer (about the 12^th week) followed by a smaller peak in autumn (about the 36^th week). The county-level model showed that Longchuan (R0 = 33), Gaozhou (R0 = 24), Huazhou (R0 = 23) and Qingxin (R0 = 19) counties have higher basic reproduction rate than other counties in the province. The epidemic of HFMD in Guangdong Province is still grim, and strategies like the World Health Organization’s expanded program on immunization need to be implemented. An elimination of HFMD in Guangdong might need a Herd Immunity Threshold of 78%.