Incidence Of Hand, Foot And Mouth Disease Research Articles

Effects of extreme meteorological factors and high air pollutant concentrations on the incidence of hand, foot and mouth disease in Jining, China.

The evidence on the effects of extreme meteorological conditions and high air pollution levels on incidence of hand, foot and mouth disease (HFMD) is limited. Moreover, results of the available studies are inconsistent. Further investigations are imperative to elucidate the specific issue. Data on the daily cases of HFMD, meteorological factors and air pollution were obtained from 2017 to 2022 in Jining City. We employed distributed lag nonlinear model (DLNM) incorporated with Poisson regression to explore the impacts of extreme meteorological conditions and air pollution on HFMD incidence. We found that there were nonlinear relationships between temperature, wind speed, PM2.5, SO2, O3 and HFMD. The cumulative risk of extreme high temperature was higher at the 95th percentile (P95th) than at the 90th percentile(P90th), and the RR values for both reached their maximum at 10-day lag (P95th RR = 1.880 (1.261-2.804), P90th RR = 1.787 (1.244-2.569)), the hazardous effect of extreme low temperatures on HFMD is faster than that of extreme high temperatures. The cumulative effect of extreme low wind speeds reached its maximum at 14-day lag (P95th RR = 1.702 (1.389-2.085), P90th RR = 1.498(1.283-1.750)). The cumulative effect of PM2.5 concentration at the P90th was largest at 14-day lag (RR = 1.637 (1.069-2.506)), and the cumulative effect at the P95th was largest at 10-day lag (RR = 1.569 (1.021-2.411)). High SO2 concentration at the P95th at 14-day lag was associated with higher risk for HFMD (RR: 1.425 (1.001-2.030)). Our findings suggest that high temperature, low wind speed, and high concentrations of PM2.5 and SO2 are associated with an increased risk of HFMD. This study not only adds insights to the understanding of the impact of extreme meteorological conditions and high levels of air pollutants on HFMD incidence but also holds practical significance for the development and enhancement of an early warning system for HFMD.

How multiple air pollutants affect hand, foot, and mouth disease incidence in children: assessing effect modification by geographical context in multicity of Sichuan, southwest China

BackgroundSeveral studies have suggested a significant association of hand, foot, and mouth disease (HFMD) with ambient air pollutants. Existing studies have characterized the role of air pollutants on HFMD using only risk ratio measures while ignoring the attributable burden. And whether the geographical context (i.e., diverse topographic features) could modulate the relationships is unclear.MethodsDaily reported childhood HFMD counts, ambient air pollution, and meteorological data during 2015–2017 were collected for each of 21 cities in Sichuan Province. A multistage analysis was carried out in different populations based on geographical context to assess effect modification by topographic conditions. We first constructed a distributed lag nonlinear model (DLNM) for each city to describe the relationships with risk ratio measures. Then, we applied a multivariate meta-regression to estimate the pooled effects of multiple air pollutants on HFMD from the exposure and lagged dimensions. Finally, attributable risks measures were calculated to quantify HFMD burden by air pollution.ResultsBased on 207554 HFMD cases in Sichuan Province, significant associations of HFMD with ambient air pollutants were observed mainly at relatively high exposure ranges. The effects of ambient air pollutants on HFMD are most pronounced on lag0 or around lag7, with relative risks gradually approaching the reference line thereafter. The attributable risks of O3 were much greater than those of other air pollutants, particularly in basin and mountain regions.ConclusionsThis study revealed significant pooled relationships between multiple air pollutants and HFMD incidence from both exposure and lag dimensions. However, the specific effects, including RRs and ARs, differ depending on the air pollution variable and geographical context. These findings provide local authorities with more evidence to determine key air pollutants and regions for devising and implementing targeted interventions.

Assessing the impact of COVID-19 interventions on the hand, foot and mouth disease in Guangdong Province, China: a Bayesian modeling study.

The non-pharmaceutical interventions (NPIs) against COVID-19 may have affected the transmission of hand, foot and mouth disease (HFMD). We aimed to assess the impact of the NPIs on HFMD in the high epidemic area of HFMD, Guangdong Province. The data of HFMD cases, etiological information, and meteorological factors in Guangdong from January 1, 2012, to December 31, 2021, were collected. Using a Bayesian structural time series (BSTS) model integrated counterfactual framework, we assessed the effect of NPIs on HFMD by different intervention periods, populations (gender, age, occupation), and cities. We further explored the correlation between the reduction of HFMD and socioeconomic factors in 21 cities. A total of 351,217 HFMD cases were reported and 455,327 cases were averted in Guangdong Province during 2020-2021 with a reduction of 84.94% (95%CI: 81.63-87.22%) in 2020 and 29.49% (95%CI: 15.26-39.54%) in 2021. The impact of NPIs on HFMD differed by age and gender. The effects of NPIs were more remarkable for children aged 0-2 years and scattered children. We found that the relative reductions in 21 cities were related to the composition ratio of children and COVID-19 incidence. The reduction of HFMD incidence was significantly associated with COVID-19 NPIs, and school closure was an effective intervention to prevent HFMD outbreaks. Our findings will contribute to the development of HFMD prevention and control measures.

Non-linear association between daily mean temperature and children’s hand foot and mouth disease in Chongqing, China

Chongqing was seriously affected by hand, foot, and mouth disease (HFMD), but the relationships between daily mean temperature and the incidence of HFMD remain unclear. This study used distributed lag nonlinear model to evaluate the effect of daily mean temperature on the incidence of HFMD in children aged < 5 years in Chongqing. Daily HFMD data from 2012 to 2019 in Chongqing were retrieved from the notifiable infectious disease surveillance system. A total of 413,476 HFMD cases aged < 5 years were reported in Chongqing from 2012 to 2019. The exposure–response curve of daily mean temperature and daily HFMD cases was wavy-shaped. The relative risks (RRs) increased as daily mean temperature below 5.66 °C or above 9.43 °C, with two peaks at 16.10 °C and 26.68 °C. The RRs reached the highest when the daily mean temperature at 26.68 °C on the current day (RR = 1.20, 95% CI 1.09–1.32), followed by the daily mean temperature at 16.10 °C at lag 5 days (RR = 1.07, 95% CI 1.05–1.08). The RRs for girls and daycare children were much higher than those for boys and scattered children, respectively. Taken together, daily mean temperature has strong effect on HFMD in children aged < 5 years old in Chongqing, particularly for girls and daycare children.

Identification Of Local Clusters Of Hand Foot And Mouth Disease Based On Local Geary C Statistic

Background: Hand, foot, and mouth disease (HFMD) is a common childhood illness caused by enteroviruses. Increasingly, the disease has a substantial burden throughout Vietnam. To better understand of the epidemiology of HFMD, this study aims to investigate the use of local Geary’s C statistic in the identification of local clusters of HFMD in Ho Chi Minh city, Vietnam. Methods: Histogram was first used to study the distribution of HFMD cases the incidence of HFMD. Local Geary C statistics was then applied to identify the spatial clusters of HFMD cases and HFMD incidence including high-high, low-low, negative and other positive clusters. Finally, HFMD cases and infection rates collected in Ho Chi Minh were used to explore the spatial clusters of HFMD. Results: It was found that, in the case of using HFMD cases, two high-high clusters in District 12 and Binh Tan in the city center, one low-low cluster in District 5 in the east of the city center and two negative clusters in Binh Thanh and District 7 in the west of the city were successfully detected. On the other hand, in the case of using HFMD infection rates, a total of three high-high clusters, one low-low cluster, one negative and one other positive clusters were successfully detected, in which, the three high-high clusters were found in the districts of Binh Tan (289 cases/100,000 inhabitants), Binh Chanh (283 cases/100,000 inhabitants) and Tan Phu (281 cases/100,000 inhabitants) in the east of the city. Conclusions: findings in this study confirm the usefulness of local Geary’s C statistic in the identification of spatial clusters of HFMD.

Surveillance, epidemiology, and impact of the coronavirus disease 2019 interventions on the incidence of enterovirus infections in Nanchang, China, 2010-2022.

Pathogen spectrum of Hand, foot and mouth disease (HFMD) has substantially changed in the past decade in China. Growing evidence has indicated that anti-COVID-19 nonpharmaceutical interventions (NPIs) can support control of various infectious diseases, including intestinal diseases. In this study, HFMD cases were enrolled from sentinel hospitals of Nanchang, Jiangxi province, and enteroviruses were genotyped using specific real time RT-PCR. We systematically characterized the epidemiology of HFMD based on the continuous molecular surveillance and estimated the impact of COVID-19 intervention on HFMD incidence using seasonal autoregressive integrated moving average (ARIMA) models. A total of 10247 HFMD cases were included during 2010-2022, of which 6121 enterovirus (EV)-positive cases (59.7%) were identified by real-time RT-PCR. Over 80% cases were associated with EV-A71 and coxsackievirus A16 (CVA16) during 2010-2012, while the type distribution significantly changed as CVA6 emerged to be dominant, accounting for 22.6%-59.6% during 2013-2022. It was observed that the prevalence patterns of EV-A71 and CVA16 were similar and both of them peaked in the second quarter and then leveled off. However, CVA6 was generally prevalent around the fourth quarter, demonstrating a staggered prevalence during 2010-2019. During the COVID-19 epidemic, the seasonal HFMD epidemic peak was restrained, and the ARIMA analysis indicated that the COVID-19 intervention had mitigated EV transmission during the first COVID-19 outbreak in early 2020. In addition, bivariate Spearman's cross-correlation coefficients were estimated for the major types CVA6, CVA16 and EV-A71. Our analyses indicated the possible existence of correlations among CVA6, CVA16 and EV-A71 prevalence in the epidemiological level. Taken together, the type distribution of HFMD has substantially changed over the last decade and CVA6 and CVA16 are currently the most predominant types co-circulating in Nanchang. The anti-COVID-19 NPIs significantly reduced the incidence of EV infections.

Dynamics of hand, foot and mouth disease in children under 15 years old: A case study of Malaysia using age-structured modelling approach

Hand, foot, and mouth disease (HFMD) is a viral infection that primarily affects children. The disease is characterized by fever, sores in the mouth, and a rash on the hands, feet, and buttocks. In this case study, we analyze the dynamics of HFMD in children under 15 years old in Malaysia using an age-structured modeling approach. First we prove backward bifurcation for a baseline model which is then extended to an age-structured model. We used data on the incidence of HFMD in Malaysia from 2021 to 2022 to calibrate the model parameters and simulate the disease dynamics. Sensitivity analysis is done by Latin hypercube sampling - partial rank correlation coefficient (LHS/PRCC) method. Simulation is done and the impact of imperfect vaccine and quarantine is explored. Our results show that the dynamics of the disease is mostly driven by children under 5 years old. The model also predicts that vaccination could significantly reduce the incidence of HFMD in Malaysia. Vaccination is most effective when targeted at young children, who are at the highest risk of disease as this will lead to drastic decrease in the incidence of HFMD in all age groups. Our simulations show that quarantining of infected children until they fully recover will reduce the transmission of HFMD, but this strategy needs to be sustained for a sufficient duration to have a significant impact. The result of this paper can inform the development of policies for controlling the spread of HFMD and other infectious diseases in Malaysia and other similar settings.

Impact of meteorological factors on the incidence of hand-foot-mouth disease in Yangzhou from 2017 to 2022: a time series study.

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China, and numerous studies have indicated a close association between HFMD incidence and meteorological factors. This study aims to investigate the relationship between meteorological factors and HFMD in Yangzhou City, Jiangsu Province, China. HFMD case reports and meteorological data from Yangzhou City between 2017 and 2022 were extracted from the National Notifiable Infectious Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. A generalized additive model (GAM) was employed to assess the exposure-response relationship between meteorological factors and HFMD. Subsequently, a distributed lag nonlinear model (DLNM) was used to explore the exposure-lag-effect of meteorological factors on HFMD. HFMD in Yangzhou City exhibits obvious seasonality and periodicity. There is an inverted "U" shaped relationship between average temperature and the risk of HFMD, with the maximum lag effect observed at a temperature of 25°C with lag 0 day (RR = 2.07, 95% CI: 1.74-2.47). As the duration of sunshine and relative humidity increase, the risk of HFMD continuously rises, with the maximum lag effect observed at a sunshine duration of 12.4 h with a lag of 14 days (RR = 2.10, 95% CI: 1.17-3.77), and a relative humidity of 28% with a lag of 14 days (RR = 1.21, 95% CI: 1.01-1.64). There is a "U" shaped relationship between average atmospheric pressure and the risk of HFMD, with the maximum effect observed at an atmospheric pressure of 989 hPa with no lag (RR = 1.45, 95% CI: 1.25-1.69). As precipitation increases, the risk of HFMD decreases, with the maximum effect observed at a precipitation of 151 mm with a lag of 14 days (RR = 1.45, 95% CI: 1.19-2.53). Meteorological factors including average temperature, average atmospheric pressure, relative humidity, precipitation, and sunshine duration significantly influenced the risk of HFMD in Yangzhou City. Effective prevention measures for HFMD should be implemented, taking into account the local climate conditions.

The impacts of meteorological factors on the incidence of hand, foot, and mouth disease in China: An interactive perspective

Hand, foot, and mouth disease (HFMD) is a contagious illness and a matter of public health concern globally. It has a widespread impact in China, where it poses a significant risk to the health of young children. Previous research has discovered that the occurrence and spread of HFMD are closely linked to meteorological factors, but the specifics of these intricate nonlinear relationships and how they interact with the incidence of HFMD are still uncertain. In the present study, we filled this gap in knowledge by first obtaining data on hand, foot, and mouth disease from the National Health Commission of China alongside real-time surveillance data from meteorological stations. We then used Spearman's correlation analysis to identify the variables significantly related to HFMD, investigating the existence of co-curvilinearity among the contributing factors by using the independent effects model in the generalized additive model to analyze both the contribution of individual factors and their combined effects on the incidence of HFMD. The interactions between meteorological factors were then modeled to investigate their influence on HFMD. The results showed that, in descending order of effect size, air temperature (AT), sunshine duration (SD), wind speed (WS), and barometric pressure (BP) had a significant nonlinear impact on the incidence of HFMD, which displayed a fluctuating increase in line with rising temperatures. The interactions of (1) high temperature and low air pressure and (2) low wind speed and poor sunshine had the largest influence on HFMD. In descending order, the strengths of the interaction effects between factors were as follows: AT ∼ SD > AT ∼ WS > AT ∼ BP > WS ∼ BP > WS ∼ SD > BP ∼ SD. Our findings will inform policy initiatives contributing to the Healthy China strategy and assist in the prevention and control of HFMD by enabling the prediction and early warning of disease outbreaks.

The Effect of COVID-19 on Infectious Disease to Outpatient of Children: A Machine Learning Study

The outbreak of coronavirus disease 2019 (COVID-19) has had a significant impact worldwide. However, the effects of COVID-19 on human enteroviruses such as Herpangina and Hand, Foot, and Mouth Disease (HFMD) in children are still not fully understood. This study aimed to analyze the reported cases of Herpangina and HFMD among child outpatients in Hangzhou, China, from January 2018 to June 2021, before, during, and after the COVID-19 outbreak. Machine learning approaches were employed to analyze the time series data of Herpangina and HFMD from 2018 to 2019 and predict the trends and seasonal patterns from 2020 to 2021. The seasonal patterns at weekly and monthly levels were compared across the three stages of the COVID-19 outbreak. Prior to 2020, the reported incidence of Herpangina and HFMD exhibited a certain degree of seasonal periodicity. However, following the COVID-19 outbreak in 2020, there was a sharp decrease in the cases of Herpangina and HFMD, followed by a rebound in the first half of 2021. The observed cases reached their highest peak in July 2020, showing a decrease of 93.6% for Herpangina and 96.5% for HFMD compared to the predicted values. These findings indicate that the COVID-19 outbreak had a significant impact on the transmission of Herpangina and HFMD. Therefore, integrated strategies should be implemented to control and prevent the resurgence of Herpangina and HFMD, alongside the effective management of COVID-19.

Dynamic modeling and data fitting of climatic and environmental factors and people's behavior factors on hand, foot, and mouth disease (HFMD) in Shanghai, China

BackgroundHand, foot, and mouth disease (HFMD) appear to be a multi-wave outbreak with unknown mechanisms. We investigate the effects of climatic and environmental factors and changes in people's behavior factors that may be caused by external factors: temperature, relative humidity, and school opening and closing. MethodsDistributed lag nonlinear model (DLNM) and dynamic model are used to research multi-wave outbreaks of HFMD. Climatic and environmental factors impact on transmission rate β(t) is modeled through DLNM and then substituted into this relationship to establish the dynamic model with reported case data to test for validity. ResultsRelative risk (RR) of HFMD infection increases with increasing temperature. The RR of infection first increases and then decreases with the increase of relative humidity. For the model fitting HFMD dynamic, time average basic reproduction number [R0] of Stage I (without vaccine) and Stage II (with EV71 vaccine) are 1.9362 and 1.5478, respectively. Temperature has the highest explanatory power, followed by school opening and closing, and relative humidity. ConclusionWe obtain three conclusions about the prevention and control of HFMD. 1) According to the temperature, relative humidity and school start time, the outbreak peak of HFMD should be warned and targeted prevention and control measures should be taken. 2) Reduce high indoor temperature when more than 31.5 oC, and increase low relative humidity when less than 77.5% by opening the window for ventilation, adding houseplants, using air conditioners and humidifiers, reducing the incidence of HFMD and the number of infections. 3) The risk of HFMD transmission during winter vacations is higher than during summer vacations. It is necessary to strengthen the publicity of HFMD prevention knowledge before winter vacations and strengthen the disinfection control measures during winter vacations in children's hospitals, school classrooms, and other places where children gather to reduce the frequency of staff turnover during winter vacations.

Epidemiological characteristics and spatiotemporal patterns of hand, foot, and mouth disease in Hubei, China from 2009 to 2019.

Hand, foot, and mouth disease (HFMD) is a public health issue in Hubei and studies of- spatiotemporal clustering at a fine scale are limited. The purpose of this research was to analyze the epidemiological characteristics, temporal variation characteristics, and spatiotemporal clustering of HFMD cases at the town level from 2009 to 2019 to improve public health outcomes. Mathematical statistics, a seasonal index, wavelet analysis, and spatiotemporal scans were used to analyze epidemiological characteristics, time series trends, and spatiotemporal clusters of HFMD in Hubei. EV-A71 (Enterovirus A71) and CVA16 (Coxsackievirus A16) constitute the two primary pathogens of the HFMD epidemic in Hubei, among which EV-A71 is the dominant pathogen, especially in 2016. In terms of age distribution, a major peak occurred at 0-5 years and a very small increase appeared at 25-35 years, with the former having a higher incidence among males than females and the latter having the opposite difference between males and females. The number/rate of HFMD cases exhibited a considerable increase followed by a moderate decline from 2009 to 2019, with the first large peak in April-July and a smaller peak in November-December. HFMD in Hubei exhibited the characteristics of a 270-day cycle with multiscale nesting, which was similar to the periodicity of HFMD cases caused by EV-A71 (9 months). Cities with a higher incidence of HFMD formed a part of an "A-shaped urban skeleton". Subdistricts had the highest incidence of HFMD, followed by towns and villages. The spatiotemporal scan results showed one most likely cluster and 22 secondary clusters, which was consistent with the geographic location of railways and rivers in Hubei. These findings may be helpful in the prevention and control of HFMD transmission and in implementing effective measures in Hubei Province.

Combined impacts of environmental and socioeconomic covariates on HFMD risk in China: A spatiotemporal heterogeneous perspective.

Understanding geospatial impacts of multi-sourced influencing factors on the epidemic of hand-foot-and-mouth disease (HFMD) is of great significance for formulating disease control policies tailored to regional-specific needs, yet the knowledge is very limited. We aim to identify and further quantify the spatiotemporal heterogeneous effects of environmental and socioeconomic factors on HFMD dynamics. We collected monthly province-level HFMD incidence and related environmental and socioeconomic data in China during 2009-2018. Hierarchical Bayesian models were constructed to investigate the spatiotemporal relationships between regional HFMD and various covariates: linear and nonlinear effects for environmental covariates, and linear effects for socioeconomic covariates. The spatiotemporal distribution of HFMD cases was highly heterogeneous, indicated by the Lorenz curves and the corresponding Gini indices. The peak time (R2 = 0.65, P = 0.009), annual amplitude (R2 = 0.94, P<0.001), and semi-annual periodicity contribution (R2 = 0.88, P<0.001) displayed marked latitudinal gradients in Central China region. The most likely cluster areas for HFMD were located in south China (Guangdong, Guangxi, Hunan, Hainan) from April 2013 to October 2017. The Bayesian models achieved the best predictive performance (R2 = 0.87, P<0.001). We found significant nonlinear associations between monthly average temperature, relative humidity, normalized difference vegetation index and HFMD transmission. Besides, population density (RR = 1.261; 95%CI, 1.169-1.353), birth rate (RR = 1.058; 95%CI, 1.025-1.090), real GDP per capita (RR = 1.163; 95%CI, 1.033-1.310) and school vacation (RR = 0.507; 95%CI, 0.459-0.559) were identified to have positive or negative effects on HFMD respectively. Our model could successfully predict months with HFMD outbreaks versus non-outbreaks in provinces of China from Jan 2009 to Dec 2018. Our study highlights the importance of refined spatial and temporal data, as well as environmental and socioeconomic information, on HFMD transmission dynamics. The spatiotemporal analysis framework may provide insights into adjusting regional interventions to local conditions and temporal variations in broader natural and social sciences.

Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China

BackgroundThis study adopted complete meteorological indicators, including eight items, to explore their impact on hand, foot, and mouth disease (HFMD) in Fuzhou, and predict the incidence of HFMD through the long short-term memory (LSTM) neural network algorithm of artificial intelligence.MethodA distributed lag nonlinear model (DLNM) was used to analyse the influence of meteorological factors on HFMD in Fuzhou from 2010 to 2021. Then, the numbers of HFMD cases in 2019, 2020 and 2021 were predicted using the LSTM model through multifactor single-step and multistep rolling methods. The root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (SMAPE) were used to evaluate the accuracy of the model predictions.ResultsOverall, the effect of daily precipitation on HFMD was not significant. Low (4 hPa) and high (≥ 21 hPa) daily air pressure difference (PRSD) and low (< 7 °C) and high (> 12 °C) daily air temperature difference (TEMD) were risk factors for HFMD. The RMSE, MAE, MAPE and SMAPE of using the weekly multifactor data to predict the cases of HFMD on the following day, from 2019 to 2021, were lower than those of using the daily multifactor data to predict the cases of HFMD on the following day. In particular, the RMSE, MAE, MAPE and SMAPE of using weekly multifactor data to predict the following week's daily average cases of HFMD were much lower, and similar results were also found in urban and rural areas, which indicating that this approach was more accurate.ConclusionThis study’s LSTM models combined with meteorological factors (excluding PRE) can be used to accurately predict HFMD in Fuzhou, especially the method of predicting the daily average cases of HFMD in the following week using weekly multifactor data.

Tomato flu: need to look beyond the frame

Tomato flu: need to look beyond the frame

Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China

BackgroundThis study aimed to construct a more accurate model to forecast the incidence of hand, foot, and mouth disease (HFMD) in mainland China from January 2008 to December 2019 and to provide a reference for the surveillance and early warning of HFMD.MethodsWe collected data on the incidence of HFMD in mainland China between January 2008 and December 2019. The SARIMA, SARIMA-BPNN, and SARIMA-PSO-BPNN hybrid models were used to predict the incidence of HFMD. The prediction performance was compared using the mean absolute error(MAE), mean squared error(MSE), root mean square error (RMSE), mean absolute percentage error (MAPE), and correlation analysis.ResultsThe incidence of HFMD in mainland China from January 2008 to December 2019 showed fluctuating downward trends with clear seasonality and periodicity. The optimal SARIMA model was SARIMA(1,0,1)(2,1,2)[12], with Akaike information criterion (AIC) and Bayesian Schwarz information criterion (BIC) values of this model were 638.72, 661.02, respectively. The optimal SARIMA-BPNN hybrid model was a 3-layer BPNN neural network with nodes of 1, 10, and 1 in the input, hidden, and output layers, and the R-squared, MAE, and RMSE values were 0.78, 3.30, and 4.15, respectively.For the optimal SARIMA-PSO-BPNN hybrid model, the number of particles is 10, the acceleration coefficients c1 and c2 are both 1, the inertia weight is 1, the probability of change is 0.95, and the values of R-squared, MAE, and RMSE are 0.86, 2.89, and 3.57, respectively.ConclusionsCompared with the SARIMA and SARIMA-BPNN hybrid models, the SARIMA-PSO-BPNN model can effectively forecast the change in observed HFMD incidence, which can serve as a reference for the prevention and control of HFMD.

Associations between ambient air pollutants and childhood hand, foot, and mouth disease in Sichuan, China: a spatiotemporal study

Hand, foot, and mouth disease (HFMD) is a major public health concern in the Asia–Pacific region. Previous studies have implied that ambient air pollution may affect the incidence of HFMD, but the results among different regions are inconsistent. We aimed to deepen the understanding of the associations between air pollutants and HFMD by conducting a multicity study. Daily data on childhood HFMD counts and meteorological and ambient air pollution (PM2.5, PM10, NO2, CO, O3, and SO2) concentrations in 21 cities in Sichuan Province from 2015 to 2017 were collected. A spatiotemporal Bayesian hierarchical model framework was established, and then a distributed lag nonlinear models (DLNMs) was constructed to reveal exposure-lag-response relationships between air pollutants and HFMD while controlling for spatiotemporal effects. Furthermore, given the differences in the levels and seasonal trends of air pollutants between the basin region and plateau region, we explored whether these associations varied between different areas (basin and plateau). The associations between air pollutants and HFMD were nonlinear, with different lag responses. Low NO2 concentrations and both low and high PM2.5 and PM10 concentrations were associated with a decreased risk of HFMD. No significant associations between CO, O3, and SO2 and HFMD were found. The associations between air pollutant concentrations and HFMD were different between the basin and plateau regions. Our study revealed associations between PM2.5, PM10, and NO2 concentrations and HFMD, deepening the understanding of the relationships between air pollutants and HFMD. These findings provide evidence to support the formulation of relevant prevention measures and the establishment of an early warning system.

Analysis of a SARIMA-XGBoost model for hand, foot, and mouth disease in Xinjiang, China.

Hand, foot, and mouth disease (HFMD) is a common childhood infectious disease. The incidence of HFMD has a pronounced seasonal tendency and is closely related to meteorological factors such as temperature, rainfall, and wind speed. In this paper, we propose a combined SARIMA-XGBoost model to improve the prediction accuracy of HFMD in 15 regions of Xinjiang, China. The SARIMA model is used for seasonal trends, and the XGBoost algorithm is applied for the nonlinear effects of meteorological factors. The geographical and temporal weighted regression model is designed to analyze the influence of meteorological factors from temporal and spatial perspectives. The analysis results show that the HFMD exhibits seasonal characteristics, peaking from May to August each year, and the HFMD incidence has significant spatial heterogeneity. The meteorological factors affecting the spread of HFMD vary among regions. Temperature and daylight significantly impact the transmission of the disease in most areas. Based on the verification experiment of forecasting, the proposed SARIMA-XGBoost model is superior to other models in accuracy, especially in regions with a high incidence of HFMD.

Effects of different levels of non-pharmaceutical interventions on hand, foot and mouth disease in Guangzhou, China

BackgroundNon-pharmaceutical interventions (NPIs) against coronavirus disease 2019 (COVID-19) may have suppressed the transmission of other infectious diseases. This study aimed to evaluate the impact of different degrees of NPIs during the COVID-19 pandemic on hand, foot and mouth disease (HFMD) in Guangzhou, China.MethodsWeekly reported HFMD cases and pathogens information during 2015–2021 in Guangzhou were collected from the China National Notifiable Disease Reporting System. The observed number of HFMD cases in 2020 and 2021 was compared to the average level in the same period during 2015–2019. Then, an interrupted time-series segmented regression analysis was applied to estimate the impact of NPIs on HFMD, such as social distancing, suspension of schools, community management and mask wearing. The effects across different subgroups stratified by gender, children groups and enterovirus subtype of HFMD were also examined.ResultsA total of 13,224 and 36,353 HFMD cases were reported in 2020 and 2021, which decreased by 80.80% and 15.06% respectively compared with the average number of cases in the same period during 2015–2019. A significant drop in the number of HFMD cases during time when strict NPIs were applied (relative change: 69.07% [95% confidence interval (CI): 68.84%–69.30%]). The HFMD incidence rebounded to historical levels in 2021 as the lockdown eased. The slightest reduction of HFMD cases was found among children at kindergartens or childcare centres among the three children groups (children at kindergartens or childcare centres: 55.50% [95% CI: 54.96%–56.03%]; children living at home: 72.64% [95% CI: 72.38%–72.89%]; others: 74.06% [95% CI: 73.19%–74.91%]).ConclusionsThe strong NPIs during the COVID-19 epidemic may have a significant beneficial effect on mitigating HFMD. However, the incidence of HFMD rebounded as the NPIs became less stringent. Authorities should consider applying these NPIs during HFMD outbreaks and strengthening personal hygiene in routine prevention.

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.