scholarly journals Trend analysis and forecast of daily reported incidence of hand, foot and mouth disease in Hubei, China by Prophet model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Cong Xie ◽  
Haoyu Wen ◽  
Wenwen Yang ◽  
Jing Cai ◽  
Peng Zhang ◽  
...  
Keyword(s):  
Moving Average ◽  
Arima Model ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Spring Festival ◽  
High Incidence ◽  
Foot And Mouth ◽  
Accurate Forecast ◽  
Changing Patterns ◽  
Two Peaks

AbstractHand, foot, and mouth disease (HFMD) is common among children below 5 years. HFMD has a high incidence in Hubei Province, China. In this study, the Prophet model was used to forecast the incidence of HFMD in comparison with the autoregressive-integrated moving average (ARIMA) model, and HFMD incidence was decomposed into trends, yearly, weekly seasonality and holiday effect. The Prophet model fitted better than the ARIMA model in daily reported incidence of HFMD. The HFMD incidence forecast by the Prophet model showed that two peaks occurred in 2019, with the higher peak in May and the lower peak in December. Periodically changing patterns of HFMD incidence were observed after decomposing the time-series into its major components. In specific, multi-year variability of HFMD incidence was found, and the slow-down increasing point of HFMD incidence was identified. Relatively high HFMD incidences appeared in May and on Mondays. The effect of Spring Festival on HFMD incidence was much stronger than that of other holidays. This study showed the potential of the Prophet model to detect seasonality in HFMD incidence. Our next goal is to incorporate climate variables into the Prophet model to produce an accurate forecast of HFMD incidence.

scholarly journals Time-series modelling and forecasting of hand, foot and mouth disease cases in China from 2008 to 2018

2019 ◽  
Vol 147 ◽  
Author(s):  
C. W. Tian ◽  
H. Wang ◽  
X. M. Luo
Keyword(s):  
Time Series ◽  
Seasonal Variation ◽  
Moving Average ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Sarima Model ◽  
Autoregressive Integrated Moving Average ◽  
Annual Peak ◽  
Time Series Modelling ◽  
Foot And Mouth

AbstractSeasonal autoregressive-integrated moving average (SARIMA) has been widely used to model and forecast incidence of infectious diseases in time-series analysis. This study aimed to model and forecast monthly cases of hand, foot and mouth disease (HFMD) in China. Monthly incidence HFMD cases in China from May 2008 to August 2018 were analysed with the SARIMA model. A seasonal variation of HFMD incidence was found from May 2008 to August 2018 in China, with a predominant peak from April to July and a trough from January to March. In addition, the annual peak occurred periodically with a large annual peak followed by a relatively small annual peak. A SARIMA model of SARIMA (1, 1, 2) (0, 1, 1)12 was identified, and the mean error rate and determination coefficient were 16.86% and 94.27%, respectively. There was an annual periodicity and seasonal variation of HFMD incidence in China, which could be predicted well by a SARIMA (1, 1, 2) (0, 1, 1)12 model.

scholarly journals Forecasting incidence of hand, foot and mouth disease using BP neural networks in Jiangsu province, China

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Wendong Liu ◽  
Changjun Bao ◽  
Yuping Zhou ◽  
Hong Ji ◽  
Ying Wu ◽  
...  
Keyword(s):  
Public Health ◽  
Neural Networks ◽  
Meteorological Factors ◽  
Arima Model ◽  
Foot And Mouth Disease ◽  
Public Health Problem ◽  
Mouth Disease ◽  
Jiangsu Province ◽  
Foot And Mouth ◽  
Bp Model

Abstract Background Hand, foot and mouth disease (HFMD) is a rising public health problem and has attracted considerable attention worldwide. The purpose of this study was to develop an optimal model with meteorological factors to predict the epidemic of HFMD. Methods Two types of methods, back propagation neural networks (BP) and auto-regressive integrated moving average (ARIMA), were employed to develop forecasting models, based on the monthly HFMD incidences and meteorological factors during 2009–2016 in Jiangsu province, China. Root mean square error (RMSE) and mean absolute percentage error (MAPE) were employed to select model and evaluate the performance of the models. Results Four models were constructed. The multivariate BP model was constructed using the HFMD incidences lagged from 1 to 4 months, mean temperature, rainfall and their one order lagged terms as inputs. The other BP model was fitted just using the lagged HFMD incidences as inputs. The univariate ARIMA model was specified as ARIMA (1,0,1)(1,1,0)12 (AIC = 1132.12, BIC = 1440.43). And the multivariate ARIMAX with one order lagged temperature as external predictor was fitted based on this ARIMA model (AIC = 1132.37, BIC = 1142.76). The multivariate BP model performed the best in both model fitting stage and prospective forecasting stage, with a MAPE no more than 20%. The performance of the multivariate ARIMAX model was similar to that of the univariate ARIMA model. Both performed much worse than the two BP models, with a high MAPE near to 40%. Conclusion The multivariate BP model effectively integrated the autocorrelation of the HFMD incidence series. Meanwhile, it also comprehensively combined the climatic variables and their hysteresis effects. The introduction of the climate terms significantly improved the prediction accuracy of the BP model. This model could be an ideal method to predict the epidemic level of HFMD, which is of great importance for the public health authorities.

scholarly journals Spatiotemporal Characteristics and meteorological determinants of Hand, Foot and Mouth Disease in Shaanxi Province, China: a county-level analysis

2021 ◽  
Author(s):  
Li Ding ◽  
Ning Zhang ◽  
Bin Zhu ◽  
Jinlin Liu ◽  
Xue Wang ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Meteorological Factors ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Shaanxi Province ◽  
County Level ◽  
Spatiotemporal Characteristics ◽  
High Incidence ◽  
Foot And Mouth ◽  
The Government

Abstract 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.

Predicting the incidence of hand, foot and mouth disease in Sichuan province, China using the ARIMA model

2015 ◽  
Vol 144 (1) ◽  
pp. 144-151 ◽  
Author(s):  
L. LIU ◽  
R. S. LUAN ◽  
F. YIN ◽  
X. P. ZHU ◽  
Q. LÜ
Keyword(s):  
Goodness Of Fit ◽  
Arima Model ◽  
Foot And Mouth Disease ◽  
Information Criterion ◽  
Sichuan Province ◽  
Mouth Disease ◽  
Control Measures ◽  
Coefficient Of Determination ◽  
Goodness Of Fit Test ◽  
Foot And Mouth

SUMMARYHand, foot and mouth disease (HFMD) is an infectious disease caused by enteroviruses, which usually occurs in children aged <5 years. In China, the HFMD situation is worsening, with increasing number of cases nationwide. Therefore, monitoring and predicting HFMD incidence are urgently needed to make control measures more effective. In this study, we applied an autoregressive integrated moving average (ARIMA) model to forecast HFMD incidence in Sichuan province, China. HFMD infection data from January 2010 to June 2014 were used to fit the ARIMA model. The coefficient of determination (R2), normalized Bayesian Information Criterion (BIC) and mean absolute percentage of error (MAPE) were used to evaluate the goodness-of-fit of the constructed models. The fitted ARIMA model was applied to forecast the incidence of HMFD from April to June 2014. The goodness-of-fit test generated the optimum general multiplicative seasonal ARIMA (1,0,1) × (0,1,0)12 model (R2 = 0·692, MAPE = 15·982, BIC = 5·265), which also showed non-significant autocorrelations in the residuals of the model (P = 0·893). The forecast incidence values of the ARIMA (1,0,1) × (0,1,0)12 model from July to December 2014 were 4103–9987, which were proximate forecasts. The ARIMA model could be applied to forecast HMFD incidence trend and provide support for HMFD prevention and control. Further observations should be carried out continually into the time sequence, and the parameters of the models could be adjusted because HMFD incidence will not be absolutely stationary in the future.

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

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li Ding ◽  
Ning Zhang ◽  
Bin Zhu ◽  
Jinlin Liu ◽  
Xue Wang ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Meteorological Factors ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Shaanxi Province ◽  
County Level ◽  
Spatiotemporal Characteristics ◽  
High Incidence ◽  
Foot And Mouth ◽  
The Government

Abstract 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.

scholarly journals Clinical and Etiological Characteristics of Atypical Hand-Foot-and-Mouth Disease in Children from Chongqing, China: A Retrospective Study

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Xiang Yan ◽  
Zhen-Zhen Zhang ◽  
Zhen-Hua Yang ◽  
Chao-Min Zhu ◽  
Yun-Ge Hu ◽  
...  
Keyword(s):  
Enterovirus 71 ◽  
Foot And Mouth Disease ◽  
Good Prognosis ◽  
Mouth Disease ◽  
Coxsackievirus A16 ◽  
Neurologic Involvement ◽  
Coxsackievirus A6 ◽  
Foot And Mouth ◽  
Two Peaks ◽  
Epidemiological Characteristics

Background. Hand-foot-and-mouth disease (HFMD) is a disease that had similar manifestations to chickenpox, impetigo, and measles, which is easy to misdiagnose and subsequently causes delayed therapy and subsequent epidemic. To date, no study has been conducted to report the clinical and epidemiological characteristics of atypical HFMD.Methods. 64 children with atypical HFMD out of 887 HFMD children were recruited, stool was collected, and viral VP1 was detected.Results. The atypical HFMD accounted for 7.2% of total HFMD in the same period (64/887) and there were two peaks in its prevalence in nonepidemic seasons. Ten children (15.6%) had manifestations of neurologic involvement, of whom 4 (6.3%) were diagnosed with severe HFMD and 1 with critically severe HFMD, but all recovered smoothly. Onychomadesis and desquamation were found in 14 patients (21.9%) and 15 patients (23.4%), respectively. The most common pathogen was coxsackievirus A6 (CV-A6) which accounted for 67.2%, followed by nontypable enterovirus (26.6%), enterovirus 71 (EV-A71) (4.7%), and coxsackievirus A16 (A16) (1.5%).Conclusions. Atypical HFMD has seasonal prevalence. The manifestations of neurologic involvement in atypical HFMD are mild and usually have a good prognosis. CV-A6 is a major pathogen causing atypical HFMD, but not a major pathogen in Chongqing, China.

scholarly journals Forecasting Hand-Foot-and-Mouth Disease Cases Using a Wavelet-based SARIMA-NNAR Hybrid Model

2020 ◽  
Author(s):  
Gongchao Yu ◽  
Huifen Feng ◽  
Shuang Feng ◽  
Jing Zhao ◽  
Jing Xu
Keyword(s):  
Time Series ◽  
Hybrid Model ◽  
Prevention And Control ◽  
Moving Average ◽  
Foot And Mouth Disease ◽  
Hybrid Models ◽  
Mouth Disease ◽  
High Morbidity ◽  
Foot And Mouth ◽  
And Control

Abstract Background: Hand-foot-and-mouth disease(HFMD) is one of the most common diseases in children, which has high morbidity. Reliable forecasting is significant for prevention and control. Recently, hybrid models have been becoming popular and wavelet analysis has been widely used. Better prediction accuracy may be achieved with wavelet-based hybrid models. Thus, our aim is to forecast number of HFMD cases with wavelet-based hybrid models.Materials and methods: We fitted a wavelet-based SARIMA(seasonal autoregressive integrated moving average)-NNAR(neural network nonlinear autoregressive) hybrid model with HFMD weekly cases from 2009 to 2016 in Zhengzhou, China. At the same time, single SARIMA model, simplex NNAR model and pure SARIMA-NNAR hybrid model were established as well for comparison and estimation.Results: The wavelet-based SARIMA-NNAR hybrid model had an excellent performance whether in fitting or in forecasting compared to other models. Its fitted and forecasting time series were approximate to the actual observed time series.Conclusions: This wavelet-based SARIMA-NNAR hybrid model that we fitted is suitable for forecasting number of HFMD cases. It will facilitate prevention and control of HFMD.

scholarly journals Transmissibility of hand, foot, and mouth disease in 97 counties of China.

2021 ◽  
Author(s):  
Wei Zhang ◽  
Jia Rui ◽  
Xiaoqing Cheng ◽  
Bin Deng ◽  
Hesong Zhang ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Jiangsu Province ◽  
Asia Pacific ◽  
Seasonal Characteristics ◽  
High Incidence ◽  
Foot And Mouth ◽  
Low Incidence ◽  
Serious Disease

Abstract Background Hand, foot, and mouth disease (HFMD) has been a serious disease burden in the Asia Pacific region represented by China, and the transmission characteristics of HFMD in regions haven’t been clear. This study calculated the transmissibility of HFMD at county levels in Jiangsu Province, China, analyzed the differences of transmissibility and explored the reasons. Methods We built susceptible-exposed-infectious-asymptomatic-removed (SEIAR) model for seasonal characteristics of HFMD, estimated effective reproduction number (Reff) by fitting the incidence of HFMD in 97 counties of Jiangsu Province from 2015 to 2020, compared incidence rate and transmissibility in different counties by non -parametric test, rapid cluster analysis and rank-sum ratio. Results The average daily incidence rate was between 0 and 4 per 100,000 in Jiangsu province from 2015–2020. The 97 counties could be divided into three levels: low incidence, medium incidence and high incidence, and occurred that the average daily incidence rate dropped sharply in 2016–2017, and increased sharply in 2017–2018 years. The Quartile of Reff in Jiangsu Province from 2015 to 2020 was 1.54 (0.49, 2.50), Rugao district in Central Jiangsu and Jianhu district in Northern Jiangsu had the highest transmissibility by rank-sum ratio. Reff generally decreased in 2017 and increased in 2018 in most counties, and the median level of Reff was lowest in 2017 (P < 0.05). Conclusion Transmissibility was different in 97 counties of Jiangsu Province, and the reasons for the differences may be related to the climate, demographic characteristics, virus subtypes, vaccination and other infectious diseases.

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