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 Parameter-dependent transmission dynamics and optimal control of foot and mouth disease in a contaminated environment

2019 ◽  
Vol 27 (1) ◽  
Author(s):  
Francis Mugabi ◽  
Joseph Mugisha ◽  
Betty Nannyonga ◽  
Henry Kasumba ◽  
Margaret Tusiime
Keyword(s):  
Optimal Control ◽  
Deterministic Model ◽  
Foot And Mouth Disease ◽  
Decay Rates ◽  
Mouth Disease ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Optimality System ◽  
Foot And Mouth ◽  
Environmental Decontamination

AbstractThe problem of foot and mouth disease (FMD) is of serious concern to the livestock sector in most nations, especially in developing countries. This paper presents the formulation and analysis of a deterministic model for the transmission dynamics of FMD through a contaminated environment. It is shown that the key parameters that drive the transmission of FMD in a contaminated environment are the shedding, transmission, and decay rates of the virus. Using numerical results, it is depicted that the host-to-host route is more severe than the environmental-to-host route. The model is then transformed into an optimal control problem. Using the Pontryagin’s Maximum Principle, the optimality system is determined. Utilizing a gradient type algorithm with projection, the optimality system is solved for three control strategies: optimal use of vaccination, environmental decontamination, and a combination of vaccination and environmental decontamination. Results show that a combination of vaccination and environmental decontamination is the most optimal strategy. These results indicate that if vaccination and environmental decontamination are used optimally during an outbreak, then FMD transmission can be controlled. Future studies focusing on the control measures for the transmission of FMD in a contaminated environment should aim at reducing the transmission and the shedding rates, while increasing the decay rate.

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 Association between meteorological factors and reported cases of hand, foot, and mouth disease from 2000 to 2015 in Japan

2017 ◽  
Vol 145 (14) ◽  
pp. 2896-2911 ◽  
Author(s):  
A. SUMI ◽  
S. TOYODA ◽  
K. KANOU ◽  
T. FUJIMOTO ◽  
K. MISE ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Foot And Mouth Disease ◽  
Entropy Method ◽  
Temperature Data ◽  
Mouth Disease ◽  
Lower Threshold ◽  
Control Measures ◽  
Temperature Threshold ◽  
Average Temperature ◽  
Foot And Mouth

SUMMARYThe purpose of this study was to clarify the association between hand, foot, and mouth disease (HFMD) epidemics and meteorological conditions. We used HFMD surveillance data of all 47 prefectures in Japan from January 2000 to December 2015. Spectral analysis was performed using the maximum entropy method (MEM) for temperature-, relative humidity-, and total rainfall-dependent incidence data. Using MEM-estimated periods, long-term oscillatory trends were calculated using the least squares fitting (LSF) method. The temperature and relative humidity thresholds of HFMD data were estimated from the LSF curves. The average temperature data indicated a lower threshold at 12 °C and a higher threshold at 30 °C for risk of HFMD infection. Maximum and minimum temperature data indicated a lower threshold at 6 °C and a higher threshold at 35 °C, suggesting a need for HFMD control measures at temperatures between 6 and 35 °C. Based on our findings, we recommend the use of maximum and minimum temperatures rather than the average temperature, to estimate the temperature threshold of HFMD infections. The results obtained might aid in the prediction of epidemics and preparation for the effect of climatic changes on HFMD epidemiology.

scholarly journals The Effectiveness of a Foot and Mouth Disease Outbreak Control Programme in Thailand 2008–2015: Case Studies and Lessons Learned

2018 ◽  
Vol 5 (4) ◽  
pp. 101 ◽  
Author(s):  
Terdsak Yano ◽  
Sith Premashthira ◽  
Tosapol Dejyong ◽  
Sahatchai Tangtrongsup ◽  
Mo D. Salman
Keyword(s):  
Prevention And Control ◽  
Animal Movement ◽  
Foot And Mouth Disease ◽  
Control Programme ◽  
Mouth Disease ◽  
Lessons Learned ◽  
Control Measures ◽  
Prevention Measures ◽  
Foot And Mouth ◽  
And Control

Three Foot and Mouth Disease (FMD) outbreaks in northern Thailand that occurred during the implementation of the national FMD strategic plan in 2008–2015 are described to illustrate the lessons learned and to improve the prevention and control of future outbreaks. In 2008, during a FMD outbreak on a dairy farm, milk delivery was banned for 30 days. This was a part of movement management, a key strategy for FMD control in dairy farms in the area. In 2009, more than half the animals on a pig farm were affected by FMD. Animal quarantine and restricted animal movement played a key role in preventing the spread of FMD. In 2010, FMD infection was reported in a captive elephant. The suspected source of virus was a FMD-infected cow on the same premises. The infected elephant was moved to an elephant hospital that was located in a different province before the diagnosis was confirmed. FMD education was given to elephant veterinarians to promote FMD prevention and control strategies in this unique species. These three cases illustrate how differences in outbreak circumstances and species require the implementation of a variety of different FMD control and prevention measures. Control measures and responses should be customized in different outbreak situations.

scholarly journals Evaluation of Quality Control Methods for Foot-And-Mouth Disease Vaccines by High-Performance Liquid Chromatography

Pathogens ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 194
Author(s):  
Mun-Hyeon Kim ◽  
Seon-Jong Yun ◽  
Yeon-Hee Kim ◽  
Hyang-Sim Lee ◽  
Ji-Yeon Kim ◽  
...  
Keyword(s):  
Quality Control ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
High Performance ◽  
Foot And Mouth Disease ◽  
Reference Method ◽  
Mouth Disease ◽  
Control Measures ◽  
Standard Material ◽  
Foot And Mouth

Foot-and-mouth disease (FMD) is considered one of the highly contagious viral infections affecting livestock. In Korea, an FMD vaccination policy has been implemented nationwide since 2010 for the prevention and control of FMD. Since the vaccines are imported from various countries, standardized quality control measures are critical. In this study, we aimed to validate a high-performance liquid chromatography (HPLC) device in the Animal and Plant Quarantine Agency lab and identify an appropriate FMD vaccine pretreatment method for HPLC—a simple, reliable, and practical method to measure antigen content. Based on the analyses of specificity, linearity, accuracy, repeatability, intermediate precision, limits of detection, and limits of quantification using FMD standard samples, we validated the method using a standard material. Overall, we confirmed that the HPLC technique is effective for the quantitative assessment of the FMD virus 146S antigen in Korea. Using commercial FMD vaccines, we evaluated three separation methods and identified the method using n-pentanol and trichloroethylene as optimal for HPLC analysis. Our HPLC method was effective for the analytical detection of the antigen content in FMD vaccine, and it may be useful as a reference method for national lot-release testing.

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.

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