Predicting the outbreak of hand, foot, and mouth disease in Nanjing, China: a time-series model based on weather variability

Abstract

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China and an accurate prediction of epidemic can improve the effectiveness of HFMD control. This study aims to develop a weather-based forecasting model for HFMD using the information on climatic variables and HFMD surveillance in Nanjing, China. Daily data on HFMD cases and meteorological variables between 2010 and 2015 were acquired from the Nanjing Center for Disease Control and Prevention, and China Meteorological Data Sharing Service System, respectively. A multivariate seasonal autoregressive integrated moving average (SARIMA) model was developed and validated by dividing HFMD infection data into two datasets: the data from 2010 to 2013 were used to construct a model and those from 2014 to 2015 were used to validate it. Moreover, we used weekly prediction for the data between 1 January 2014 and 31 December 2015 and leave-1-week-out prediction was used to validate the performance of model prediction. SARIMA (2,0,0) associated with the average temperature at lag of 1 week appeared to be the best model (R = 0.936, BIC = 8.465), which also showed non-significant autocorrelations in the residuals of the model. In the validation of the constructed model, the predicted values matched the observed values reasonably well between 2014 and 2015. There was a high agreement rate between the predicted values and the observed values (sensitivity 80%, specificity 96.63%). This study suggests that the SARIMA model with average temperature could be used as an important tool for early detection and prediction of HFMD outbreaks in Nanjing, China.

Forecasting hand, foot, and mouth disease in Shenzhen based on daily level clinical data and multiple environmental factors

“…Many researchers used data collected from the surveillance system to develop an early warning system of HFMD to lower the damage caused by a HFMD outbreak. A study by Nanjing Medical University attempted to predict the HFMD epidemics in Nanjing city, the main epidemic area of eastern China, by developing a weather-based forecasting model (6). A research team from Beijing explored the data collected in Beijing to find seasonal and other potential effects of weather factors on HFMD (7).…”

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

“…For example, Liu et al . found high agreement between predicted values of HFMD based on trends from 2010 to 2013 in Nanjing, China, and observed values in 2014–2015 (sensitivity 80%, specificity 96.63%) . Combining these data with known infectivity periods may strengthen infection control measures.…”

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

“…Due to the seasonality, value of 1 was set to P. Along with automatic selection as (6,1,4) 52 by "nnetar" function, we also tried different p values from one to ten (Table 1). Taking into consideration three indices of performance both in training set and validation set, we finally selected NNAR (8,1,5) 52 as the optimal model. The residuals was displayed in Fig.4.…”

“…Many scholars used all kinds of models to forecast the incidence of HFMD. Among these models, the traditional ARIMA model is utilized widely [7][8][9]. Linearity is the necessary condition of its application.…”