ArticleScientific reports2019
A method for hand-foot-mouth disease prediction using GeoDetector and LSTM model in Guangxi, China.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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30 citing papers in PubMed, 76 citations in OpenAlex.
- Epidemiological characteristics and spatiotemporal analysis of hand-foot-mouth disease in Shandong Province, China.International health · 2026Article
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- Zoonotic outbreak risk prediction with long short-term memory models: a case study with schistosomiasis, echinococcosis, and leptospirosis.BMC infectious diseases · 2024Article
- Dual-attention-based recurrent neural network for hand-foot-mouth disease prediction in Korea.Scientific reports · 2023Article
- Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China.BMC infectious diseases · 2023Article
- Forecasting upper respiratory tract infection burden using high-dimensional time series data and forecast combinations.PLoS computational biology · 2023Article
- Prediction of outpatients with conjunctivitis in Xinjiang based on LSTM and GRU models.PloS one · 2023Article
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- A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.International journal of environmental research and public health · 2022Article
- Study on the influence of meteorological factors on influenza in different regions and predictions based on an LSTM algorithm.BMC public health · 2022Article
- Forecasting of non-accidental, cardiovascular, and respiratory mortality with environmental exposures adopting machine learning approaches.Environmental science and pollution research international · 2022Article
- Comparison of ARIMA model, DNN model and LSTM model in predicting disease burden of occupational pneumoconiosis in Tianjin, China.BMC public health · 2022Article
- A multivariate multi-step LSTM forecasting model for tuberculosis incidence with model explanation in Liaoning Province, China.BMC infectious diseases · 2022Article
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- Effectiveness of cascading time series models based on meteorological factors in improving health risk prediction.Environmental science and pollution research international · 2022Article
- Predicting the Number of Reported Pulmonary Tuberculosis in Guiyang, China, Based on Time Series Analysis Techniques.Computational and mathematical methods in medicine · 2022Article
- Comparison of ARIMA and LSTM for prediction of hemorrhagic fever at different time scales in China.PloS one · 2022Article
- Deep learning time series prediction models in surveillance data of hepatitis incidence in China.PloS one · 2022Article
- Spatio-temporal stratified associations between urban human activities and crime patterns: a case study in San Francisco around the COVID-19 stay-at-home mandate.Computational urban science · 2022Article
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Authors and funding
10 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Hand-foot-mouth disease (HFMD) is a common infectious disease in children and is particularly severe in Guangxi, China. Meteorological conditions are known to play a pivotal role in the HFMD. Previous studies have reported numerous models to predict the incidence of HFMD. In this study, we proposed a new method for the HFMD prediction using GeoDetector and a Long Short-Term Memory neural network (LSTM). The daily meteorological factors and HFMD records in Guangxi during 2014-2015 were adopted. First, potential risk factors for the occurrence of HFMD were identified based on the GeoDetector. Then, region-specific prediction models were developed in 14 administrative regions of Guangxi, China using an optimized three-layer LSTM model. Prediction results (the R-square ranges from 0.39 to 0.71) showed that the model proposed in this study had a good performance in HFMD predictions. This model could provide support for the prevention and control of HFMD. Moreover, this model could also be extended to the time series prediction of other infectious diseases.
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