ArticlePloS one2021
Forecasting hand-foot-and-mouth disease cases using wavelet-based SARIMA-NNAR hybrid model.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Weighted ensemble learning outperforms statistical, machine-learning, and deep-learning models for varicella forecasting: a 12-model benchmarking study using 11-year surveillance data from Nanjing, China.Frontiers in public health · 2026Article
- Prediction of pulmonary tuberculosis case trends among older adults in Chongqing based on time series models.Frontiers in public health · 2026Article
- Multiple change point analysis and time series forecast of brucellosis reports in Xinjiang, China from 2010 to 2024.BMC public health · 2025Article
- Modeling and Forecasting Dead-on-Arrival in Broilers Using Time Series Methods: A Case Study from Thailand.Animals : an open access journal from MDPI · 2025Article
- Incidence of acute hemorrhagic conjunctivitis in Chongqing: a forecasting study based on mathematical models.Frontiers in public health · 2025Article
- Article
- Spatial Distribution Analysis and Comparative Forecasting of Dengue Resurgence in the Philippines (2025-2027): A Nationwide Study.Transboundary and emerging diseases · 2025Article
- Trends and multi-model prediction of hepatitis B incidence in Xiamen.Infectious Disease Modelling · 2024Article
- Estimating the Temporal Epidemiological Trends of Tuberculosis Incidence by Using an Advanced Theta Method.The American journal of tropical medicine and hygiene · 2024Article
- Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China.BMC public health · 2023Article
- Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study.BMC infectious diseases · 2022Article
- Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy.The European journal of health economics : HEPAC : health economics in prevention and care · 2022Article
- Innovation Strategy of Cultivating Innovative Enterprise Talents for Young Entrepreneurs Under Higher Education.Frontiers in psychology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHand-foot-and-mouth disease_(HFMD) is one of the most typical diseases in children that is associated with high morbidity. Reliable forecasting is crucial for prevention and control. Recently, hybrid models have become popular, and wavelet analysis has been widely performed. Better prediction accuracy may be achieved using wavelet-based hybrid models. Thus, our aim is to forecast number of HFMD cases with wavelet-based hybrid models. MATERIALS AND
methodsWe fitted a wavelet-based seasonal autoregressive integrated moving average (SARIMA)-neural network nonlinear autoregressive (NNAR) hybrid model with HFMD weekly cases from 2009 to 2016 in Zhengzhou, China. Additionally, a single SARIMA model, simplex NNAR model, and pure SARIMA-NNAR hybrid model were established for comparison and estimation.
resultsThe wavelet-based SARIMA-NNAR hybrid model demonstrates excellent performance whether in fitting or forecasting compared with other models. Its fitted and forecasting time series are similar to the actual observed time series.
conclusionsThe wavelet-based SARIMA-NNAR hybrid model fitted in this study is suitable for forecasting the number of HFMD cases. Hence, it will facilitate the prevention and control of HFMD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.