Predicting Seasonal Influenza Based on Sarima Model, in Mainland China from 2005 to 2018
Bibliographic Data
| ID | 15497152 |
|---|---|
| Authors | Jing Cong (0009-0001-5624-4157, Binzhou Medical University), Mengmeng Ren (0000-0001-8124-6915, Binzhou Medical University), Shuyang Xie (0000-0002-8090-2180, Binzhou Medical University), Pingyu Wang (0000-0003-0980-4294, Binzhou University, corresponding author) |
| Year | 2019 |
| Volume | 16 |
| Issue | 23 |
| Pages | 4760-4760 |
| Publication date | 2019-11-27 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph16234760 |
| PMID | 31783697 |
| OpenAlex | W2990268217 |
| Language | EN |
| Citations received | 6 |
| References cited | 26 |
Seasonal influenza is one of the mandatorily monitored infectious diseases, in China. Making full use of the influenza surveillance data helps to predict seasonal influenza. In this study, a seasonal autoregressive integrated moving average (SARIMA) model was used to predict the influenza changes by analyzing monthly data of influenza incidence from January 2005 to December 2018, in China. The inter-annual incidence rate fluctuated from 2.76 to 55.07 per 100,000 individuals. The SARIMA (1, 0, 0) × (0, 1, 1) 12 model predicted that the influenza incidence in 2018 was similar to that of previous years, and it fitted the seasonal fluctuation. The relative errors between actual values and predicted values fluctuated from 0.0010 to 0.0137, which indicated that the predicted values matched the actual values well. This study demonstrated that the SARIMA model could effectively make short-term predictions of seasonal influenza
Autoregressive integrated moving average · China · Coronavirus disease 2019 (COVID-19 · Geography · Incidence (geometry · Infectious disease (medical specialty · Mainland China · Seasonal influenza · Seasonality · Statistics · Time series · Animal Disease Management and Epidemiology · COVID-19 epidemiological studies · Demography · Environmental Science · Influenza Virus Research Studies · Mathematics · Medicine · Internal Medicine
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| Citations per year | 1 |
|---|---|
| Citation span | 2020 - 2024 (5) |
| Highly cited | No |