Epidemiological and clinical characteristics of influenza patients in respiratory department under the prediction of autoregressive integrated moving average model
| Autor: | Jing Yuan, Dan Li |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Epidemiological distribution characteristics Fitting prediction Physics QC1-999 General Physics and Astronomy virus diseases Biology Elman neural network model Autoregressive integrated moving average model Influenza respiratory tract diseases Age and gender Epidemiology Statistics medicine Autoregressive integrated moving average |
| Zdroj: | Results in Physics, Vol 24, Iss, Pp 104070-(2021) |
| ISSN: | 2211-3797 |
| Popis: | This study was to explore the epidemiological distribution characteristics and future development trends of influenza-like illness (ILI) by autoregressive integrated moving average model (ARIMA). The information on ILI in the hospital from January 2016 to August 2020 was collected in this study. Firstly, the differences in distribution of different virus subtypes, the distribution of epidemic time, and the gender and age of susceptible groups were analyzed comprehensively. Secondly, the ARIMA model was constructed based on the number of weekly influenza cases and the percentage of visits to predict the percentage of ILI in the percentage of visits (ILI%). The optimized Elman neural network (ENN) model was applied to combine the ARIMA model into the ARIMA-ENN model, so as to improve the prediction effect of the ARIMA model. Then, the fitting prediction effect was evaluated with the ARIMA model. The results showed that there was a total of 11,293 suspected ILI cases in hospital, of which 773 were positive results, with the ILI% of 6.84%. There were obvious differences in ILI% among patients of different ages in various years (P |
| Databáze: | OpenAIRE |
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