Next Article in Journal
Burnout and Its Relationships with Alexithymia, Stress, and Social Support among Romanian Medical Students: A Cross-Sectional Study
Previous Article in Journal
Enteric Viruses and Fecal Bacteria Indicators to Assess Groundwater Quality and Suitability for Irrigation
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Int. J. Environ. Res. Public Health 2017, 14(6), 559; doi:10.3390/ijerph14060559

Epidemiological Features and Forecast Model Analysis for the Morbidity of Influenza in Ningbo, China, 2006–2014

1
Department of Chronic Diseases and Community Health, Fenghua Municipal Center for Disease Control and Prevention, Ningbo 315500, China
2
Department of Virus Research, Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China
3
Department of Science Research and Information Management, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Peter Congdon
Received: 5 April 2017 / Revised: 17 May 2017 / Accepted: 19 May 2017 / Published: 25 May 2017
(This article belongs to the Section Global Health)
View Full-Text   |   Download PDF [1747 KB, uploaded 25 May 2017]   |  

Abstract

This study aimed to identify circulating influenza virus strains and vulnerable population groups and investigate the distribution and seasonality of influenza viruses in Ningbo, China. Then, an autoregressive integrated moving average (ARIMA) model for prediction was established. Influenza surveillance data for 2006–2014 were obtained for cases of influenza-like illness (ILI) (n = 129,528) from the municipal Centers for Disease Control and virus surveillance systems of Ningbo, China. The ARIMA model was proposed to predict the expected morbidity cases from January 2015 to December 2015. Of the 13,294 specimens, influenza virus was detected in 1148 (8.64%) samples, including 951 (82.84%) influenza type A and 197 (17.16%) influenza type B viruses; the influenza virus isolation rate was strongly correlated with the rate of ILI during the overall study period (r = 0.20, p < 0.05). The ARIMA (1, 1, 1) (1, 1, 0)12 model could be used to predict the ILI incidence in Ningbo. The seasonal pattern of influenza activity in Ningbo tended to peak during the rainy season and winter. Given those results, the model we established could effectively predict the trend of influenza-related morbidity, providing a methodological basis for future influenza monitoring and control strategies in the study area. View Full-Text
Keywords: ARIMA model; influenza; influenza-like illness; prediction ARIMA model; influenza; influenza-like illness; prediction
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wang, C.; Li, Y.; Feng, W.; Liu, K.; Zhang, S.; Hu, F.; Jiao, S.; Lao, X.; Ni, H.; Xu, G. Epidemiological Features and Forecast Model Analysis for the Morbidity of Influenza in Ningbo, China, 2006–2014. Int. J. Environ. Res. Public Health 2017, 14, 559.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top