Seasonal pattern of influenza and the association with meteorological factors based on wavelet analysis in Jinan City, Eastern China, 2013-2016

Wei Su; Ti Liu; Xingyi Geng; Guoliang Yang

doi:10.7717/peerj.8626

Seasonal pattern of influenza and the association with meteorological factors based on wavelet analysis in Jinan City, Eastern China, 2013-2016

PeerJ. 2020 Mar 9:8:e8626. doi: 10.7717/peerj.8626. eCollection 2020.

Authors

Wei Su^#¹, Ti Liu^#², Xingyi Geng³, Guoliang Yang³

Affiliations

¹ School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, Shandong Province, China.
² Shandong Center for Disease Control and Prevention, Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong University Institution for Prevention Medicine, Jinan, Shandong Province, China.
³ Jinan Center for Disease Control and Prevention, Jinan, Shandong Province, China.

^# Contributed equally.

Abstract

Background: Influenza is a disease under surveillance worldwide with different seasonal patterns in temperate and tropical regions. Previous studies have conducted modeling of influenza seasonality using climate variables. This study aimed to identify potential meteorological factors that are associated with influenza seasonality in Jinan, China.

Methods: Data from three influenza sentinel hospitals and respective climate factors (average temperature, relatively humidity (RH), absolute humidity (AH), sunshine duration, accumulated rainfall and speed of wind), from 2013 to 2016, were collected. Statistical and wavelet analyses were used to explore the epidemiological characteristics of influenza virus and its potential association with climate factors.

Results: The dynamic of influenza was characterized by annual cycle, with remarkable winter epidemic peaks from December to February. Spearman's correlation and wavelet coherence analysis illuminated that temperature, AH and atmospheric pressure were main influencing factors. Multiple wavelet coherence analysis showed that temperature and atmospheric pressure might be the main influencing factors of influenza virus A(H3N2) and influenza virus B, whereas temperature and AH might best shape the seasonality of influenza virus A(H1N1)pdm09. During the epidemic season, the prevalence of influenza virus lagged behind the change of temperature by 1-8 weeks and atmospheric pressure by 0.5-3 weeks for different influenza viruses.

Conclusion: Climate factors were significantly associated with influenza seasonality in Jinan during the influenza epidemic season and the optional time for influenza vaccination is before November. These finding should be considered in influenza planning of control and prevention.

Keywords: Climatic factors; Influenza surveillance; Seasonality; Wavelet analysis.

Grants and funding

The study is supported by Health and Family Planning Commission of Shandong Province (2016WS0382 and 2016WS0381). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.