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

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.

Identifying the Dynamic Pattern and Influencing Factors of Influenza in Northwest China from 2013 to 2020, Based on Dynamic Regression Model and Wavelet Analysis

“…Chong et al [49] verified that the temperature may be connected with the influenza virus epidemic, not only influenza virus A, but also influenza virus B. In this study, we also observed that minimum temperature is negatively associated with influenza cases, which was consistent with the finding of related studies of Lowen and Steel [17]. The mechanism may be that the influenza transmission was most efficient at low temperature (e.g.…”

“…The temperature difference is an important feature of climate that can have important impacts on the influenza virus transmission [47] and may cause the seasonal influenza outbreaks [48]. Su et al [17] observed a negative association between average temperature and three influenza virus subtype by using of Spearman's correlation and WTC. Chong et al [49] verified that the temperature may be connected with the influenza virus epidemic, not only influenza virus A, but also influenza virus B.…”

“…At the same time, the mathematical models have become a powerful tools to investigate the time-series of infectious diseases recently, thus, various models (such as generalized regression [11], stochastic model [12], compartmental model [13,14] and autoregressive moving average models [7,15]) have been used to forecast influenza in order to analyze the trends and predict the root cause of the influenza incidence epidemic. In addition, the wavelet analysis recently has become an powerful tool to investigate the potential inter-connectedness between influenza and climate factors according to the method proposed by Grinsted, Moore and Jevrejeva [16,17]. These methods provide the approaches to investigated the dynamic pattern of influenza, which is important to analyze and know the epidemic situation of influenza.…”

Meteorological factors correlate with transmission of 2019-nCoV: Proof of incidence of novel coronavirus pneumonia in Hubei Province, China

“…The cause of influenza may be that nasal mucosa is easy to rupture under dry conditions and high pressure in winter, so it is easy to be infected with virus. However, the detailed mechanism needs further study (Su et al,2020).…”

“…In epidemiological studies, seasonal and metering conditions of influenza were compared, and the results showed lower temperature and water vapor pressure can increase the survival and transmission of influenza virus in temperate regions (Shaman & Kohn, 2009;Shaman et al, 2010Shaman et al, & 2011Kolberg et al, 2019). Studies from China also prove that influenza virus is negatively correlated with temperature and water vapor pressure (Cao et al, 2010;Sun et al, 2018;Yang et al, 2019;Su et al, 2020). The average water vapor pressure in sub-cold zone climate is lower than 4 hPa, which may trigger the occurrence of influenza (Kolberg et al, 2019).…”