Different responses of influenza epidemic to weather factors among Shanghai, Hong Kong, and British Columbia

Abstract

Weather factors have long been considered as key sources for regional heterogeneity of influenza seasonal patterns. As influenza peaks coincide with both high and low temperature in subtropical cities, weather factors may nonlinearly or interactively affect influenza activity. This study aims to assess the nonlinear and interactive effects of weather factors with influenza activity and compare the responses of influenza epidemic to weather factors in two subtropical regions of southern China (Shanghai and Hong Kong) and one temperate province of Canada (British Columbia). Weekly data on influenza activity and weather factors (i.e., mean temperature and relative humidity (RH)) were obtained from pertinent government departments for the three regions. Absolute humidity (AH) was measured by vapor pressure (VP), which could be converted from temperature and RH. Generalized additive models were used to assess the exposure-response relationship between weather factors and influenza virus activity. Interactions of weather factors were further assessed by bivariate response models and stratification analyses. The exposure-response curves of temperature and VP, but not RH, were consistent among three regions/cities. Bivariate response model revealed a significant interactive effect between temperature (or VP) and RH (P < 0.05). Influenza peaked at low temperature or high temperature with high RH. Temperature and VP are important weather factors in developing a universal model to explain seasonal outbreaks of influenza. However, further research is needed to assess the association between weather factors and influenza activity in a wider context of social and environmental conditions.

Effect of meteorological factors on the activity of influenza in Chongqing, China, 2012–2019

“…A signi cant wet effect on in uenza activity was observed in Chongqing, which is consistent with previous studies 12, [20][21][22][23] . Experimental study has shown stronger infectivity of in uenza virus in a high relative humidity 24 .…”

The complex associations of climate variability with seasonal influenza A and B virus transmission in subtropical Shanghai, China

“…A decline of 1°C in temperature increased influenza infections risk by 11% in Finland (Jaakkola et al, 2014). Moreover, 1°C decrease of temperature cased a rising of 8.55% in influenza cases in Hong Kong, and an increase of 32.14% in the UK (Wang et al, 2017). Low temperature may lengthen the survival of influenza virus, and lead to increasing contact rates through more people indoor crowding (Cheng et al, 2016;Liao et al, 2005).…”

“…There are different responses of influenza to climate factors in different climate zones. The area with temperate climate appeared to have greater risk in temperature and humidity, compared to subtropical regions (Wang et al, 2017). The author reported that this may due to a lower mean temperature and humidity in temperate areas than that in subtropical regions.…”

“…Other climate variables, such as absolute humidity, relative humidity and rainfall have also been reported to be associated with seasonal influenza infections (Gomez-Barroso et al, 2017;Shaman and Kohn, 2009;Shaman et al, 2010b;Tamerius et al, 2013). Moreover, the geographical variation of seasonal patterns of influenza indicates that climate factors may promote influenza infections with complex interactive effects, such as the significant interactive effect between temperature and relative humidity (Wang et al, 2017). However, the majority of previous studies focused on tropical or temperate zones, little is known about the associations of multiple climate variables with different influenza types in subtropical regions.…”

Meteorological factors and the incidence of mumps in Fujian Province, China, 2005–2013: Non-linear effects

“…Non-linear models have been widely used in assessing the relationships between meteorological factors and health outcomes (Peng et al, 2017;Wang et al, 2017). Meanwhile, most studies found the lagged effects of meteorological factors (Antunes et al, 2017;Seposo et al, 2017).…”