
Independent association between meteorological factors, PM2.5, and seasonal influenza activity in Hangzhou, Zhejiang province, China
Author(s) -
Lau Steven YukFai,
Cheng Wei,
Yu Zhao,
Mohammad Kirran N.,
Wang Maggie Haitian,
Zee Benny ChungYing,
Li Xi,
Chong Ka Chun,
Chen Enfu
Publication year - 2021
Publication title -
influenza and other respiratory viruses
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.743
H-Index - 57
eISSN - 1750-2659
pISSN - 1750-2640
DOI - 10.1111/irv.12829
Subject(s) - relative humidity , relative risk , poisson regression , environmental science , generalized additive model , distributed lag , demography , china , geography , medicine , climatology , atmospheric sciences , environmental health , veterinary medicine , meteorology , confidence interval , statistics , mathematics , population , sociology , geology , archaeology
Background Due to variations in climatic conditions, the effects of meteorological factors and PM 2.5 on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM 2.5 . Methods A total of 20 165 laboratory‐confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi‐Poisson‐generalized additive model and the distributed lag non‐linear model to examine the relationship of interest, controlling for long‐term trends, seasonal trends, and holidays. Results A hockey‐stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m 3 ) and high (>17.5 µg/m 3 ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM 2.5 , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections. Conclusions The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.