Association of climatic variables with risk of transmission of influenza in Guangzhou, China, 2005–2021

Abstract

<h3>Background</h3><p>Climatic variables constitute important extrinsic determinants of transmission and <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/seasonality" title="Learn more about seasonality from ScienceDirect's AI-generated Topic Pages">seasonality</a> of influenza. Yet quantitative evidence of independent associations of viral transmissibility with <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/climatic-factor" title="Learn more about climatic factors from ScienceDirect's AI-generated Topic Pages">climatic factors</a> has thus far been scarce and little is known about the potential effects of interactions between <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/climatic-factor" title="Learn more about climatic factors from ScienceDirect's AI-generated Topic Pages">climatic factors</a> on transmission.</p><h3>Objective</h3><p>This study aimed to examine the associations of key climatic factors with risk of influenza transmission in subtropical Guangzhou.</p><h3>Methods</h3><p><a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/seasonal-influenza" title="Learn more about Influenza epidemics from ScienceDirect's AI-generated Topic Pages">Influenza epidemics</a> were identified over a 17-year period using the moving epidemic method (MEM) from a dataset of N = 295,981 clinically- and laboratory-confirmed cases of influenza in Guangzhou. Data on eight key climatic variables were collected from China Meteorological Data Service Centre. Generalized additive model combined with the distributed lag non-linear model (DLNM) were developed to estimate the exposure-lag-response curve showing the trajectory of instantaneous reproduction number (R_t) across the distribution of each climatic variable after adjusting for depletion of susceptible, inter-epidemic effect and school holidays. The potential interaction effects of temperature, humidity and rainfall on influenza transmission were also examined.</p><h3>Results</h3><p>Over the study period (2005–21), 21 distinct influenza epidemics with varying peak timings and durations were identified. Increasing air temperature, sunshine, absolute and relative humidity were significantly associated with lower R_t, while the associations were opposite in the case of ambient pressure, <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/wind-velocity" title="Learn more about wind speed from ScienceDirect's AI-generated Topic Pages">wind speed</a> and rainfall. Rainfall, relative humidity, and ambient temperature were the top three climatic contributors to variance in transmissibility. Interaction models found that the detrimental association between high relative humidity and transmissibility was more pronounced at high temperature and rainfall.</p><h3>Conclusion</h3><p>Our findings are likely to help understand the complex role of climatic factors in influenza transmission, guiding informed climate-related mitigation and adaptation policies to reduce transmission in high density subtropical cities.</p>