Abstract
The study of climate and respiratory viral infections using big data may enable the recognition and interpretation of relationships between disease occurrence and climatic variables. In this study, realtime reverse transcription quantitative PCR (qPCR) methods were used to identify Human respiratory coronaviruses (HCoV). infections in patients below 10 years of age with respiratory infections who visited Dankook University Hospital in Cheonan, South Korea, from January 1, 2012, to December 31, 2018. Out of the 9010 patients who underwent respiratory virus real-time reverse transcription qPCR test, 364 tested positive for HCoV infections. Among these 364 patients, 72.8% (n = 265) were below 10 years of age. Data regarding the frequency of infections was used to uncover the seasonal pattern of the two viral strains, which was then compared with local meteorological data for the same time period. HCoV-229E and HCoV-OC43 showed high infection rates in patients below 10 years of age. There was a negative relationship between HCoV-229E and HCoV-OC43 infections with air temperature and wind-chill temperatures. Both HCoV-229E and HCoV-OC43 rates of infection were positively related to atmospheric pressure, while HCoV-229E was also positively associated with particulate matter concentrations. Our results suggest that climatic variables affect the rate in which children below 10 years of age are infected with HCoV. These findings may help to predict when prevention strategies may be most effective.