Effects of climatic factors on human parainfluenza 1, 2, and 3 infections in Cheonan, Republic of Korea

Studying relationships between meteorological conditions and respiratory virus infections may help interpret the causality of disease outbreaks and provide a better understanding of the seasonal distribution of viruses. Therefore, in this study, we analyzed the correlations between meteorological data and the trends of infection by human parainfluenza virus-1 (HPIV-1; also known as human respirovirus 1), human parainfluenza virus-2 (human orthorubulavirus 2), and human parainfluenza virus-3 (human respirovirus 3) using 9010 viral samples collected at Dankook University Hospital from January 1, 2012, to December 31, 2018. Infection frequency data were used to detect the seasonal patterns of HPIV-1, HPIV-2, and HPIV-3 infections, and these patterns were compared with local weather data over the same period. We performed descriptive statistical analysis, frequency analysis, t test, and binomial logistic regression analysis to examine the relationships of weather and particulate matter conditions with the incidence of HPIV-1, HPIV-2, and HPIV-3 infections. The highest average infection rate with one of these three viruses (88.17%) was found in children aged 1-9 years. Specifically, the infection rate of HPIV-1 was 91.9% in children aged 1-9 years, whereas that of HPIV-2 and HPIV-3 was 86.3%. HPIV infection exhibited a meaningful relationship with climatic factors, such as temperature, wind-chill temperature, and atmospheric pressure. Our results suggest that climate changes might affect the rate of infection by HPIV. These findings may help in predicting the effectiveness of preventive strategies of HPIV infection.

Automated summary

Studying the relationship between meteorological conditions and respiratory virus infections can help interpret disease outbreak causality and seasonal virus distribution. The analysis of three human parainfluenza virus infections indicated a meaningful relationship with climatic factors, suggesting that climate changes might affect infection rates and preventive strategies.