Air quality, meteorological variability and pediatric respiratory syncytial virus infections in Singapore

Abstract

Respiratory syncytial virus (RSV) is an important cause of respiratory illness among children. While studies have focused on the air-quality and climate dependence of RSV infections, few have been undertaken in South-East Asia where the burden of respiratory illness is among the highest across the globe. This study aimed to determine the relationships between climatic factors and air quality with RSV infections among children in Singapore. We obtained all laboratory-confirmed reports of RSV infections in children below 5 years old from the largest public hospital specializing in pediatric healthcare in Singapore. We assessed the independent cumulative effects of air quality and meteorological factors on RSV infection risk using the Distributed Lag Non-Linear Model (DLNM) framework in negative binomial models adjusted for long-term trend, seasonality and changes in the diagnostic systems. We included 15,715 laboratory-confirmed RSV reports from 2009 to 2019. Daily maximum temperature exhibited a complex, non-linear association with RSV infections. Absolute humidity (Relative Risk, 90th percentile [RR90th percentile]: 1.170, 95% CI: [1.102, 1.242]) was positively associated with RSV risk. Higher levels of particulate matter of aerodynamic diameter of less than (i) 2.5 µm (PM2.5), (ii) 10 µm (PM10), carbon monoxide (CO) and sulfur dioxide (SO2) were associated with lower RSV infection risk. RSV infections exhibited both annual and within-year seasonality. Our findings suggest that falls in ambient temperature and rises in absolute humidity exacerbated pediatric RSV infection risk while increases in air pollutant concentrations were associated with lowered infection risk. These meteorological factors, together with the predictable seasonality of RSV infections, can inform the timing of mitigation measures aimed at reducing transmission.

Epidemiology and burden of respiratory syncytial virus in Italian adults: A systematic review and meta-analysis

“…Compared with central and southern regions, mean winter temperature in northern regions is lower [70]. Lower ambient temperature is a well-known positive predictor of RSV detection frequency [71][72][73]. Smaller studies tended to report a higher RSV prevalence, which is consistent with the small study effect.…”

Multilevel analysis identifying the factors associated with RSV detection in infants admitted for viral bronchiolitis in the era of the COVID‐19 pandemic

“…45 Third, other studies have also reported an inverse relationship between levels of the same and other air pollutants and the rate of hospitalization for respiratory tract infections and RSV infection risk. [46][47][48] Interestingly, all these studies reporting these inverse relationships have been conducted in countries with tropical or subtropical climates, as is also the case in our country. This finding may suggest residual confounding by an unmeasured seasonal confounder or other bias present in countries with this climate.…”

“…Second, due to restrictions imposed during the COVID‐19 pandemic, levels of air pollutants decreased, but indoor stays also increased, which in some individuals may have increased exposure to indoor air pollutants and the risk of human‐to‐human transmission of RSV as a result of indoor crowding 45 . Third, other studies have also reported an inverse relationship between levels of the same and other air pollutants and the rate of hospitalization for respiratory tract infections and RSV infection risk 46–48 . Interestingly, all these studies reporting these inverse relationships have been conducted in countries with tropical or subtropical climates, as is also the case in our country.…”

Spatio-temporal characteristics and influencing factors of air quality in Hunan Province: investigation based on functional data model

“…A large body of literature has shown that meteorological conditions significantly affect air quality. In this paper, based on existing literature, temperature (C), wind speed (m/s) and rainfall (mm) were selected as meteorological indicators affecting air quality (Hoque et al, 2022;Asimakopoulos, 2012;Jacob et al, 2019;Querol, 2011;Zhang, 2020;Lee et al, 2023). In terms of socio-economic factors, according to the Environmental Kuznets Curve (EKC), there is an inverted "U"-shaped relationship between economic growth and environmental quality.…”

“…The influencing factors of air quality are divided into meteorological and social and economic factors. It has been shown that wind, relative humidity, and climate among meteorological factors have a significant impact on air quality (Hoque et al, 2022;Asimakopoulos, 2012;Jacob et al, 2019;Querol, 2011;Zhang, 2020;Lee et al, 2023). Researchers have confirmed the correlation between GDP and air pollution (Grossman and Krueger, 1991;Lee, 2009;Ngaravas et al, 2019;Plassmann, 2006;Ahmad et al, 2021).…”