Climate variability and seasonal patterns of paediatric parainfluenza infections in the tropics: An ecological study in Singapore

Climate change and population health in Singapore: a systematic review

Gaseous emissions have contributed to global warming, an increase in the frequency of extreme weather events and poorer air quality. The associated health impacts have been well reported in temperate regions. In Singapore, key climate change adaptation measures and activities include coastal and flood protection, and mitigating heat impacts. We systematically reviewed studies examining climate variability and air quality with population health in Singapore, a tropical city-state in South-East Asia (SEA), with the aim to identify evidence gaps for policymakers. We included 14 studies with respiratory illnesses, cardiovascular outcomes, foodborne disease and dengue. Absolute humidity (3 studies) and rainfall (2 studies) were positively associated with adverse health. Extreme heat (2 studies) was inversely associated with adverse health. The effects of mean ambient temperature and relative humidity on adverse health were inconsistent. Nitrogen dioxide and ozone were positively associated with adverse health. Climate variability and air quality may have disease-specific, differing directions of effect in Singapore. Additional high quality studies are required to strengthen the evidence for policymaking. Research on effective climate action advocacy and adaptation measures for community activities should be strengthened.

Funding

There was no funding source for this study.

Epidemiological Characteristics of Parainfluenza Virus Type 3 and the Effects of Meteorological Factors in Hospitalized Children With Lower Respiratory Tract Infection

Objective

To investigate the relationship between meteorological factors and Human parainfluenza virus type 3 (HPIV-3) infection among hospitalized children.

Methods

All hospitalized children with acute lower respiratory tract infections were tested for viral pathogens and enrolled, at the second affiliated hospital of Wenzhou medical university, between 2008 and 2017. Meteorological data were directly obtained from Wenzhou Meteorology Bureau's nine weather stations and expressed as the mean exposure for each 10-day segment (average daily temperatures, average daily relative humidity, rainfall, rainfall days, and wind speed). The correlation between meteorological factors and the incidence of HPIV-3 was analyzed, with an autoregressive integrated moving average model (ARIMA), generalized additive model (GAM), and least absolute shrinkage and selection operator (LASSO).

Results

A total of 89,898 respiratory specimens were tested with rapid antigen tests, and HPIV-3 was detected in 3,619 children. HPIV-3 was detected year-round, but peak activities occurred most frequently from March to August. The GAM and LASSO-based model had revealed that HPIV-3 activity correlated positively with temperature and rainfall day, but negatively with wind speed. The ARIMA (1,0,0)(0,1,1) model well-matched the observed data, with a steady R2 reaching 0.708 (Ljung-Box Q = 21.178, P = 0.172).

Conclusion

Our study suggests that temperature, rainfall days, and wind speed have significant impacts on the activity of HPIV-3. GAM, ARIMA, and LASSO-based models can well predict the seasonality of HPIV-3 infection among hospitalized children. Further understanding of its mechanism would help facilitate the monitoring and early warning of HPIV-3 infection.