Abstract
Objectives: Human parainfluenza viruses (hPIV) are a common cause of acute respiratory infections, especially in children under five years and the elderly. hPIV can be subclassified as types 1-4: these showed various seasonality patterns worldwide, and it is unclear how climatic factors might consistently explain their global epidemiology.
Methods: This study collected time-series incidence data from the literature and hPIV surveillance programs worldwide (47 locations). Wavelet analysis and circular statistics were used to detect the seasonality and the months of peak incidence for each hPIV type. Relationships between climatic drivers and incidence peaks were assessed using a generalized estimating equation.
Results: The average positive rate of hPIV among patients with respiratory symptoms was 5.6% and ranged between 0.69-3.48% for different types. In the northern temperate region, the median peak incidence months for hPIV1, hPIV2, and hPIV4 were from September to October, while for hPIV3, it was in late May. Seasonal peaks of hPIV3 were associated with higher monthly temperatures and lower diurnal temperatures range throughout the year; hPIV4 peaks appeared to correlate with lower monthly temperatures and higher precipitation throughout the year. Different hPIV types exhibit different patterns of global epidemiology and transmission.
Conclusions: Climate drivers may play a role in hPIV transmission. More comprehensive and coherent surveillance of hPIV types would enable more in-depth analyses and inform the timing of preventive measures.
• Global type-specific hPIV incidence time-series data enables detailed analysis of seasonality.
• hPIV3 shows a different seasonality across many regions, compared to the hPIV1, 2 & 4.
• Increases in hPIV3 incidence are correlated with higher temperatures.