Seasonality of respiratory viruses causing hospitalizations for acute respiratory infections in children in Nha Trang, Vietnam

Abstract

Background: Acute respiratory infections (ARIs) are the most common causes of death in children under 5 years of age. While the etiology of most pneumonia and ARI episodes is undiagnosed, a broad range of ARI-causing viruses circulate widely in South East Asia. However, the patterns and drivers of the seasonal transmission dynamics are largely unknown. Here we identify the seasonal patterns of multiple circulating viruses associated with hospitalizations for ARIs in Nha Trang, Vietnam.

Methods: Hospital based enhanced surveillance of childhood ARI is ongoing at Khanh Hoa General Hospital in Nha Trang. RT-PCR was performed to detect 13 respiratory viruses in nasopharyngeal samples from enrolled patients. Seasonal patterns of childhood ARI hospital admissions of various viruses were assessed, as well as their association with rainfall, temperature, and dew point.

Results: Respiratory syncytial virus peaks in the late summer months, and influenza A in April to June. We find significant associations between detection of human parainfluenza 3 and human rhinovirus with the month's mean dew point. Using a cross-wavelet transform we find a significant out-of-phase relationship between human parainfluenza 3 and temperature and dew point.

Conclusions: Our results are important for understanding the temporal risk associated with circulating pathogens in Southern Central Vietnam. Specifically, our results can inform timing of routing seasonal influenza vaccination and for when observed respiratory illness is likely viral, leading to judicious use of antibiotics in the region.

Keywords: Respiratory viruses; Seasonality of transmission; weather effects on transmission.

Figure 1

Monthly hospitalizations by virus in Nha Trang, Vietnam. Figure shows monthly detections of virus as percentages of all enrolled ARI hospitalizations.

Figure 2

Seasonality of hospitalizations and any viral detection in Nha Trang, Vietnam. Figure shows weekly counts of all hospitalizations (top row) and any virus detection (bottom row). Right-hand column shows model-adjusted incidence rate ratios for month of year as compared to January. Red months indicates statistically significant deviations from January.

Figure 3

Seasonality of common respiratory viruses in Nha Trang, Vietnam. Figure shows model-adjusted incidence rate ratios for month of year as compared to January. Red months indicates statistically significant deviations from January.

Figure 4

Weather effects. Figure shows model-adjusted incidence rate ratios for the main three weather effects: monthly mean rainfall (in inches), temperature (1^∘ F), and dew point (1^∘ F).

Figure 5

Cross-wavelet transform of the z-standardized all hospitalization counts and weather time series. Figure shows the cross-wavelet of all hospitalization counts and rainfall, temperature, and dew point. Colors indicate increasing cross-wavelet power (strength of coherence between the time series) blue to red. The 5% significance level against red noise is shown as a thick contour and the cone of influence (within which the wavelets are not influenced by the edges of the time series) is shown in white shading. The relative phase relationship is shown as arrows (with in-phase pointing right, out-of-phase pointing left, and weather leading hospitalizations by 90^∘ pointing straight down).

Figure 6

Cross-wavelet transform of the z-standardized RSV and weather time series. Figure shows the cross-wavelet of RSV and rainfall, temperature, and dew point. Colors indicate increasing cross-wavelet power (strength of coherence between the time series) blue to red. The 5% significance level against red noise is shown as a thick contour and the cone of influence (within which the wavelets are not influenced by the edges of the time series) is shown in white shading. The relative phase relationship is shown as arrows (with in-phase pointing right, out-of-phase pointing left, and weather leading RSV by 90^∘ pointing straight down).

Figure 7

Cross-wavelet transform of the z-standardized HPIV3 and weather time series. Figure shows the cross-wavelet of HPIV3 and rainfall, temperature, and dew point. Colors indicate increasing cross-wavelet power (strength of coherence between the time series) blue to red. The 5% significance level against red noise is shown as a thick contour and the cone of influence (within which the wavelets are not influenced by the edges of the time series) is shown in white shading. The relative phase relationship is shown as arrows (with in-phase pointing right, out-of-phase pointing left, and weather leading HPIV3 by 90^∘ pointing straight down).