SEASONAL DISTRIBUTION OF INFLUENZA AND PARAINFLUENZA VIRUS INFECTIONS: RESULTS FROM A MULTI-YEAR EPIDEMIOLOGICAL SURVEILLANCE STUDY
Keywords:
Influenza, Parainfluenza (PIV), epidemiology, seasonality, surveillance, Acute Respiratory Infection (ARI), multiplex RT-PCR, co-circulation.Abstract
Objective: To define and compare the seasonal circulation patterns of Influenza viruses (A and B) and Parainfluenza viruses (PIV 1-4) using multi-year data from a national epidemiological surveillance network. Methods: We conducted a retrospective analysis of laboratory data from 35,820 nasopharyngeal swabs collected from patients (all ages) presenting with Influenza-Like Illness (ILI) to sentinel surveillance sites across [Country/Region] between January 2021 and December 2024. All samples were tested using a validated multiplex real-time RT-PCR panel detecting Influenza A (Flu A), Influenza B (Flu B), PIV-1, PIV-2, PIV-3, and PIV-4. The weekly positivity rate for each virus was analyzed to determine temporal distribution and peak activity. Results: At least one virus was detected in 38.5% (13,790/35,820) of samples. Influenza viruses accounted for 14.2% (n=5,086) and PIVs for 10.1% (n=3,618). Their seasonality was distinctly different. Influenza: Showed a highly consistent, sharp peak in the winter (Weeks 48-8), collectively accounting for >80% of its annual detections. Flu A (H3N2) and Flu B (Victoria) were the dominant co-circulating strains. Parainfluenza: PIV-3 was the most common type (5.5% of all samples) and exhibited a clear late spring/early summer peak (Weeks 18-25). PIV-1 and PIV-2 showed a biennial pattern, peaking in the autumn (Weeks 40-45) of odd-numbered years (2021, 2023). PIV-4 was detected at low levels year-round. Co-infections between Influenza and PIV were rare (<0.5%). Conclusion: Influenza and Parainfluenza viruses, while causing similar symptoms, follow highly predictable and distinct seasonal patterns. Influenza circulates almost exclusively in winter, whereas Parainfluenza activity peaks in spring (PIV-3) and autumn (PIV-1/2). These surveillance data are critical for clinical algorithms, guiding clinicians on the probable etiology of ILI based on the time of year and optimizing the use of antiviral therapy.
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