Study on the clinico demographic profile and prevalence of human influenza cases among the severe acute respiratory illness cases in a rural teaching hospital of West Bengal, India

Background: Influenza is an infectious disease caused mainly by influenza virus types A and B. High frequency of mutation and genetic reassortment results in the introduction of a new influenza strain which causes major epidemics and pandemics.  Aims and Objectives: The aims and objectives of this study were to find the incidence of Influenza A and B viruses as well as the subtypes of influenza A (H1N1 pdm09 and H3N2) among patients admitted at our hospital with severe acute respiratory illness (SARI) and also to find the demographic characteristics and seasonal distribution of the influenza cases. Materials and Methods: This study was done for one year at the Department of Microbiology of Tamralipto Government Medical College and Hospital, Tamluk, West Bengal with 310 samples from patients admitted at our hospital with SARI. Viral ribonucleic acid (RNA) extraction was performed using QIAamp Viral RNA Mini Kit by QIAGEN kit followed by performing real-time-polymerase chain reaction (RT-PCR) by applied Biosystems 7500 Fast Dx by Thermo Fisher Scientific for typing and subtyping of influenza virus using VIASURE RT-PCR Detection Kits. Results: Among the 310 SARI patients tested by RT-PCR, 25 (8.06%) patients tested positive for influenza virus out of which 18 patients (72%) were positive for influenza A, whereas 7 patients (28%) were positive for influenza B. Out of the 18 influenza A virus-positive samples, 12 samples (66.67%) were positive for H3N2 subtype and 6 samples (33.33%) were positive for H1N1 subtype. Most of the Influenza positive patients belonged to the age group of 26–40 years and the majority of the influenza cases were detected during monsoon and post-monsoon season.  Conclusion: Influenza is a major challenge to public health which causes many complications and deaths each year. Early detection by RT-PCR among suspected cases will determine the prevalence of influenza and help in the appropriate treatment in time, which will reduce complications and mortality.