Dynamics of Influenza A and SARS-CoV-2 coinfections during the COVID-19 pandemic in India

The SARS-CoV-2 exhibits similar aetiology, mode of transmission and clinical presentation as the H1N1pdm09 (a subtype of Influenza A) and Influenza A (other subtypes), and can exist as a coinfection in the same patient. It is essential to understand the coinfection dynamics of these viruses for effective management of the disease. This study examined 959 SARS-CoV-2 positive samples collected from the six states and three union territories in India from May to December 2022. The clinical data was accessed from the Integrated Health Information Platform (IHIP) and the Indian council of medical research (ICMR) COVID-19 data portal. The samples were tested for SARS-CoV-2, H1N1pdm09 and Influenza A using Reverse Transcriptase Real-Time Polymerase Chain Reaction q(RT-PCR). All 959 samples were subjected to SARS-CoV-2 whole genome sequencing (WGS) using Oxford Nanopore Next Generation Sequencing (NGS). From the 959 SARS-CoV-2 positive samples, 17.5% were co-infected with H1N1pdm09, 8.2% were co-infected with Influenza A, and 74.2% were only positive for SARS-CoV-2. The comparative analysis of viral load among the coinfected cases revealed that Influenza A and H1N1pdm09 had higher viral loads than SARS-CoV-2 in the studied samples. Out of 959 samples subjected to WGS, 815 and 144 were considered quality control (QC) passed, and QC failed, respectively, for SARS-CoV-2 variant calling. SARS-CoV-2 WGS identified 46 different variants belonging to the Omicron lineage. The SARS-CoV-2 and Influenza A coinfection group; and the SARS-CoV-2 and H1N1pdm09 coinfection group showed a higher proportion of symptomatic cases. This work demonstrates the need for coinfection analysis for the H1N1pdm09 virus, Influenza A virus and SARS-CoV-2 while studying the etiological agent in individuals with ILI/SARI symptoms. It is recommended that, in addition to determining the aetiology of ILI/SARI, an examination for H1N1pdm09 and Influenza A be conducted concurrently utilising molecular tools such as WGS and RT-PCR to understand the variant dynamics and the viral load for taking an informed decision during the patient management and treatment discourse.