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Abstract
Respiratory viruses that were suppressed through previous lockdowns during the COVID-19 pandemic have recently started to co-circulate with SARS-CoV-2. Understanding the clinical characteristics and symptomatology of different respiratory viral infections can help address the challenges related to the identification of cases and the understanding of SARS-CoV-2 variants' evolutionary patterns. Flu Watch (2006–2011) and Virus Watch (2020–2022) are household community cohort studies monitoring the epidemiology of influenza, respiratory syncytial virus, rhinovirus, seasonal coronavirus, and SARS-CoV-2, in England and Wales. This study describes and compares the proportion of symptoms reported during illnesses infected by common respiratory viruses. The SARS-CoV-2 symptom profile increasingly resembles that of other respiratory viruses as new strains emerge. Increased cough, sore throat, runny nose, and sneezing are associated with the emergence of the Omicron strains. As SARS-CoV-2 becomes endemic, monitoring the evolution of its symptomatology associated with new variants will be critical for clinical surveillance.
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1 Imperial College London, MRC Centre for Global Infectious Disease Analysis and NIHR Health Protection Research Unit in Modelling and Health Economics, Department of Infectious Disease Epidemiology, School of Public Health, London, UK (GRID:grid.7445.2) (ISNI:0000 0001 2113 8111); University College London, Centre for Public Health Data Science, Institute of Health Informatics, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201)
2 University College London, Centre for Public Health Data Science, Institute of Health Informatics, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201)
3 University College London, Institute of Epidemiology and Health Care, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); London School of Hygiene and Tropical Medicine, Department of Infectious Disease Epidemiology, London, UK (GRID:grid.8991.9) (ISNI:0000 0004 0425 469X)
4 University College London, Centre for Public Health Data Science, Institute of Health Informatics, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201); University College London, Institute of Epidemiology and Health Care, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201)
5 University College London, Institute of Epidemiology and Health Care, London, UK (GRID:grid.83440.3b) (ISNI:0000000121901201)