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Infection dynamics across regions during the COVID-19 pandemic in Norway
Sanjay Gyawali1, Espen Rostrup Nakstad2, Bjørn Sletvold3
1Health Services Research Unit, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Background:
Urban areas often act as early epicentres of pandemics, yet transmission dynamics across regions with different demographic profiles remains poorly understood. We aimed to characterise COVID-19 transmission in Norway and assess how it interacted with infection control measures across urban and rural settings.
Methods:
We analysed daily COVID-19 cases across three pandemic waves (Alpha, Delta, Omicron). For local trends, 36 sites in the Greater Oslo Region were grouped by infection trajectories using group-based trajectory modelling. For national trends, we examined the cities of Oslo, Bergen, Trondheim, Stavanger, Tromsø, and Akershus county. Infection trends were analysed using linear mixed models and lagged regression analyses and related to demographic characteristics.
Results:
In the Greater Oslo Region, three distinct site groups-high, moderate, and low infection-were identified. The high infection group had the highest population density, largest proportion of crowded housing and immigrant population and preceded the moderate and low groups by 5-13 days during the Alpha wave. Nationally, Oslo's infection rates peaked 11-24 days before other cities during the Alpha wave, with shorter lags during the Delta and Omicron waves. Despite similar control measures, infection rates differed substantially, with the high infection group and Oslo city consistently bearing the greatest burden.
Conclusions:
Densely populated areas with crowded housing act as early warning signals, with infection growth preceding that in other areas by days to weeks. Systematic monitoring of such high-burden urban areas could provide valuable lead time for policymakers and support more targeted, timely responses in future pandemics.
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