The large spatial scale, geographical overlap, and similarities in transmission mode between the 1918 H1N1 influenza and 2020 SARS-CoV-2 pandemics together provide a novel opportunity to investigate relationships between transmission of two different diseases in the same location. To this end, we use initial exponential growth rates in a Bayesian hierarchical framework to estimate the basic reproductive number, R 0, of both disease outbreaks in a common set of 43 cities in the United States. By leveraging multiple epidemic time series across a large spatial area, we are able to better characterize the variation in R 0 across the United States. Additionally, we provide one of the first city-level comparisons of R 0 between these two pandemics and explore how demography and outbreak timing are related to R 0. Despite similarities in transmission modes and a common set of locations, R 0 estimates for COVID-19 were uncorrelated with estimates of pandemic influenza R 0 in the same cities. Also, the relationships between R 0 and key population or epidemic traits differed between diseases. For example, epidemics that started later tended to be less severe for COVID-19, while influenza epidemics exhibited an opposite pattern. Our results suggest that despite similarities between diseases, epidemics starting in the same location may differ markedly in their initial progression.
Keywords: COVID-19; infectious diseases; pandemic influenza; public health.
© The Author(s) 2022. Published by Oxford University Press on behalf of National Academy of Sciences.