Abstract
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.