tetano
Editor, Senior Moderator
PNAS Nexus
. 2022 Sep 17;1(4)
gac194.
doi: 10.1093/pnasnexus/pgac194. eCollection 2022 Sep.
Estimating R [SUB]0[/SUB] from early exponential growth: parallels between 1918 influenza and 2020 SARS-CoV-2 pandemics
Grant Foster[SUP] 1 2 [/SUP], Bret D Elderd[SUP] 2 [/SUP], Robert L Richards[SUP] 2 [/SUP], Tad Dallas[SUP] 1 2 [/SUP]
Affiliations
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 [SUB]0[/SUB], 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 [SUB]0[/SUB] across the United States. Additionally, we provide one of the first city-level comparisons of R [SUB]0[/SUB] between these two pandemics and explore how demography and outbreak timing are related to R [SUB]0[/SUB]. Despite similarities in transmission modes and a common set of locations, R [SUB]0[/SUB] estimates for COVID-19 were uncorrelated with estimates of pandemic influenza R [SUB]0[/SUB] in the same cities. Also, the relationships between R [SUB]0[/SUB] 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.
. 2022 Sep 17;1(4)
gac194.doi: 10.1093/pnasnexus/pgac194. eCollection 2022 Sep.
Estimating R [SUB]0[/SUB] from early exponential growth: parallels between 1918 influenza and 2020 SARS-CoV-2 pandemics
Grant Foster[SUP] 1 2 [/SUP], Bret D Elderd[SUP] 2 [/SUP], Robert L Richards[SUP] 2 [/SUP], Tad Dallas[SUP] 1 2 [/SUP]
Affiliations
- PMID: 36714850
- PMCID: PMC9802102
- DOI: 10.1093/pnasnexus/pgac194
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 [SUB]0[/SUB], 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 [SUB]0[/SUB] across the United States. Additionally, we provide one of the first city-level comparisons of R [SUB]0[/SUB] between these two pandemics and explore how demography and outbreak timing are related to R [SUB]0[/SUB]. Despite similarities in transmission modes and a common set of locations, R [SUB]0[/SUB] estimates for COVID-19 were uncorrelated with estimates of pandemic influenza R [SUB]0[/SUB] in the same cities. Also, the relationships between R [SUB]0[/SUB] 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.