tetano
Editor, Senior Moderator
Sci Rep
. 2023 Jun 21;13(1):10114.
doi: 10.1038/s41598-023-37184-z. Identifying the regional drivers of influenza-like illness in Nova Scotia, Canada, with dominance analysis
Yigit Aydede[SUP] 1 [/SUP], Jan Ditzen[SUP] 2 [/SUP]
Affiliations
The spread of viral pathogens is inherently a spatial process. While the temporal aspects of viral spread at the epidemiological level have been increasingly well characterized, the spatial aspects of viral spread are still understudied due to a striking absence of theoretical expectations of how spatial dynamics may impact the temporal dynamics of viral populations. Characterizing the spatial transmission and understanding the factors driving it are important for anticipating local timing of disease incidence and for guiding more informed control strategies. Using a unique data set from Nova Scotia, Canada, the objective of this study is to apply a new novel method that recovers a spatial network of the influenza-like viral spread where the regions in their dominance are identified and ranked. We, then, focus on identifying regional predictors of those dominant regions. Our analysis uncovers 18 key regional drivers among 112 regions, each distinguished by unique community-level vulnerability factors such as demographic and economic characteristics. These findings offer valuable insights for implementing targeted public health interventions and allocating resources effectively.
. 2023 Jun 21;13(1):10114.
doi: 10.1038/s41598-023-37184-z. Identifying the regional drivers of influenza-like illness in Nova Scotia, Canada, with dominance analysis
Yigit Aydede[SUP] 1 [/SUP], Jan Ditzen[SUP] 2 [/SUP]
Affiliations
- PMID: 37344569
- PMCID: PMC10284866
- DOI: 10.1038/s41598-023-37184-z
The spread of viral pathogens is inherently a spatial process. While the temporal aspects of viral spread at the epidemiological level have been increasingly well characterized, the spatial aspects of viral spread are still understudied due to a striking absence of theoretical expectations of how spatial dynamics may impact the temporal dynamics of viral populations. Characterizing the spatial transmission and understanding the factors driving it are important for anticipating local timing of disease incidence and for guiding more informed control strategies. Using a unique data set from Nova Scotia, Canada, the objective of this study is to apply a new novel method that recovers a spatial network of the influenza-like viral spread where the regions in their dominance are identified and ranked. We, then, focus on identifying regional predictors of those dominant regions. Our analysis uncovers 18 key regional drivers among 112 regions, each distinguished by unique community-level vulnerability factors such as demographic and economic characteristics. These findings offer valuable insights for implementing targeted public health interventions and allocating resources effectively.