National assessment of Canadian pandemic preparedness: Employing InFluNet to identify high-risk areas for inter-wave vaccine distribution

Background: Influenza pandemics emerge at irregular and unpredictable intervals to cause substantial health, economic and social burdens. Optimizing health-system response is vital to mitigating the consequences of future pandemics. Methods: We developed a mathematical model to assess the preparedness of Canadian health systems to accommodate pandemic-related increases in patient demand. We identify vulnerable areas, assess the potential of inter-wave vaccination to mitigate impacts and evaluate the association between demographic and health-system characteristics in order to identify predictors of pandemic consequences. Results: Modelled average attack rates were 23.7â37.2% with no intervention and 2.5â6.4% with pre-vaccination. Peak acute-care demand was 7.5â19.5% of capacity with no intervention and 0.6â2.6% with pre-vaccination. The peak ICU demand was 39.3â101.8% with no intervention and 2.9â13.3% with pre-vaccination. Total mortality was 2258â7944 with no intervention and 88â472 with pre-vaccination. Regions of Southern Ontario were identified as most vulnerable to surges in patient demand. The strongest predictors of peak acute-care demand and ICU demand were acute-care bed capacity (RÂ =Â â0.8697; r2Â =Â 0.7564) and ICU bed capacity (RÂ =Â â0.8151; r2Â =Â 0.6644), respectively. Demographic characteristics had mild associations with predicted pandemic consequences. Conclusion: Inter-wave vaccination provided adequate acute-care resource protection under all scenarios; ICU resource adequacy was protected under mild disease assumptions, but moderate and severe diseases caused demand to exceed expected availability in 21% and 49% of study areas, respectively. Our study informs priority vaccine distribution strategies for pandemic planning, emphasizing the need for targeted early vaccine distribution to high-risk individuals and areas. Keywords: Pandemic influenza, Vaccination, Differential equations, Mathematical modelling, Surge capacity, Canad