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Infect Dis Model. 2017 Jul 5;2(3):341-352. doi: 10.1016/j.idm.2017.06.005. eCollection 2017 Aug.
National assessment of Canadian pandemic preparedness: Employing InFluNet to identify high-risk areas for inter-wave vaccine distribution.
Saunders-Hastings P1,2, Hayes BQ3, Smith R2,3, Krewski D1,2,4.
Author information
Abstract
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 23.7-37.2% with no intervention and 2.5-6.4% with pre-vaccination. Peak acute-care demand was 7.5-19.5% of capacity with no intervention and 0.6-2.6% with pre-vaccination. The peak ICU demand was 39.3-101.8% with no intervention and 2.9-13.3% with pre-vaccination. Total mortality was 2258-7944 with no intervention and 88-472 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 (R = -0.8697; r2 = 0.7564) and ICU bed capacity (R = -0.8151; r2 = 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:
Canada; Differential equations; Mathematical modelling; Pandemic influenza; Surge capacity; Vaccination
PMID: 29928746 PMCID: PMC6002068 DOI: 10.1016/j.idm.2017.06.005
National assessment of Canadian pandemic preparedness: Employing InFluNet to identify high-risk areas for inter-wave vaccine distribution.
Saunders-Hastings P1,2, Hayes BQ3, Smith R2,3, Krewski D1,2,4.
Author information
Abstract
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 23.7-37.2% with no intervention and 2.5-6.4% with pre-vaccination. Peak acute-care demand was 7.5-19.5% of capacity with no intervention and 0.6-2.6% with pre-vaccination. The peak ICU demand was 39.3-101.8% with no intervention and 2.9-13.3% with pre-vaccination. Total mortality was 2258-7944 with no intervention and 88-472 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 (R = -0.8697; r2 = 0.7564) and ICU bed capacity (R = -0.8151; r2 = 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:
Canada; Differential equations; Mathematical modelling; Pandemic influenza; Surge capacity; Vaccination
PMID: 29928746 PMCID: PMC6002068 DOI: 10.1016/j.idm.2017.06.005