tetano
Editor, Senior Moderator
Infect Dis Model. 2017 Jul 5;2(3):341-352. doi: 10.1016/j.idm.2017.06.005. eCollection 2017 Aug.
[h=1]National assessment of Canadian pandemic preparedness: Employing InFluNet to identify high-risk areas for inter-wave vaccine distribution.[/h] Saunders-Hastings P[SUP]1,[/SUP][SUP]2[/SUP], Hayes BQ[SUP]3[/SUP], Smith R[SUP]2,[/SUP][SUP]3[/SUP], Krewski D[SUP]1,[/SUP][SUP]2,[/SUP][SUP]4[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]Background:[/h] 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.
[h=4]Methods:[/h] 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.
[h=4]Results:[/h] 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; r[SUP]2[/SUP] = 0.7564) and ICU bed capacity (R = -0.8151; r[SUP]2[/SUP] = 0.6644), respectively. Demographic characteristics had mild associations with predicted pandemic consequences.
[h=4]Conclusion:[/h] 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.
[h=4]KEYWORDS:[/h] Canada; Differential equations; Mathematical modelling; Pandemic influenza; Surge capacity; Vaccination
PMID: 29928746 PMCID: PMC6002068 DOI: 10.1016/j.idm.2017.06.005
[h=1]National assessment of Canadian pandemic preparedness: Employing InFluNet to identify high-risk areas for inter-wave vaccine distribution.[/h] Saunders-Hastings P[SUP]1,[/SUP][SUP]2[/SUP], Hayes BQ[SUP]3[/SUP], Smith R[SUP]2,[/SUP][SUP]3[/SUP], Krewski D[SUP]1,[/SUP][SUP]2,[/SUP][SUP]4[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]Background:[/h] 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.
[h=4]Methods:[/h] 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.
[h=4]Results:[/h] 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; r[SUP]2[/SUP] = 0.7564) and ICU bed capacity (R = -0.8151; r[SUP]2[/SUP] = 0.6644), respectively. Demographic characteristics had mild associations with predicted pandemic consequences.
[h=4]Conclusion:[/h] 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.
[h=4]KEYWORDS:[/h] Canada; Differential equations; Mathematical modelling; Pandemic influenza; Surge capacity; Vaccination
PMID: 29928746 PMCID: PMC6002068 DOI: 10.1016/j.idm.2017.06.005