tetano
Editor, Senior Moderator
J Theor Biol. 2019 Jul 19. pii: S0022-5193(19)30288-7. doi: 10.1016/j.jtbi.2019.07.011. [Epub ahead of print]
[h=1]Prioritization of vaccine strategy using an age-dependent mathematical model for 2009 A/H1N1 influenza in the Republic of Korea.[/h] Kim S[SUP]1[/SUP], Jung E[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] We developed a mathematical model of the 2009 A/H1N1 influenza epidemic in the Republic of Korea by considering five age groups and suggested the best way to prioritize an age-dependent vaccination strategy for mitigating the epidemic. An age-structured SEIAR influenza model was constructed based on the laboratory confirmed data obtained from the Korea Centers for Disease Control and Prevention (KCDC). The estimated transmission matrix captured one of the main characteristics of the 2009 A/H1N1 influenza, the transmission rate of which is high among young people, unlike that of seasonal influenza. We investigated the impact of age-dependent vaccination priority on the transmission dynamics of the 2009 A/H1N1 influenza and evaluated the Korean government vaccination policy when the vaccination started being administered 90 days (or 120 days) after the onset of the outbreak. We found that the government's age priority vaccination policy (Group 2, Group 1, Group 5, Group 4, and Group 3 in order) was a good strategy for reducing 62.06% of the cumulative cases when the vaccination was applied 90 days after the onset of the outbreak, while the proposed model's best suggestion (Group 2, Group 1, Group 3, Group 4, and Group 5 in order) showed 64.52% reduction. Furthermore, we studied the region-specific vaccination policy. For instance, the best age-priority of vaccination in Gwangwon province showed a different order (Group 3, Group 1, Group 2, Group 4, and Group 5 in order) and it reduced the incidence by 58.1%, which is 5.54% higher than that of the 2009 Korean government policy.
Copyright ? 2019. Published by Elsevier Ltd.
[h=4]KEYWORDS:[/h] Age-priority of vaccination; Age-structured model; Influenza Epidemic; Parameter estimation; Region-specific vaccine strategy
PMID: 31330133 DOI: 10.1016/j.jtbi.2019.07.011
[h=1]Prioritization of vaccine strategy using an age-dependent mathematical model for 2009 A/H1N1 influenza in the Republic of Korea.[/h] Kim S[SUP]1[/SUP], Jung E[SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] We developed a mathematical model of the 2009 A/H1N1 influenza epidemic in the Republic of Korea by considering five age groups and suggested the best way to prioritize an age-dependent vaccination strategy for mitigating the epidemic. An age-structured SEIAR influenza model was constructed based on the laboratory confirmed data obtained from the Korea Centers for Disease Control and Prevention (KCDC). The estimated transmission matrix captured one of the main characteristics of the 2009 A/H1N1 influenza, the transmission rate of which is high among young people, unlike that of seasonal influenza. We investigated the impact of age-dependent vaccination priority on the transmission dynamics of the 2009 A/H1N1 influenza and evaluated the Korean government vaccination policy when the vaccination started being administered 90 days (or 120 days) after the onset of the outbreak. We found that the government's age priority vaccination policy (Group 2, Group 1, Group 5, Group 4, and Group 3 in order) was a good strategy for reducing 62.06% of the cumulative cases when the vaccination was applied 90 days after the onset of the outbreak, while the proposed model's best suggestion (Group 2, Group 1, Group 3, Group 4, and Group 5 in order) showed 64.52% reduction. Furthermore, we studied the region-specific vaccination policy. For instance, the best age-priority of vaccination in Gwangwon province showed a different order (Group 3, Group 1, Group 2, Group 4, and Group 5 in order) and it reduced the incidence by 58.1%, which is 5.54% higher than that of the 2009 Korean government policy.
Copyright ? 2019. Published by Elsevier Ltd.
[h=4]KEYWORDS:[/h] Age-priority of vaccination; Age-structured model; Influenza Epidemic; Parameter estimation; Region-specific vaccine strategy
PMID: 31330133 DOI: 10.1016/j.jtbi.2019.07.011