Individual-based modelを用いた新型インフルエンザに対するワクチン接種対策の効果解析

抄録

Objectives: In this study, we aimed to evaluate vaccination strategies with regard to the impact of prioritization, coverage, and a delay in the vaccination program against a novel influenza pandemic with high-level fatality equivalent to Spanish flu using an individual-based model (IBM). Vaccination is one of the main measures to prevent infection, a serious condition, or death.
Methods: We constructed an IBM for the transmission of a novel influenza virus utilizing personal information on the basis of demographic data from Sapporo City, thereby resulting in a more realistic model. We designed simulations for scenarios along the guidelines of the Ministry of Health, Labour and Welfare of Japan, which requests the prioritization of vaccination of pregnant women and persons with underlying diseases, among whom influenza would cause higher fatality than among healthy persons, infants, or their parents, as well as school-aged and old-aged persons.
Results: A vaccination program fully taking into account the ordered priority groups would more effectively reduce the number of deaths in the priority groups and also the total number of deaths in comparison with a program shortening the transition time to the next priority or a non-priority group. A delay in the vaccination program would lower the effectiveness of reducing the numbers of patients and deaths.
Conclusions: According to the simulation-based results, when vaccination programs scheduled on the basis of priority groups start 90 and 150 days after outbreak, the total numbers of patients would be reduced to one-third–one-half, and two-thirds, respectively, in comparison with baseline of no vaccination, which leads to the necessity to conduct a vaccination program as soon as possible.