APPENDIX

Description of the “no herd immunity” scenario

In order to explore a scenario which excluded herd effects from our transmission model, we modified the Susceptible Exposed Infectious Recovered (SEIR) model so that vaccine effects were applied only to clinical outcomes (i.e. vaccination does not change the force of infection). This required recalibration of the model to health outcome data as the herd effects from the existing program also had to be removed and consequently slight changes in the age-specific attack rates under current practice.The resulting model equations are as follows:

Here, SEIR are population groups corresponding to number of Susceptible, Exposed, Infected, Recovered individuals respectively; the labels , and , and denote age group, vaccination status (unvaccinated and vaccinated), symptomatic and asymptomatic status, respectively; is the internal (imported) force of infection; is the latent period (basecase: 1 day); is the proportion of asymptomatic infections (basecase: 65%); is the recovery rate (basecase: 0.5 per day); and is the vaccine efficacy. A more detailed description of all the model parameters can be found in Newall et. al1.

References

1. Newall AT, Dehollain JP, Wood J. Under-explored assumptions in influenza vaccination models: Implications for the universal vaccination of children Vaccine 2012;30(39):5776-81.

*Average number of days after being exposed and before becoming infectious

^ Average number of days a person remains infectious

Figure A1.

One-way sensitivity analysis of school-based vaccination compared to current practice, with (top) and without (bottom) herd immunity. All parameters were varied between 75% (light bars) and 125% (dark bars) of base-case value. The results are shown for the alternative perspectives, healthcare and societal.

Table A1. Model predicted current practice clinical attack rates (CAR) and attack rates by age-group*

Age-group / CAR / Attack rates
0-4 / 5.0% / 14.3%
5-9 / 7.8% / 22.3%
10-14 / 9.7% / 27.7%
15-17 / 9.6% / 27.4%
18-19 / 8.7% / 24.9%
20-24 / 6.4% / 18.3%
25-29 / 6.3% / 17.9%
30-34 / 6.7% / 19.1%
35-39 / 6.9% / 19.7%
40-44 / 6.9% / 19.8%
45-49 / 6.3% / 17.9%
50-54 / 6.1% / 17.4%
55-59 / 5.1% / 14.5%
60-64 / 4.2% / 12.1%
65-69 / 4.0% / 11.4%
70-74 / 3.0% / 8.6%
75-79 / 3.0% / 8.6%
80-84 / 3.0% / 8.6%
85+ / 3.0% / 8.6%

*These attack rates and CAR were calculated over simulations with R distributed as lognormal distribution (μ=0.2429, σ=0.2).

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Table A2. Age-specific parameter values used in the model

Age-group / 0-4 / 5-9 / 10-14 / 15-19 / 20-24 / 25-29 / 30-34 / 35-39 / 40-44 / 45-49 / 50-54 / 55-59 / 60-64 / 65-69 / 70-74 / 75-79 / 80-84 / 85+
Influenza death rate per 100,000 / 0.194 / 0.064 / 0.064 / 0.027 / 0.027 / 0.028 / 0.028 / 0.028 / 0.028 / 0.028 / 0.600 / 0.600 / 0.600 / 17.600 / 17.600 / 17.600 / 17.600 / 17.600
Influenza hospitalisation rate per 100,000 / 105.8 / 11.3 / 11.3 / 16.3 / 16.3 / 16.3 / 16.3 / 16.3 / 16.3 / 16.3 / 33.3 / 33.3 / 33.3 / 83.8 / 83.8 / 202.4 / 202.4 / 378.2
General practitioner visits rate per 100,000 / 1085.6 / 975.0 / 975.0 / 2054.4 / 2054.4 / 2054.4 / 2054.4 / 2054.4 / 2054.4 / 1476.0 / 1476.0 / 1476.0 / 1476.0 / 1058.1 / 1058.1 / 899.3 / 899.3 / 899.3
Discounted QALY loss from influenza death / 16.9 / 16.7 / 16.5 / 16.4 / 16.0 / 15.6 / 15.2 / 14.7 / 14.0 / 13.2 / 12.3 / 11.4 / 10.3 / 8.9 / 7.4 / 5.9 / 4.5 / 3.0
Cost per day of absenteeism (A$) / 0.00 / 0.00 / 0.00 / 58.50 / 134.58 / 185.38 / 212.09 / 232.03 / 243.90 / 237.11 / 220.30 / 195.95 / 140.09 / 64.02 / 12.37 / 12.37 / 12.37 / 12.37
Hospitalisation cost (A$per episode) / 2919 / 3036 / 3036 / 4401 / 4401 / 4401 / 4401 / 4401 / 4401 / 4401 / 6102 / 6102 / 6102 / 7343 / 7343 / 8678 / 8678 / 9486

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