P3.3 Economic evaluation (Section 3)

Page last updated: September 2016

P3.3.1 Computational methods and structure for economic models of vaccines (Subsection 3A.2)

Time horizon of the model

Ensure that the duration of a model extends to the point where the estimate of cost-effectiveness is stable. Explain if herd immunity and community activity are involved, and follow a different pattern to other medicines, and ensure the information is well supported.

Present model traces (in Section 3) of the incremental cost-effectiveness ratio and key variables over time, to help assess the impact of varying the time horizon of the model. This may also help to assess the consequences of any waning or limited duration of vaccine effectiveness or herd immunity implications.

Structural assumptions and computational methods

State whether the model is static or dynamic, and justify the approach.

Use a static model when the force of infection (probability per unit of time that a susceptible person acquires infection) is constant over time. These are usually structured as decision analysis models or Markov models. Static models ignore herd immunity effects (see below).

A static model is appropriate where a small proportion of the population is to be vaccinated, either through low coverage or targeted vaccination, or the proposed vaccine does not prevent circulation of the pathogen, and herd immunity effects are expected to be negligible.

Use a dynamic model when the force of infection depends on the number of infectious individuals in the population at each time point and this number is expected to decline following immunisation. Dynamic models allow herd immunity and age shift to be assessed; use this model when the force of infection is likely to change after vaccination (ie if the proposed vaccine blocks transmission of infection and coverage is extensive), and when the risk or severity of the disease depends on age.

Joint analysis

A joint analysis includes analysis of changes in costs and outcomes associated with other medicines or vaccines. In this context, a joint analysis may be appropriate across all other affected vaccinations where the proposed vaccine may affect the cost of delivery or the coverage rate across multiple vaccinations. For example, this might apply when the proposed vaccine contains multiple components and could change the number of injections at one or more steps in the vaccination schedule.

P3.3.2 Population and circumstances in the model (Subsection 3A.3)

Ensure that the base-case population of the model reflects the primary population proposed for eligibility for the proposed vaccine, accounting for anticipated uptake patterns, if relevant. The population for vaccination would generally be considerably larger than (and not necessarily well reflected by any epidemiological data) the number of patients who acquire the disease.

To assess the evidence on effectiveness, consider the applicability of the baseline risk (population at risk) and the applicability of the disease pattern described by the evidence. Possible sources of epidemiological evidence include routine surveillance data, seroprevalence studies and surveys.

P3.3.3 Transition probabilities and variables (Subsection 3A.4)

Use a systematic basis to support key assumptions and variables relating to vaccine effectiveness, including:

• duration of vaccine effectiveness/waning effectiveness (eg include surveillance studies on the need for booster doses)
• herd immunity assumptions and implications (eg observational studies identifying level of coverage required to obtain some degree of herd immunity).

Present and assess these nonrandomised studies for extrapolation purposes separately.

P3.3.4 Translation of immunogenicity outcomes (Subsection 3A.4)

For the proposed vaccine, translating an immunogenicity outcome from a vaccine trial usually requires two separate analyses:

• Show that a threshold level of antibody response predicts a particular extent of protection, and thus a subsequent magnitude of reduction in cases of the disease presenting in each of one or more manifestations.
• Identify a limit to the duration of the effect or characterise waning of the effect over time.

Provide relevant regulatory standards for immunogenicity outcomes; however, these may not be sufficient to satisfy the requirements needed to map the direction and magnitude of a change in the surrogate immunogenicity outcome to the duration, magnitude and severity of one or more changes in subsequent clinical outcomes, for inclusion in an economic evaluation.

P3.3.5 Additional program costs (Subsection 3A.6)

Consider the following resources and costs specifically associated with an immunisation program listing:

• any required amendments to Australian immunisation registers, including the addition of new vaccine types or brands, and potential system changes relating to new or existing vaccine schedule points
• costs associated with delivery/changes to the delivery of the proposed vaccine through clinics, community centres and schools
• initiation or enhancement of a surveillance program for effectiveness and/or safety assessments (which may be requested or advised by ATAGI) as an essential component of funding the proposed vaccine under the NIP; include the costs of the resources for such a program.

Seek the advice of the department, particularly the Immunisation Policy Section, to identify relevant costs to include in the economic model.

P3.3.6 Validating the model (Subsection 3A.7)

The duration of effectiveness of a vaccine before any waning of effect, and the extent of any herd immunity are often particularly important factors in the economic evaluation of vaccines. Cross-reference supporting evidence presented in Section 3A.3 and look for any relevant external data that may provide additional evidence on the patterns of these matters over time. If additional external data incorporating these effects are identified during the validation process, it may be appropriate to recalibrate the model outputs based on such evidence.

P3.3.7 Sensitivity analyses (Subsection 3A.9)

Note that sensitivity analyses using alternative discount rates may be particularly relevant for cost-effectiveness models of vaccines.

Where catch-up programs are requested, present scenario analyses in Subsection 3A.9 to examine the effect on the base case if adding a catch-up program, extending the catch-up population and/or lengthening the duration of the catch-up program.