Trends in parameterization, economics and host behaviour in influenza pandemic modelling: a review and reporting protocol

Abstract

Background: The volume of influenza pandemic modelling studies has increased dramatically in the last decade. Many models incorporate now sophisticated parameterization and validation techniques, economic analyses and the behaviour of individuals.

Methods: We reviewed trends in these aspects in models for influenza pandemic preparedness that aimed to generate policy insights for epidemic management and were published from 2000 to September 2011, i.e. before and after the 2009 pandemic.

Results: We find that many influenza pandemics models rely on parameters from previous modelling studies, models are rarely validated using observed data and are seldom applied to low-income countries. Mechanisms for international data sharing would be necessary to facilitate a wider adoption of model validation. The variety of modelling decisions makes it difficult to compare and evaluate models systematically.

Conclusions: We propose a model Characteristics, Construction, Parameterization and Validation aspects protocol (CCPV protocol) to contribute to the systematisation of the reporting of models with an emphasis on the incorporation of economic aspects and host behaviour. Model reporting, as already exists in many other fields of modelling, would increase confidence in model results, and transparency in their assessment and comparison.

Figure 1

Literature review of pandemic influenza modelling papers. A: type of compartmental and non-compartmental models and parameterization approaches used. B: cumulative number of modelling and simulation papers identified from 2000 to 2011 (left axis) and number of hits retrieved on PubMed for the query: “pandemic AND influenza” (right axis). This search is used as a surrogate for general research interest in pandemic influenza. C: proportion of models incorporating economic aspects, individuals’ behaviour, parameterization from data other than reproducing parameter value choices in previous studies and validation. ABM: agent-based model; CGE: computable or general equilibrium model; Epi. lab. case data: models are fitted to epidemiological, laboratory or case data.