Population-based simulations of influenza pandemics: validity and significance for public health policy

Abstract

OBJECTIVE: To examine the validity and usefulness of pandemic simulations aimed at informing practical decision-making in public health. METHODS: We recruited a multidisciplinary group of nine experts to assess a case-study simulation of influenza transmission in a Swedish county. We used a non-statistical nominal group technique to generate evaluations of the plausibility, formal validity (verification) and predictive validity of the simulation. A health-effect assessment structure was used as a framework for data collection. FINDINGS: The unpredictability of social order during disasters was not adequately addressed by simulation methods; even minor disruptions of the social order may invalidate key infrastructural assumptions underpinning current pandemic simulation models. Further, a direct relationship between model flexibility and computation time was noted. Consequently, simulation methods cannot, in practice, support integrated modifications of microbiological, epidemiological and spatial submodels or handle multiple parallel scenarios. CONCLUSION: The combination of incomplete surveillance data and simulation methods that neglect social dynamics limits the ability of national public health agencies to provide policy-makers and the general public with the critical and timely information needed during a pandemic.