Academic journal article Bulletin of the World Health Organization

Population-Based Simulations of Influenza Pandemics: Validity and Significance for Public Health policy/Simulations En Population D'une Pandemie De Grippe: Validite et Signification Pour Les Politiques De Sante publique/Simulaciones Poblacionales De Las Pandemias De Gripe: Validez E Importancia Para Las Politicas De Salud Publica

Academic journal article Bulletin of the World Health Organization

Population-Based Simulations of Influenza Pandemics: Validity and Significance for Public Health policy/Simulations En Population D'une Pandemie De Grippe: Validite et Signification Pour Les Politiques De Sante publique/Simulaciones Poblacionales De Las Pandemias De Gripe: Validez E Importancia Para Las Politicas De Salud Publica

Article excerpt

Introduction

By 2006, many countries had responded to WHO initiatives to update contingency plans to mitigate the consequences of an influenza pandemic. However, some general concerns arose in connection with these national plans, (1,2) as it became clear that there would be a shortage of antiviral drugs and vaccine (3) and that a pandemic would place new demands on public health information systems. At the global level, WHO's Global Influenza Surveillance Network (FluNet) collects and processes influenza data from 83 countries, (4) but at the national level few public health surveillance systems can either detect pandemic outbreaks or warn relevant agencies and the public. This inadequacy persists despite a 2005 report to the Government of the United States of America (USA) that identified public health information systems as a priority area for restructuring and investment to secure preparedness for pandemics and bioterrorist attacks. (5) The development of a National Health Information Infrastructure in the USA had, at the time of the 2005 report, been proposed to detect atypical patterns of health-care use and to provide essential health information to citizens. (6) This recommendation, however, has not translated into widespread practice, and many health information infrastructure projects remain in the planning stages.

Given that surveillance systems for collecting and analysing pandemic data are not sufficiently robust as a resource for policy planning and decision-making, attention has shifted towards computer-based simulation models. Using artificially generated community models as a basis, workers have forecast the effectiveness of different intervention strategies for containing or delaying the influenza pandemic at its expected source (e.g. rural south-east Asia). Longini et al. (7) found that if the basic reproductive number ([R.sub.0])--the average number of secondary cases that a single case is expected to produce while still infectious in a completely susceptible population--was below 1.60, a prepared response with targeted antiviral drugs would have a high probability of containing the disease. When prevaccination was introduced into the model, targeted antiviral prophylaxis was found to contain an outbreak with an [R.sub.0] as high as 2.1. Addressing the same research question, but using an individual-based stochastic simulation model, Ferguson et al. (8) reported that a combination of geographically targeted prophylaxis and social distancing measures is feasible only if the [R.sub.0] is below 1.8. Simulation studies have also included international air transportation patterns in the analyses of the early phases of a pandemic. Colizza et al. (9) reported that the large-scale therapeutic use of antiviral drugs in all affected countries would mitigate a pandemic effect with an [R.sub.0] as high as 1.9 during the first year, if one assumes the antiviral drug supply is sufficient to treat approximately 2-6% of the population and that case detection and drug distribution are efficient. More recently, methods for representing specific social-contact networks in analyses of local influenza transmission have been developed. Using artificially generated social networks grounded in typical American community structures in their analyses, Glass & Glass (10) have suggested that high-school students may form the local transmission backbone of the next pandemic. Therefore, closing schools and keeping students at home during a pandemic would remove the transmission potential in these age groups and could effectively thwart subsequent spread of the disease within a community.

In the absence of reliable pandemic detection systems, computer-based simulations have become an important information tool for both policy-makers and the general public. In this study we examine the validity and usefulness of population-based pandemic simulations from a national-level public health perspective. Specifically, we assess a simulated pandemic influenza outbreak in a Scandinavian community using a non-statistical nominal group technique. …

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