BACKGROUND: @entity683 pandemics result in excess mortality and social disruption. To assist health authorities update the French pandemic plan, the authors estimated the number of @entity283 (cases, hospitalisations, and @entity204 ) in a pandemic and compared interventions in terms of impact and efficiency. METHOD: A Monte Carlo simulation model, incorporating probability distributions of key variables, provided estimates of @entity283 ( @entity283 ) by age and risk group. Input variables were set after literature and expert consultation. The impact of targeted @entity683 vaccination and antiviral prophylaxis/treatment ( @entity684 ) in high risk groups (elderly, @entity102 ), priority (essential professionals), and total populations was compared. Outcome measures were @entity283 avoided, number of doses needed, and direct cost per @entity283 avoided. RESULTS: Without intervention, an @entity683 pandemic could result in 14.9 million cases, 0.12 million @entity204 , and 0.6 million hospitalisations in France. Twenty four per cent of @entity204 and 40% of hospitalisations would be among high risk groups. With a 25% attack rate, 2000-86,000 @entity204 could be avoided, depending on population targeted and intervention. If available initially, vaccination of the total population is preferred. If not, for priority populations, seasonal prophylaxis seems the best strategy. For high risk groups, antiviral treatment, although less effective, seems more feasible and cost effective than prophylaxis (respectively 29% @entity204 avoided; 1800 doses/death avoided and 56% @entity204 avoided; 18,500 doses/death avoided) and should be chosen, especially if limited drug availability. CONCLUSION: The results suggest a strong role for antivirals in an @entity683 pandemic. While this model can compare the impact of different intervention strategies, there remains uncertainty surrounding key variables.

XXXX pandemic preparedness in France: modelling the impact of interventions.

@entity684 :: ('MESH:D053139', 'Chemical') :: ['oseltamivir'] @entity283 :: ('OMIM:603663', 'Disease') :: ['HE', 'health events'] @entity102 :: ('MESH:D002908', 'Disease') :: ['chronic diseases'] @entity683 :: ('MESH:D007251', 'Disease') :: ['influenza', 'Influenza'] @entity204 :: ('MESH:D003643', 'Disease') :: ['deaths']
@entity683 :: (MESH:D007251,Disease) :: ['Influenza']
