The updated Italian national plan for preparedness and response to an influenza pandemic was published in February 2006 [1], in response to recommendations and checklists on national influenza pandemic preparedness plans issued by the World Health Organization [2].
The Italian plan includes the following preventive measures:

To evaluate the impact of these preventive measures on the national population, a mathematical model was developed by a working group that included researchers from the Universities of Trento, Pisa and Rome, and the National Institute of Health (Istituto Superiore di sanità, ISS) The results were published in an ISS report in December 2006 [3] and are summarised here.

Modelling pandemic influenza transmission and control measures
A SEIR (susceptible; infected but not infectious; infectious; resistent, that is, immune to re-infection) deterministic model, with a stochastic simulation component was used. An R₀ (the basic reproductive number) of 1.8 was assumed, with a cumulative attack rate (AR) of 35% [4].

We modelled the impact of vaccination, antiviral prophylaxis and measures aimed to increase social distancing. For each measure, various scenarios were considered, assuming different target populations and duration of interventions [3].

As standard parameters, we considered that the target population would receive the first dose of vaccine 12 weeks after the onset of the index case in Italy, and the second dose four weeks after that. This two dose cycle was assumed to be 70% effective, starting 15 days after the administration of the second dose. Vaccine coverage was fixed at 60%.

Antiviral prophylaxis of uninfected individuals was assumed to reduce susceptibility to infection by 30% [5]. We supposed that only household contacts of influenza cases would be treated, limiting the use of antiviral prohlylaxis to a maximum of 8 weeks after the onset of illness in the index case.

School closure lasting 3 weeks was assumed to start 2, 4, or 8 weeks after the onset of the index case. As the same time, it was assumed that public offices not providing essential services would be closed for 4 weeks, and recreational venues such as theatres and cinemas, for 8 weeks.

Results
In absence of control measures, the epidemic peak would be reached approximately 4 months after the first case onset, with a total of 3 million cases during the peak week. The epidemic would be over in 7 months, with a cumulative attack rate of 35% (approximately 20 million cases).

The interventions considered, when implemented singly, would reduce the cumulative attack rate to, at best, approximately 32% (vaccination only). Using either prophylaxis with antiviral drugs or social distancing measures alone would have no effect in reducing the cumulative AR, but would delay the epidemic peak by approximately one and three weeks, respectively.

Multiple interventions involving vaccination, antiviral prophylaxis and social distancing measures, would reduce the cumulative attack rate to 20% at a minimum [range: 20% - 24%], with 8 millions cases avoided.

Conclusions
Modelling results confirm the need to respond to a pandemic with multiple preventive measures [6-8]. None of the interventions looked at is highly effective when implemented independently.

These results, which evaluated interventions included in the national prepardness plan, also show that preparedness is crucial, in order to organise all the control measures necessary to face an emergency. Timing is also essential, and measures which at first glance appear to be less important, such as increasing social distancing, could be extremely useful for delaying the epidemic peak, allowing time for greater availability of a vaccine, and thus optimising its impact.

The implementation of multiple measures, including closure of schools and workplaces requires the involvment of various medical and non-medical structures. It is therefore essential to properly communicate them the importance of such actions. Mathematical modelling based on national data are a relevant tool to assist public health decisors in preparing for responding to a new influenza pandemic.