Abstract

Modeling is an important aspect of pandemic preparedness, and different approaches have been conducted to date. The epidemic dynamics and the assessment of containment or mitigation strategies, such as vaccination, border restriction, antiviral treatment of cases and prophylaxis of household or school/workplace contacts of index cases can be predicted by employing classical compartmental models [susceptible, exposed but not yet infectious, infectious, recovered and no longer susceptible (SEIR), possibly with age and/or geographic component]. Other authors have implemented the evaluation of realistic, individually targeted, public health intervention strategies that requires highly detailed models, such as the individual based model (IBM). According to the predictive models used, an influenza pandemic would spread worldwide over a period of 2–7 months, depending on the basic reproductive number (a measure on how many people an infectious individual infects on average), and reducing transmission would entail combining control measures, specifically, reducing contacts and performing both therapeutic and prophylactic use of antivirals and vaccination. International border restrictions are unlikely to delay the spread by more than 2–3 weeks unless more than 99% effective. Similar results were obtained for social distancing measures, such as school closure. Treatment of clinical cases and prophylaxis of close contacts can lower transmission, reducing the clinical attack rate by 40–50%, but it would be logistically challenging, requiring a stockpile for more than 25% of the population. Vaccine stockpiled in advance, even if less efficacious than pandemic vaccines, could significantly reduce the cumulative attack rates. In Italy, the combination of the described measures would lead to 10–15 million of cases being avoided, depending on vaccine effectiveness (taken as 50% or 70%). Mathematical models are necessary to plan and evaluate interventions based on different strategies. They represent a relevant tool to assist public health decision-making in preparing the response to a new influenza pandemic.

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