TRA1-5 AN INFUENZA VACCINATION POLICY BASED ON A PREVIOUS YEAR'S ILLNESS

Thursday, October 18, 2012: 11:42 AM
Regency Ballroom A/B (Hyatt Regency)
Health Services, and Policy Research (HSP)

Dan Yamin, MSc1, Arieh Gavious, PhD1, Eyal Solnik, BSc2, Nadav Davidovitch, MD, PhD3 and Joseph S. Pliskin, PhD4, (1)Ben Gurion University of the Negev, Beer Sheva, Israel, (2)Ben Gurion University of the Negev, Beer-Sheva, Israel, (3)Ben-Gurion University of the Negev, Beer Sheva, Israel, (4)Ben-Gurion University of the Negev, Be'er-Sheva, Israel

Purpose: Vaccination is the most efficient and cost effective method to prevent influenza, reducing morbidity and mortality rates not only for those vaccinated, but also for the entire population by reducing the spread of the virus. In the context of contact network epidemiology, an individual who is located in the center of the network is more likely to become infected. Thus, vaccinating such individuals before others would be more efficient in reducing the influenza burden.

Method: We offer a practical way to identify the central people by using accessible data; we show that immunizing those who have been infected in the previous season, especially before the peak of the disease, can substantially reduce infection rates for a wide range of influenza viruses. It is achieved by running 2.1 million computerized simulations. Using the Susceptible Infected Recovered (SIR) compartmental model, each simulation reflected two successive influenza seasons over a 1.5 million population contact network based on the Portland population. The second season in each simulation was checked twice: when a Random Vaccination Policy (RVP) was applied and when using a vaccination policy prioritizing first those who were infected in the previous season especially before the peak (PFIP). The number of infected individuals in the two policies (RVP&PFIP) was calculated to determine the conditions where one policy is preferred to another.

Result: Results suggest that when no vaccination is offered, individuals who became infected in the previous season have a higher probability of becoming infected in the following season. Accordingly, PFIP can reduce the number of infected by up to 80% compared to RVP. Moreover, even if the cross-antigenisity rate between the viruses of two seasons is as high as 60-80%, a policy prioritizing those who became ill in the previous season is superior. We provide a simple managerial tool describing the conditions when each policy should be used.

Conclusion: No CDC recommendations have ever considered the effect of a previous season on an individual in determining a future vaccination policy for him. On a practical basis, applying the PFIP can be achieved easily by sending pamphlets, telephone reminders or even family doctor recommendations to those who were diagnosed by the family doctor as suffering from influenza like illness (ILI) in the previous season.