A computer simulation of employee vaccination to mitigate an influenza epidemic
Better understanding the possible effects of vaccinating employees is important and can help policymakers and businesses plan vaccine distribution and administration logistics, especially with the current H1N1 influenza vaccine in short supply.
This article aims to determine the effects of varying vaccine coverage, compliance, administration rates, prioritization, and timing among employees during an influenza pandemic.
As part of the H1N1 influenza planning efforts of the Models of Infectious Disease Agent Study network, an agent-based computer simulation model was developed for the Washington DC metropolitan region, encompassing five metropolitan statistical areas. Each simulation run involved introducing 100 infectious individuals to initiate a 1.3 reproductive-rate (R0) epidemic, consistent with H1N1 parameters to date. Another set of scenarios represented a R0=1.6 epidemic.
An unmitigated epidemic resulted in substantial productivity losses (a mean of $112.6 million for a serologic 15% attack rate and $193.8 million for a serologic 25% attack rate), even with the relatively low estimated mortality impact of H1N1. Although vaccinating Advisory Committee on Immunization Practices–defined priority groups resulted in the largest savings, vaccinating all remaining workers captured additional savings and, in fact, reduced healthcare workers' and critical infrastructure workers' chances of infection. Moreover, although employee vaccination compliance affected the epidemic, once 20% compliance was achieved, additional increases in compliance provided less incremental benefit. Even though a vast majority of the workplaces in the DC metropolitan region had fewer than 100 employees, focusing on vaccinating only those in larger firms (?100 employees) was just as effective in mitigating the epidemic as trying to vaccinate employees in all workplaces.
Timely vaccination of at least 20% of the large-company workforce can play an important role in epidemic mitigation.