A Computer Simulation of Employee Vaccination to Mitigate an Influenza Epidemic

University of Pittsburgh, 200 Meyran Avenue, Pittsburgh, PA 15213, USA.
American journal of preventive medicine (Impact Factor: 4.53). 03/2010; 38(3):247-57. DOI: 10.1016/j.amepre.2009.11.009
Source: PubMed


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 (R(0)) epidemic, consistent with H1N1 parameters to date. Another set of scenarios represented a R(0)=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 (> or =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.

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    • "An agent-based model represented each individual person living in the state of Pennsylvania and was similar in design to previously described models of Allegheny County, Pennsylvania [8,23], and the Washington, DC metropolitan area [24,25]. The complete list of data sources appears in Table 1. "
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    ABSTRACT: Background States’ pandemic influenza plans and school closure statutes are intended to guide state and local officials, but most faced a great deal of uncertainty during the 2009 influenza H1N1 epidemic. Questions remained about whether, when, and for how long to close schools and about which agencies and officials had legal authority over school closures. Methods This study began with analysis of states’ school-closure statutes and pandemic influenza plans to identify the variations among them. An agent-based model of one state was used to represent as constants a population’s demographics, commuting patterns, work and school attendance, and community mixing patterns while repeated simulations explored the effects of variations in school closure authority, duration, closure thresholds, and reopening criteria. Results The results show no basis on which to justify statewide rather than school-specific or community-specific authority for school closures. Nor do these simulations offer evidence to require school closures promptly at the earliest stage of an epidemic. More important are criteria based on monitoring of local case incidence and on authority to sustain closure periods sufficiently to achieve epidemic mitigation. Conclusions This agent-based simulation suggests several ways to improve statutes and influenza plans. First, school closure should remain available to state and local authorities as an influenza mitigation strategy. Second, influenza plans need not necessarily specify the threshold for school closures but should clearly define provisions for early and ongoing local monitoring. Finally, school closure authority may be exercised at the statewide or local level, so long as decisions are informed by monitoring incidence in local communities and schools.
    BMC Public Health 11/2012; 12(1):977. DOI:10.1186/1471-2458-12-977 · 2.26 Impact Factor
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    • "Although focused on workplace vaccinations, Lee et al. [13,25] developed a decision model for the value of for employers and found that, depending on the serologic attack rate, cost-savings varied from $15-$995 to $39-$1,494 per vaccinated employee. Lee et al. focused more on the importance of immunizing employees as a component of pandemic planning, and thus used higher estimates of influenza incidence (15% – 25%) compared with our default range (4.1% – 5.5%). "
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    ABSTRACT: Although annual influenza vaccination could decrease the significant economic and humanistic burden of influenza in the United States, immunization rates are below recommended levels, and concerns remain whether immunization programs can be cost beneficial. The research objective was to compare cost benefit of various immunization strategies from employer, employee, and societal perspectives. An actuarial model was developed based on the published literature to estimate the costs and benefits of influenza immunization programs. Useful features of the model included customization by population age and risk-level, potential pandemic risk, and projection year. Various immunization strategies were modelled for an average U.S. population of 15,000 persons vaccinated in pharmacies or doctor's office during the 2011/12 season. The primary outcome measure reported net cost savings per vaccinated (PV) from the perspective of various stakeholders. Given a typical U.S. population, an influenza immunization program will be cost beneficial for employers when more than 37% of individuals receive vaccine in non-traditional settings such as pharmacies. The baseline scenario, where 50% of persons would be vaccinated in non-traditional settings, estimated net savings of $6 PV. Programs that limited to pharmacy setting ($31 PV) or targeted persons with high-risk comorbidities ($83 PV) or seniors ($107 PV) were found to increase cost benefit. Sensitivity analysis confirmed the scenario-based findings. Both universal and targeted vaccination programs can be cost beneficial. Proper planning with cost models can help employers and policy makers develop strategies to improve the impact of immunization programs.
    Cost Effectiveness and Resource Allocation 07/2012; 10(1):10. DOI:10.1186/1478-7547-10-10 · 0.87 Impact Factor
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    • "For example, when the initial R0 = 1.5 and 10% of the population is involved in a mass gathering event, the resulting peak prevalence and total attack rate are 2.89% and 51.4%, respectively, after a 2-day event starting on Day 60; however, these values are 2.80% and 51.1%, respectively, after a 3-day event starting at the same time. Note that the baseline average infectious period is 3-4 days (see Table 1); sensitivity analyses show results with infectious periods of 7-8 days [41,42]. Under the new assumption, when the initial R0 = 1.5, the total attack rate is 49.05% and the peak prevalence is 4.05% in the baseline scenario without traveling/mass gathering. "
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    ABSTRACT: During the 2009 H1N1 influenza pandemic, concerns arose about the potential negative effects of mass public gatherings and travel on the course of the pandemic. Better understanding the potential effects of temporal changes in social mixing patterns could help public officials determine if and when to cancel large public gatherings or enforce regional travel restrictions, advisories, or surveillance during an epidemic. We develop a computer simulation model using detailed data from the state of Georgia to explore how various changes in social mixing and contact patterns, representing mass gatherings and holiday traveling, may affect the course of an influenza pandemic. Various scenarios with different combinations of the length of the mass gatherings or traveling period (range: 0.5 to 5 days), the proportion of the population attending the mass gathering events or on travel (range: 1% to 50%), and the initial reproduction numbers R0 (1.3, 1.5, 1.8) are explored. Mass gatherings that occur within 10 days before the epidemic peak can result in as high as a 10% relative increase in the peak prevalence and the total attack rate, and may have even worse impacts on local communities and travelers' families. Holiday traveling can lead to a second epidemic peak under certain scenarios. Conversely, mass traveling or gatherings may have little effect when occurring much earlier or later than the epidemic peak, e.g., more than 40 days earlier or 20 days later than the peak when the initial R0 = 1.5. Our results suggest that monitoring, postponing, or cancelling large public gatherings may be warranted close to the epidemic peak but not earlier or later during the epidemic. Influenza activity should also be closely monitored for a potential second peak if holiday traveling occurs when prevalence is high.
    BMC Public Health 12/2010; 10(1):778. DOI:10.1186/1471-2458-10-778 · 2.26 Impact Factor
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