A computer simulation of employee vaccination to mitigate an influenza epidemic.
A computer simulation of employee vaccination to mitigate an influenza epidemic.
复制标题
DOI:
10.1016/j.amepre.2009.11.009
复制
发表时间:
2010-03
影响因子:
5.5
通讯作者:
Burke DS
中科院分区:
文献类型:
--
作者:
Lee BY;Brown ST;Cooley PC;Zimmerman RK;Wheaton WD;Zimmer SM;Grefenstette JJ;Assi TM;Furphy TJ;Wagener DK;Burke DS
Determining the effects of varying vaccine coverage, compliance, administration rates, prioritization, and timing among employees during an influenza pandemic. As part of the Models of Infectious Disease Agent Study (MIDAS) network’s H1N1 influenza planning efforts, an agent-based computer simulation model (ABM) was developed of 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. While vaccinating Advisory Committee on Immunization Practices (ACIP) 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. While 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 Metro 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 all workplaces. Timely vaccination of at least 20% of the large company workforce can play an important role in epidemic mitigation.
登录
查看更多内容
DOI:
10.1073/pnas.0706849105
发表时间:
2008-03-25
影响因子:
11.1
作者:
Halloran, M. Elizabeth;Ferguson, Neil M.;Cooley, Philip
通讯作者:
Cooley, Philip
影响因子:
5.9
作者:
Rothberg, MB;Rose, DN
通讯作者:
Rose, DN
DOI:
10.1073/pnas.0601266103
发表时间:
2006-04-11
影响因子:
11.1
作者:
Germann, TC;Kadau, K;Macken, CA
通讯作者:
Macken, CA
影响因子:
64.8
作者:
Cauchemez, Simon;Valleron, Alain-Jacques;Ferguson, Neil M.
通讯作者:
Ferguson, Neil M.
DOI:
10.1016/0965-8564(96)00004-3
发表时间:
1996-11-01
影响因子:
6.4
作者:
Beckman, RJ;Baggerly, KA;McKay, MD
通讯作者:
McKay, MD