Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom, Department of Medical Microbiology, University Medical Center Groningen, University of Groningen, Groningen, 9713 GZ, The Netherlands, Center for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, 3721 MA, The Netherlands, and Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, 3584 CX, The Netherlands.
Proc Natl Acad Sci U S A. 2014 Feb 11;111(6):2271-6. doi: 10.1073/pnas.1308062111. Epub 2014 Jan 27.
Early detection of new or novel variants of nosocomial pathogens is a public health priority. We show that, for healthcare-associated infections that spread between hospitals as a result of patient movements, it is possible to design an effective surveillance system based on a relatively small number of sentinel hospitals. We apply recently developed mathematical models to patient admission data from the national healthcare systems of England and The Netherlands. Relatively short detection times are achieved once 10-20% hospitals are recruited as sentinels and only modest reductions are seen as more hospitals are recruited thereafter. Using a heuristic optimization approach to sentinel selection, the same expected time to detection can be achieved by recruiting approximately half as many hospitals. Our study provides a robust evidence base to underpin the design of an efficient sentinel hospital surveillance system for novel nosocomial pathogens, delivering early detection times for reduced expenditure and effort.
早期发现医院感染病原体的新或新型变体是公共卫生的重点。我们表明,对于由于患者移动而在医院之间传播的与医疗保健相关的感染,可以设计一种基于相对较少的监测医院的有效监测系统。我们将最近开发的数学模型应用于来自英国和荷兰国家卫生保健系统的患者入院数据。一旦招募了 10-20%的医院作为监测站,就可以实现相对较短的检测时间,此后招募更多的医院只会看到适度的减少。使用监测站选择的启发式优化方法,可以通过招募大约一半的医院来实现相同的预期检测时间。我们的研究为设计用于新型医院病原体的高效监测医院监测系统提供了可靠的证据基础,为减少支出和努力提供了早期检测时间。