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Public health surveillance data in North Carolina.北卡罗来纳州的公共卫生监测数据。
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Modeling the worldwide spread of pandemic influenza: baseline case and containment interventions.模拟大流行性流感的全球传播:基线病例与遏制干预措施。
PLoS Med. 2007 Jan;4(1):e13. doi: 10.1371/journal.pmed.0040013.
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Epidemiology of seasonal influenza: use of surveillance data and statistical models to estimate the burden of disease.季节性流感的流行病学:利用监测数据和统计模型评估疾病负担
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An object simulation model for modeling hypothetical disease epidemics - EpiFlex.一种用于模拟假设疾病流行情况的对象模拟模型——EpiFlex。
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A susceptible-infected model of early detection of respiratory infection outbreaks on a background of influenza.一种在流感背景下早期检测呼吸道感染暴发的易感-感染模型。
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Modeling the spread of annual influenza epidemics in the U.S.: the potential role of air travel.模拟美国年度流感疫情的传播:航空旅行的潜在作用。
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Changing geographic access to and locational efficiency of health services in two Indian districts between 1981 and 1996.1981年至1996年间印度两个地区医疗服务的地理可及性和区位效率变化
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9
Mortality associated with influenza and respiratory syncytial virus in the United States.美国与流感和呼吸道合胞病毒相关的死亡率。
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优化州级流感哨点监测。

Optimizing influenza sentinel surveillance at the state level.

作者信息

Polgreen Philip M, Chen Zunqui, Segre Alberto M, Harris Meghan L, Pentella Michael A, Rushton Gerard

机构信息

Division of Infectious Diseases, Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, Iowa 52242, USA.

出版信息

Am J Epidemiol. 2009 Nov 15;170(10):1300-6. doi: 10.1093/aje/kwp270. Epub 2009 Oct 12.

DOI:10.1093/aje/kwp270
PMID:19822570
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2800268/
Abstract

Influenza-like illness data are collected via an Influenza Sentinel Provider Surveillance Network at the state level. Because participation is voluntary, locations of the sentinel providers may not reflect optimal geographic placement. The purpose of this study was to determine the "best" locations for sentinel providers in Iowa by using a maximal coverage model (MCM) and to compare the population coverage obtained with that of the current sentinel network. The authors used an MCM to maximize the Iowa population located within 20 miles (32.2 km) of 1-143 candidate sites and calculated the coverage provided by each additional site. The first MCM location covered 15% of the population; adding a second increased coverage to 25%. Additional locations provided more coverage but with diminishing marginal returns. In contrast, the existing 22 Iowa sentinel locations covered 56% of the population, the same coverage achieved with just 10 MCM sites. Using 22 MCM sites covered more than 75% of the population, an improvement over the current site placement, adding nearly 600,000 Iowa residents. Given scarce public health resources, MCMs can help surveillance efforts by prioritizing recruitment of sentinel locations.

摘要

流感样疾病数据通过州级流感哨点医疗机构监测网络收集。由于参与是自愿的,哨点医疗机构的位置可能无法反映最佳的地理布局。本研究的目的是使用最大覆盖模型(MCM)确定爱荷华州哨点医疗机构的“最佳”位置,并将获得的人群覆盖范围与当前哨点网络的覆盖范围进行比较。作者使用MCM来最大化位于1 - 143个候选地点20英里(32.2公里)范围内的爱荷华州人口,并计算每个新增地点提供的覆盖范围。第一个MCM地点覆盖了15%的人口;增加第二个地点后,覆盖范围增加到25%。额外的地点提供了更多的覆盖范围,但边际收益递减。相比之下,爱荷华州现有的22个哨点地点覆盖了56%的人口,这与仅10个MCM地点所达到的覆盖范围相同。使用22个MCM地点覆盖了超过75%的人口,比当前的地点布局有所改善,增加了近60万爱荷华州居民。鉴于公共卫生资源稀缺,MCM可以通过优先招募哨点地点来帮助监测工作。