Informatics for empirically supported influenza pandemic control strategies

经验支持的流感大流行控制策略的信息学

• 批准号: 7295669
• 负责人: John S. Brownstein
• 金额: $ 20.51万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-30 至 2009-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7295669
• 关键词: Accounting; Address; Air; Antiviral Agents; Area; Avian Influenza A Virus; Basic Science; Censuses; Characteristics; Cities; Collection; Condition; Containment; Country; Data; Dependency; Diffuse; Disasters; Disease; Doctor of Philosophy; Domestic Fowls; Environmental Risk Factor; Epidemic; Event; Funding; Future; Geography; Graph; Health; Health care facility; Home environment; Individual; Infection; Infectious Agent; Influenza; Influenza A Virus, H5N1 Subtype; Informatics; Life; Maps; Measures; Medical Surveillance; Methods; Modeling; Monitor; Natural Disasters; Pathway interactions; Patient Monitoring System; Patients; Pattern; Pharmaceutical Preparations; Population; Population Density; Prevention; Prevention strategy; Process; Public Health; Readiness; Real-Time Systems; Recurrence; Research; Research Personnel; Resources; Risk; Risk Factors; Sentinel; Simulate; Socioeconomic Status; Southeastern Asia; System; Thinking; Time; Transportation; Travel; United States; Vaccination; Vaccines; Virus; Work; base; flu; flu activity; influenza epidemic; method development; metropolitan; network models; pandemic disease; pandemic influenza; population movement; programs; prospective; spatiotemporal; trend; urban area

DESCRIPTION (provided by applicant): Each year, a new influenza strain spreads across the nation, through cities interconnected by air and ground transportation. Consequently, there is potential for disastrous consequences, should an influenza pandemic strain emerge. In 1918, the "Spanish flu" pandemic claimed over 675,000 lives in the United States, and tens of millions worldwide. Because the last was in 1969, there is mounting concern over a recurrence; and the alarming spread of the H5N1 highly pathogenic avian influenza virus among poultry in Southeast Asia only heightens this concern. Surprisingly, there is little empirical data on how influenza spreads through cities, regions, nations and across the globe. Targeted prevention strategies could, however, be informed by enhanced understanding of local and large scale patterns. We will leverage an NLM-funded automated advanced disease surveillance system (AEGIS) to empirically measure the key determinants of influenza spread. Our first aim is to develop models of national influenza spread to inform public health preparedness strategies for epidemic and pandemic flu. We will model the national spread of the yearly influenza epidemic using network driven methods so as to understand the impact of multivariate factors, including population movement and environmental conditions. We will map the yearly pattern of spread and identify urban hubs that represent major network pathways. We expect to identify sentinel cities that should be the focus of control strategies which could include targeted vaccination, travel advisories, and flight bans. Our second aim is to develop spatial models of local influenza spread in metropolitan areas to identify targets for surveillance and control. We will develop empirically based spatial models of local influenza spread across major metropolitan areas and identify recurring hotspots of risk using surveillance data. We will exploit differences in spatial patterns of infection in major metropolitan areas to evaluate geographic and demographic risk factors that drive infection in different parts of the country. For both aims, our models and methods will be implemented in the AEGIS surveillance system for real-time monitoring of influenza activity. We will develop methods for effective linkage of influenza surveillance to prevention and control strategies. These methods have broad application for disaster preparedness for events caused by both naturally-occurring and deliberate introductions of infectious agents.

描述（由申请人提供）： 每年，一种新的流感毒株都会通过空中和地面交通相连的城市在全国范围内传播。因此，如果出现流感大流行毒株，可能会造成灾难性后果。 1918 年，“西班牙流感”大流行夺走了美国 675,000 多人的生命，全世界也夺去了数千万人的生命。 由于上一次发生在 1969 年，人们越来越担心这一事件会再次发生。 H5N1 高致病性禽流感病毒在东南亚家禽中的惊人传播加剧了这种担忧。 令人惊讶的是，关于流感如何在城市、地区、国家和全球范围内传播的实证数据很少。 然而，可以通过增强对当地和大规模模式的了解来制定有针对性的预防策略。 我们将利用 NLM 资助的自动化高级疾病监测系统 (AEGIS) 来凭经验测量流感传播的关键决定因素。 我们的首要目标是开发全国流感传播模型，为流行病和大流行性流感的公共卫生准备策略提供信息。 我们将使用网络驱动的方法对每年流感疫情的全国传播进行建模，以了解包括人口流动和环境条件在内的多变量因素的影响。 我们将绘制每年的传播模式，并确定代表主要网络路径的城市中心。 我们希望确定哨兵城市，作为控制策略的重点，其中可能包括有针对性的疫苗接种、旅行建议和飞行禁令。 我们的第二个目标是开发大都市区局部流感传播的空间模型，以确定监测和控制的目标。 我们将开发基于经验的本地流感在主要大都市区传播的空间模型，并利用监测数据确定反复出现的风险热点。 我们将利用主要大都市区感染空间模式的差异来评估导致全国不同地区感染的地理和人口风险因素。 为了实现这两个目标，我们的模型和方法将在 AEGIS 监测系统中实施，以实时监测流感活动。 我们将制定将流感监测与预防和控制战略有效联系起来的方法。 这些方法在自然发生和故意引入传染源引起的事件的防灾方面具有广泛的应用。

项目成果

Use of unstructured event-based reports for global infectious disease surveillance.

使用基于事件的非结构化报告进行全球传染病监测。

• 发表时间: 2009-05
• 影响因子: 11.8
• 作者: Keller, Mikaela;Blench, Michael;Tolentino, Herman;Freifeld, Clark C;Mandl, Kenneth D;Mawudeku, Abla;Eysenbach, Gunther;Brownstein, John S
• 通讯作者: Brownstein, John S

The new International Health Regulations: considerations for global public health surveillance.

新的国际卫生条例：全球公共卫生监测的考虑因素。

• 发表时间: 2007-11
• 作者: Sturtevant, Jessica L;Anema, Aranka;Brownstein, John S
• 通讯作者: Brownstein, John S

Breaking the news or fueling the epidemic? Temporal association between news media report volume and opioid-related mortality.

爆料还是助长疫情？

• 发表时间: 2009-11-18
• 影响因子: 3.7
• 作者: Dasgupta, Nabarun;Mandl, Kenneth D;Brownstein, John S
• 通讯作者: Brownstein, John S