Moore Melinda, Chan Edward, Lurie Nicole, Schaefer Agnes Gereben, Varda Danielle M, Zambrano John A
Health Unit, RAND Corporation, Arlington, Virginia, USA.
BMC Public Health. 2008 May 28;8:186. doi: 10.1186/1471-2458-8-186.
Global pandemic influenza preparedness relies heavily on public health surveillance, but it is unclear that current surveillance fully meets pandemic preparedness needs.
We first developed a conceptual framework to help systematically identify strategies to improve the detection of an early case or cluster of novel human influenza disease during the pre-pandemic period. We then developed a process model (flow diagram) depicting nine major pathways through which a case in the community could be detected and confirmed, and mapped the improvement strategies onto this model. Finally, we developed an interactive decision tool by building quantitative measures of probability and time into each step of the process model and programming it to calculate the net probability and time required for case detection through each detection pathway. Input values for each step can be varied by users to assess the effects of different improvement strategies, alone or in combination. We illustrate application of the tool using hypothetical input data reflecting baseline and 12-month follow-up scenarios, following concurrent implementation of multiple improvement strategies.
We compared outputs from the tool across detection pathways and across time, at baseline and 12-month follow up. The process model and outputs from the tool suggest that traditional efforts to build epidemiology and laboratory capacity are efficient strategies, as are more focused strategies within these, such as targeted laboratory testing; expedited specimen transport; use of technologies to streamline data flow; and improved reporting compliance. Other promising strategies stem from community detection - better harnessing of electronic data mining and establishment of community-based monitoring.
Our practical tool allows policymakers to use their own realistic baseline values and program projections to assess the relative impact of different interventions to improve the probability and timeliness of detecting early human cases or clusters caused by a novel influenza virus, a possible harbinger of a new pandemic. Policymakers can use results to target investments to improve their surveillance infrastructure. Multi-national planners can also use the tool to help guide directions in surveillance system improvements more globally. Finally, our systematic approach can also be tailored to help improve surveillance for other diseases.
全球大流行性流感防范在很大程度上依赖于公共卫生监测,但目前的监测是否完全满足大流行防范需求尚不清楚。
我们首先构建了一个概念框架,以帮助系统地确定在大流行前期提高对新型人类流感疾病早期病例或病例群检测能力的策略。然后,我们开发了一个流程模型(流程图),描绘了社区中病例得以检测和确诊的九条主要途径,并将改进策略映射到该模型上。最后,我们通过在流程模型的每个步骤中纳入概率和时间的定量度量,并对其进行编程以计算通过每条检测途径检测病例所需的净概率和时间,从而开发了一个交互式决策工具。用户可以改变每个步骤的输入值,以单独或组合评估不同改进策略的效果。我们使用反映基线和12个月随访情况的假设输入数据,展示了在同时实施多种改进策略后该工具的应用情况。
我们在基线和12个月随访时,比较了该工具在不同检测途径和不同时间的输出结果。流程模型和该工具的输出结果表明,传统的加强流行病学和实验室能力的努力是有效的策略,其中更具针对性的策略,如靶向实验室检测、加快标本运输、利用技术简化数据流以及提高报告依从性等也是有效的。其他有前景的策略源于社区检测——更好地利用电子数据挖掘和建立基于社区的监测。
我们的实用工具使政策制定者能够使用他们自己现实的基线值和项目预测,来评估不同干预措施对提高检测新型流感病毒引起的早期人类病例或病例群的概率和及时性的相对影响,而新型流感病毒可能是新的大流行的先兆。政策制定者可以利用结果来确定投资方向,以改善其监测基础设施。多国规划者也可以使用该工具,在更全球范围内帮助指导监测系统改进的方向。最后,我们的系统方法也可以进行调整,以帮助改进对其他疾病的监测。