Edward W. Chan

How can we strengthen the evidence base in public health preparedness

The lack of frequent real-world opportunities to study preparedness for large-scale public health emergencies has hindered the development of an evidence base to support best practices, performance measures, standards, and other tools needed to assess and improve the nations multibillion dollar investment in public health preparedness. In this article, we argue that initial funding priorities for public health systems research on preparedness should focus on using engineering-style methods to identify core preparedness processes, developing novel data sources and measures based on smaller-scale proxy events, and developing performance improvement approaches to support the translation of research into practice within the wide variety of public health systems found in the nation.

Developing national standards for public health emergency preparedness with a limited evidence base.

OBJECTIVE The paucity of evidence and wide variation among communities creates challenges for developing congressionally mandated national performance standards for public health preparedness. Using countermeasure dispensing as an example, we present an approach for developing standards that balances national uniformity and local flexibility, consistent with the quality of evidence available. METHODS We used multiple methods, including a survey of community practices, mathematical modeling, and expert panel discussion. RESULTS The article presents recommended dispensing standards, along with a general framework that can be used to analyze tradeoffs involved in developing other preparedness standards. CONCLUSIONS Standards can be developed using existing evidence, but would be helped immensely by a stronger evidence base.

Strategies to improve global influenza surveillance: A decision tool for policymakers

BackgroundGlobal pandemic influenza preparedness relies heavily on public health surveillance, but it is unclear that current surveillance fully meets pandemic preparedness needs.MethodsWe 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.ResultsWe 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.ConclusionOur 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.