Data needs and models for the opioid epidemic

阿片类药物流行所需的数据和模型

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Abstract

The evolving nature of the opioid epidemic and continued increases in overdose deaths highlight a need for fundamental change in the collection and use of surveillance data to link them to implementation of effective service, treatment, and prevention approaches. Yet at present, the quality and timeliness of US surveillance data often limits data-driven approaches. We review current information needs, summarize limitations of existing data, propose complementary surveillance resources, and provide examples of promising approaches designed to meet the needs of data end-users. We conclude that there is a need for an approach that focuses on the needs of data end-users, such as public health systems leaders, policy makers, public, nonprofit and prepaid healthcare systems, and other systems, such as the justice system. Such an approach, which may require investments in new infrastructure, should prioritize improvements in data timeliness, sample representativeness, database linkage, and increased flexibility to adapt to shifts in the environment, while preserving the privacy of survey participants. Use of simulations, distributed research and data networks, alternative data sources, such as wastewater or digital data collection and use of blockchain technology, are some of promising avenues toward an improved and more user-centered surveillance system.

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