A Synergistic Approach to Data-Driven Response Planning

Disaster Med Public Health Prep. 2021 Apr;15(2):232-238. doi: 10.1017/dmp.2019.162. Epub 2020 Mar 9.

Abstract

Public health practitioners face challenging, potentially high-consequence, problems that require computational support. Available computational tools may not adequately fit these problems, thus forcing practitioners to rely on qualitative estimates when making critical decisions. Scientists at the Center for Computational Epidemiology and Response Analysis and practitioners from the Texas Department of State Health Services (TXDSHS) have established a participatory development cycle where public health practitioners work closely with academia to foster the development of data-driven solutions for specific public health problems and to translate these solutions to practice. Tools developed through this cycle have been deployed at TXDSHS offices where they have been used to refine and enhance the region's medical countermeasure distribution and dispensing capabilities. Consequently, TXDSHS practitioners planning for a 49-county region in North Texas have achieved a 29% reduction in the number of points of dispensing required to complete dispensing to the region within time limitations. Further, an entire receiving, staging, and storing site has been removed from regional plans, thus freeing limited resources (eg, personnel, security, and infrastructure) for other uses. In 2018, planners from Southeast Texas began using these tools to plan for a multi-county, full-scale exercise which was scheduled to be conducted in October 2019.

Keywords: data-driven response planning; medical countermeasure dispensing; medical countermeasure distribution; participatory development; translational public health research.