A Synergistic Approach to Data-Driven Response Planning
| Autor: | Marty O’Neill, Armin R. Mikler, Michael Poole |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
030505 public health Process management Computer science Public health Response analysis Public Health Environmental and Occupational Health Plan (drawing) Article Participatory development Data-driven 03 medical and health sciences 0302 clinical medicine Countermeasure Work (electrical) medicine 030212 general & internal medicine Computational epidemiology 0305 other medical science |
| Zdroj: | Disaster Med Public Health Prep |
| ISSN: | 1938-744X 1935-7893 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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