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A Synergistic Approach to Data-Driven Response Planning

Published online by Cambridge University Press:  09 March 2020

Marty O’Neill ,
Michael Poole  and
Armin R. Mikler
Marty O’Neill*
Affiliation:
University of North Texas Center for Computational Epidemiology and Response Analysis, Denton, TX
Michael Poole
Affiliation:
Texas Department of State Health Services, Austin, TX
Armin R. Mikler
Affiliation:
University of North Texas Center for Computational Epidemiology and Response Analysis, Denton, TX
*
Correspondence and reprint requests to Marty O’Neill, 1155 Union Circle #310559, Denton, TX76203-5017 (e-mail: [email protected]).
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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 planningmedical countermeasure dispensingmedical countermeasure distributionparticipatory developmenttranslational public health research
Type
Concepts in Disaster Medicine
Information
Disaster Medicine and Public Health Preparedness , Volume 15 , Issue 2 , April 2021 , pp. 232 - 238
Copyright
Copyright © 2020 Society for Disaster Medicine and Public Health, Inc.

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References

REFERENCES

Avchen, RN, Le Blanc, TT, Kosmos, C. Medical countermeasures: mission, method, and management. Am J Public Health. 2018;108:S172. doi: 10.2105/AJPH.2018.304686.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. Receiving, distributing, and dispensing strategic national stockpile assets: a guide for preparedness, Version 10.02; 2006.Google Scholar
Burel, G. Technology for improved public health preparedness and response. DomPrep J. 2016;12(9):16-19.Google Scholar
Griffith, JM, Carpender, SK, Crouch, JA, Quiram, BJ. A public health hazard mitigation planning process. J Public Health Manag Pract. 2014;20(Suppl 5):69-75. doi: 10.1097/PHH.0000000000000064.CrossRefGoogle ScholarPubMed
Lee, EK, Chen, C-H, Pietz, F, Benecke, B. Modeling and optimizing the public-health infrastructure for emergency response. Interfaces (Providence). 2009;39(5):476-490. doi: 10.1287/inte.1090.0463.CrossRefGoogle Scholar
Dean, B, Bagwell, DA, Dora, V, et al. Los Angeles County Department of Public Health’s health hazard assessment: putting the “health” into hazard assessment. J Public Health Manag Pract. 2013;19(5 Suppl 2):84-90. doi: 10.1097/PHH.0b013e3182928e63.CrossRefGoogle ScholarPubMed
Ramisetty-Mikler, S, Mikler, AR, O’Neill, M, Komatz, SJ. Conceptual framework and quantification of population vulnerability for effective emergency response planning. J Emerg Manag. 2015;13(3):227-238. doi: 10.5055/jem.2015.0236.CrossRefGoogle ScholarPubMed
O’Neill, M II, Indrakanti, S, Schneider, T, Mikler, AR. RE-PLAN: an extensible software architecture to facilitate disaster response planning. IEEE Trans Syst Man Cybern Syst. 2014;44(12):1569-1583.CrossRefGoogle ScholarPubMed
Jimenez, T, Mikler, AR, Tiwari, C. A novel space partitioning algorithm to improve current practices in facility placement. IEEE Trans Syst Man Cybern A Syst Hum. 2012;42(5):1194-1205. doi: 10.1109/TSMCA.2012.2183360.CrossRefGoogle ScholarPubMed
Willis, HH, Nelson, C, Shelton, SR, et al. Initial evaluation of the cities readiness initiative TR-640-CDC. Santa Monica, CA. 2009. http://www.rand.org. Accessed April 18, 2011.Google Scholar
Chervenic, M. Assessment of MCM response capabilities to an anthrax attack and impact on recovery. Presentation; 2012.Google Scholar
Smith, LS, Wilkins, N, Marshall, SW, et al. The power of academic–practitioner collaboration to enhance science and practice integration: injury and violence prevention case studies. J Public Health Manag Pract. 2018;24(1):S67-S74. doi: 10.1097/PHH.0000000000000675.CrossRefGoogle ScholarPubMed
Gwalani, H, Mikler, AR, Ramisetty-Mikler, S, O’Neill, M. Collection and integration of multi-spatial and multi-type data for vulnerability analysis in emergency response plans. In: Wohlgemuth, V, Fuchs-Kittowski, F, Wittmann, J, eds. Advances and New Trends in Environmental Informatics. Progress in IS. Cham: Springer; 2017.10.1007/978-3-319-44711-7_8CrossRefGoogle Scholar
Kellermann, AL, Hatchett, R, Smith, K, et al. Public health preparedness research. J Public Health Manag Pract. 2013;19:S6-S8. doi: 10.1097/phh.0b013e318293f6c9.Google Scholar
Pagaoa, M, Leblanc, TT, Renard, P, et al. Performance of point of dispensing setup drills for distribution of medical countermeasures: United States and Territories, 2012–2016. Am J Public Health. 2018;108:S221-S223. doi: 10.2105/AJPH.2018.304474.CrossRefGoogle ScholarPubMed
England, C. The United States medical countermeasure enterprise: a broken link in US biopreparedness. J Homel Secur Emerg Manag. 2014;11(1):117-130. doi: 10.1515/jhsem-2013-0043.Google Scholar
Bauer, TN, Erdogan, B. Organizational socialization: the effective onboarding of new employees. In: Zedeck, S, ed. APA Handbooks in Psychology®. APA Handbook of Industrial and Organizational Psychology, Vol. 3. Maintaining, Expanding, and Contracting the Organization. Washington, DC: American Psychological Association; 2011:51-64.10.1037/12171-002CrossRefGoogle Scholar
Brownson, RC, Eyler, AA, Harris, JK, et al. Getting the word out: new approaches for disseminating public health science. J Public Health Manag Pract. 2018;24(2):102-111. doi: 10.1097/PHH.0000000000000673.CrossRefGoogle ScholarPubMed