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Abstract
The effectiveness of official warning dissemination and interpretation determines the adoption of protective actions in response to hurricane threat. This paper describes the development of a conceptual warning diffusion model that articulates the whole process of the hurricane warning diffusion and individual decision-making, drawing on emergency management and social science bodies of literature. This conceptual model is then partially encoded into a NetLogo agent-based simulation model to demonstrate the effects of various warning diffusion components on evacuation decisions for areas of interest. The translation of the conceptual model into agent-based simulations can inform the coastal engineering and science communities of the importance of communicating risk information to the public, and also helps to identify future research needed to illuminate hurricane risk communication pathways.References
Arlikatti, S., M.K. Lindell, and C. Prater. 2007. Perceived stakeholder role relationships and adoption of seismic hazard adjustments. International Journal of Mass Emergencies and Disasters, 25(3), 218–256.
Bostrom, A., R. Morss, J.K. Lazo, J. Demuth, and H. Lazrus. 2018. Eyeing the storm: How residents of coastal Florida see hurricane forecasts and warnings. International Journal of Disaster Risk Reduction, 30, 105-119.
Chen C., M.K. Lindell, E.M. Yeates, M.J. Shaw, and W. Shao. 2023. Hurricane Risk Information Dissemination Model: Theoretical formulation and evidence. Natural Hazards Review. (in review).
Cordasco, K.M., D.P. Eisenman, D.C. Glik, J.F. Golden, and S.M. Asch. 2007. “They blew the levee": Distrust of authorities among Hurricane Katrina evacuees. Journal of Health Care for the Poor and Underserved, 18(2), 277-282.
DeYoung, S.E., T. Wachtendorf, A.K. Farmer, and S.C. Penta. 2016. NOAA radios and neighbourhood networks: Demographic factors for channel preference for hurricane evacuation information. Journal of Contingencies and Crisis Management, 24(4), 275-285.
Dillon, R.L., C.H. Tinsley, and M. Cronin. 2011. Why near-miss events can decrease an individual’s protective response to hurricanes: Near-misses and protective responses to hurricanes. Risk Analysis, 31(3), 440–449. https://doi.org/10.1111/j.1539-6924.2010.01506.x
Dillon, R.L., and C.H. Tinsley. 2016. Near-miss events, risk messages, and decision making. Environment Systems and Decisions, 36(1), 34–44. https://doi.org/10.1007/s10669-015-9578-x
Dong, H., M. Halem, and S. Zhou. 2013. Social media data analytics applied to Hurricane Sandy. International Conference on Social Computing (pp. 963-966). IEEE.
Dow, K., and S.L. Cutter. 1998. Crying Wolf: Repeat responses to hurricane evacuation orders. Coastal Management, 26(4), 237–252. https://doi.org/10.1080/08920759809362356
Eisenman, D.P., K.M. Cordasco, S. Asch, J.F. Golden, and D. Glik. 2007. Disaster planning and risk communication with vulnerable communities: lessons from Hurricane Katrina. American Journal of Public Health, 97 (Supplement_1), S109-S115
Ersing, R., C. Pearce, J.M. Collins, M.E. Saunders, and A. Polen. 2020. Geophysical and social influences on evacuation decision-making: The case of Hurricane Irma. School of Geosciences Faculty and Staff Publications. 2230. https://digitalcommons.usf.edu/geo_facpub/2230.
Gao, S., and Y. Wang. 2021. Assessing the impact of geo-targeted warning messages on residents’ evacuation decisions before a hurricane using agent-based modeling. Natural Hazards, 107(1), 123-146.
Gladwin, H., J.K. Lazo, B.H. Morrow, W.G. Peacock, and H.E. Willoughby. 2007. Social science research needs for the hurricane forecast and warning system. Natural Hazards Review, 8(3), 87-95.
Hao, F., and W. Shao. 2022. Understanding the influence of political orientation, social network, and economic recovery on COVID-19 vaccine uptake among Americans. Vaccine, 40(14), 2191–2201. https://doi.org/10.1016/j.vaccine.2022.02.066
Harris, A., P. Roebber, and R. Morss. 2022. An agent-based modeling framework for examining the dynamics of the hurricane-forecast-evacuation system. International Journal of Disaster Risk Reduction, 67, 102669. https://doi.org/10.1016/j.ijdrr.2021.102669
Hasan, S., R. Mesa-Arango, and S. Ukkusuri. 2013. A random-parameter hazard-based model to understand household evacuation timing behavior. Transportation Research Part C: Emerging Technologies, 27, 108-116.
Hasan, S., and S. Ukkusuri. 2011. A threshold model of social contagion process for evacuation decision making. Transportation Research Part B: Methodological, 45(10), 1590-1605.
Hasan, S., and S. Ukkusuri. 2013. Social contagion process in informal warning networks to understand evacuation timing behavior. Journal of Public Health Management and Practice, 19, S68-S69, DOI: 10.1097/PHH.0b013e31828f1a19
Huang, S.-K., M.K. Lindell, C.S. Prater, H.-C. Wu, and L.K. Siebeneck. 2012. Household evacuation decision making in response to Hurricane Ike. Natural Hazards Review, 13(4), 283–296. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000074
Huang, S.-K., M.K. Lindell, and C.S. Prater. 2016. Who leaves and who stays? A review and statistical meta-analysis of hurricane evacuation studies. Environment and Behavior, 48(8), 991–1029. https://doi.org/10.1177/0013916515578485
Huang, S.-K., M.K. Lindell, and C.S. Prater. 2017a. Multistage model of hurricane evacuation decision: Empirical study of Hurricanes Katrina and Rita. Natural Hazards Review, 18(3), 05016008. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000237
Huang, S-K., M.K. Lindell, H-L. Wei, and C.D. Samuelson. 2017b. Perceptions, behavioral expectations, and implementation timing for response actions in a hurricane emergency. Natural Hazards, 88(1), 533-558. DOI 10.1007/s11069-017-2877-4.
Katada, T., Y. Oikawa, and T. Tanaka. 1999. Development of simulation model for evaluating the efficiency of disaster information dissemination. Doboku Gakkai Ronbunshu, (625), 1–13. (In Japanese). https://doi.org/10.2208/jscej.1999.625.
Kim, S., W. Shao, and J. Kam. 2019. Spatiotemporal patterns of US drought awareness. Palgrave Communications, 5(1), 107. https://doi.org/10.1057/s41599-019-0317-7.
King J.A. and G. Cowlishaw. 2009. Leaders, followers, and group decision-making. Communicative and Integrative Biology, 2:2, 147-150.
Koll, C., M.K. Lindell, C. Chen, and H. Wang. 2023. Emergency warning dissemination in a multiplex social network. Journal of Artificial Societies and Social Simulation, 26(1) 7. Doi: 10.18564/jasss.4946
Lazo, J.K., A. Bostrom, R.E. Morss, J.L. Demuth, and H. Lazrus. 201). Factors affecting hurricane evacuation intentions. Risk Analysis, 35(10), 1837-1857.
Linardi, S. 2016. Peer coordination and communication following disaster warnings: An experimental framework. Safety Science, 90, 24-32.
Lindell, M. K. 2018. Communicating Imminent Risk. In H. Rodríguez, W. Donner, and J. E. Trainor (Eds.), Handbook of Disaster Research (pp. 449–477). Springer International Publishing. https://doi.org/10.1007/978-3-319-63254-4_22
Lindell, M.K., S. Arlikatti. and S-K. Huang. 2019. Immediate behavioral response to the June 17, 2013 flash floods in Uttarakhand, North India. International Journal of Disaster Risk Reduction, 34, 129-146. DOI: 10.1016/j.ijdrr.2018.11.011.
Lindell, M.K., J.C. Lu, and C.S. Prater. 2005. Household decision making and evacuation in response to Hurricane Lili. Natural Hazards Review, 6, 171-179.
Lindell, M.K., P. Murray-Tuite, B. Wolshon, and E.J. Baker. 2019b. Large-scale Evacuation: The Analysis, Modeling, and Management of Emergency Relocation from Hazardous Areas. New York: Routledge.
Lindell, M.K., and R.W. Perry. 1992. Behavioral Foundations of Community Emergency Planning. (pp. xi, 309). Washington DC: Hemisphere.
Lindell, M.K., and R.W. Perry. 2004. Communicating Environmental Risk in Multiethnic Communities. SAGE Publications, Inc. https://doi.org/10.4135/9781452229188
Lindell, M.K., and R.W. Perry. 2012. The protective action decision model: Theoretical modifications and additional evidence. Risk Analysis, 32(4), 616–632. https://doi.org/10.1111/j.1539-6924.2011.01647.x
Lindell, M.K. and C.S. Prater. 2007a. A hurricane evacuation management decision support system (EMDSS). Natural Hazards, 40, 627-634.
Lindell, M.K., and C.S. Prater. 2007b. Critical behavioral assumptions in evacuation time estimate analysis for private vehicles: examples from hurricane research and planning. Journal of Urban Planning and Development, 133(1), 18–29. https://doi.org/10.1061/(ASCE)0733-9488(2007)133:1(18)
Lindell, M.K. and C.S. Prater. 2010. Tsunami preparedness on the Oregon and Washington coast: Recommendations for research. Natural Hazards Review, 11, 69-81.
Mileti, D. S., and J.H. Sorensen. 1987. Natural hazards and precautionary behavior. In N.D. Weinstein (ed.). Taking Care: Understanding and Encouraging Self-protective Behavior (189-207). New York: Cambridge University Press.
Lindell, M.K., J.H. Sorensen, E.J. Baker, and W.P. Lehman. 2020. Community response to hurricane threat: Estimates of household evacuation preparation time distributions. Transportation Research D: Transport and Environment, 85, 102457. DOI: 10.1016/j_trd.2020.102457.
Lindell, M.K., J.H. Sorensen, E.J. Baker, and W.P. Lehman. 2021. Community response to hurricane threat: Estimates of warning diffusion time distributions. Natural Hazards Review, 22(2), 04021007. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000456
Mileti, D.S., and J.H. Sorensen. 1990. Communication of emergency public warnings: A social science perspective and state-of-the-art assessment (ORNL-6609). https://doi.org/10.2172/6137387
National Hurricane Center. (n.d.). Saffir-Simpson Hurricane Wind Scale. Retrieved April 11, 2022, from https://www.nhc.noaa.gov/aboutsshws.php
Perry, R.W., M.K. Lindell, and M.R. Greene. 1981. Evacuation planning in emergency management. Lexington MA: Lexington Books.
Polen, A., J. Collins, E. Dunn, S. Murphy, I. Jernigan, and K. McSweeney. 2022. The effect of COVID-19 vaccination on evacuation behavior during Hurricane Ida. Natural Hazards Center Quick Response Grant Report Series, 344. Boulder, CO: Natural Hazards Center, University of Colorado Boulder. Available at: https://hazards.colorado.edu/quick-response-report/the-effect-of-covid-19-vaccination-on-evacuation-behavior-during-hurricane-ida.
Rogers, G.O., and J.H. Sorensen. 1988. Diffusion of emergency warnings. The Environmental Professional, 10, 281–294.
Shao, W., and F. Hao. 2021. Understanding American public support for COVID-19 risk mitigation: The role of political orientation, socio-demographic characteristics, personal concern, and experience. International Journal of Public Health, 66. https://doi.org/10.3389/ijph.2021.160403
Shao, W., B.D. Keim, J.C. Garand, and L.C. Hamilton. 2014. Weather, climate, and the economy: Explaining risk perceptions of global warming, 2001–2010. Weather, Climate, and Society, 6(1), 119–134. https://doi.org/10.1175/WCAS-D-13-00029.1
Shao, W., S. Xian, N. Lin, and M.J. Small. 2017a. A sequential model to link contextual risk, perception, and public support for flood adaptation policy. Water Research, 122, 216–225. https://doi.org/10.1016/j.watres.2017.05.072
Sorensen, J. H. 2000. Hazard warning systems: Review of 20 years of progress. Natural Hazards Review, 1(2), 119–125. https://doi.org/10.1061/(ASCE)1527-6988(2000)1:2(119)
Sorensen, J.H., M.K. Lindell, E.J. Baker. and W.P. Lehman. 2020. Community response to hurricane threat: Estimates of warning issuance time distributions. Weather, Climate and Society, 12, 837-846. DOI: 10.1175/WCAS-D-20-0031.s1
Sorensen, J.H., and B. Richardson. 1984. Risk and uncertainty as determinants of human response in emergencies: Evacuation at TMI reexamined. In Proceeding of the Annual Meeting of the Society for Risk Analysis, Knoxville, TN.
Sorensen, J.H., and B.V. Sorensen. 2007. Community Processes: Warning and Evacuation. In H. Rodríguez, E. L. Quarantelli, and R. R. Dynes (Eds.), Handbook of Disaster Research (pp. 183–199). Springer. https://doi.org/10.1007/978-0-387-32353-4_11
Wei, H.-L., M.K. Lindell, C.S. Prater, J. Wei, F. Wang, and Y.G. Ge. 2018. Perceived stakeholder characteristics and protective action for influenza emergencies: A comparative study of respondents in the United States and China. International Journal of Mass Emergencies and Disasters, 36, 52–70.
Wilensky, U. 1999. NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University. Evanston, IL.
Wolfram, 2013. Data science of the Facebook world. url: writings.stephenwolfram.com/2013/04/data-science-of-the-facebook-world/.
Yin, W., P. Murray-Tuite, S.V. Ukkusuri, and H. Gladwin. 2014. An agent-based modeling system for travel demand simulation for hurricane evacuation. Transportation Research Part C: Emerging Technologies, 42, 44-59.
Yin, W., P. Murray-Tuite, S.V. Ukkusuri, and H. Gladwin. 2016. Modeling shadow evacuation for hurricanes with random-parameter logit model. Transportation Research Record, 2599(1), 43-51.
Zhang, N., H. Huang, B. Su, J. Zhao, and B. Zhang. 2014. Information dissemination analysis of different media towards the application for disaster pre-warning. PLoS ONE, 9(5), e98649. https://doi.org/10.1371/journal.pone.0098649
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Copyright (c) 2023 Elissa M. Yeates, Chen Chen, Michael K. Lindell, Wanyun Shao, Ce’Ne Harris, Evan Cass